sha
stringlengths 40
40
| text
stringlengths 1
13.4M
| id
stringlengths 2
117
| tags
sequencelengths 1
7.91k
| created_at
stringlengths 25
25
| metadata
stringlengths 2
875k
| last_modified
stringlengths 25
25
| arxiv
sequencelengths 0
25
| languages
sequencelengths 0
7.91k
| tags_str
stringlengths 17
159k
| text_str
stringlengths 1
447k
| text_lists
sequencelengths 0
352
| processed_texts
sequencelengths 1
353
| tokens_length
sequencelengths 1
353
| input_texts
sequencelengths 1
40
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
11f7b03884f6b4f2a97cecae2c8eb30caca43c4e | ## KnowledgeMath Benchmark Description
**KnowledgeMath** is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions.
**KnowledgeMath** includes **1200 QA examples** across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.
- Paper: https://arxiv.org/abs/2311.09797
- Code: https://github.com/yale-nlp/KnowledgeMath
- Leaderboard: will be released soon!
## KnowledgeMath Dataset Information
All the data examples were divided into two subsets: *validation* and *test*.
- **validation**: 200 examples used for model development, validation, or for those with limited computing resources.
- **test**: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.
You can download this dataset by the following command:
```python
from datasets import load_dataset
dataset = load_dataset("yale-nlp/KnowledgeMath")
# print the first example on the validation set
print(dataset["validation"][0])
# print the first example on the test set
print(dataset["test"][0])
```
The dataset is provided in json format and contains the following attributes:
```json
{
"question_id": [string] The question id,
"question": [string] The question text,
"tables": [list] List of Markdown-format tables associated with the question,
"python_solution": [string] Python-format and executable solution by financial experts. The code is written in a clear and executable format, with well-named variables and a detailed explanation,
"ground_truth": [integer] Executed result of `python solution`, rounded to three decimal places,
"topic": [string] The related financial area of the question,
"knowledge_terms": [list] List of knowledge terms in our constructed knowledge bank that is necessary to answer the given question. We will release this feature upon paper publication
}
```
## Automated Evaluation
To automatically evaluate a model on **KnowledgeMath**, please refer to our GitHub repository [here](https://github.com/yale-nlp/KnowledgeMath).
## Citation
If you use the **KnowledgeMath** dataset in your work, please kindly cite the paper:
```
@misc{zhao2023knowledgemath,
title={KnowledgeMath: Knowledge-Intensive Math Word Problem Solving in Finance Domains},
author={Yilun Zhao and Hongjun Liu and Yitao Long and Rui Zhang and Chen Zhao and Arman Cohan},
year={2023},
eprint={2311.09797},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
``` | yilunzhao/KnowledgeMath | [
"license:mit",
"arxiv:2311.09797",
"region:us"
] | 2024-01-02T19:07:39+00:00 | {"license": "mit"} | 2024-01-06T02:53:53+00:00 | [
"2311.09797"
] | [] | TAGS
#license-mit #arxiv-2311.09797 #region-us
| ## KnowledgeMath Benchmark Description
KnowledgeMath is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions.
KnowledgeMath includes 1200 QA examples across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.
- Paper: URL
- Code: URL
- Leaderboard: will be released soon!
## KnowledgeMath Dataset Information
All the data examples were divided into two subsets: *validation* and *test*.
- validation: 200 examples used for model development, validation, or for those with limited computing resources.
- test: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.
You can download this dataset by the following command:
The dataset is provided in json format and contains the following attributes:
## Automated Evaluation
To automatically evaluate a model on KnowledgeMath, please refer to our GitHub repository here.
If you use the KnowledgeMath dataset in your work, please kindly cite the paper:
| [
"## KnowledgeMath Benchmark Description\n\nKnowledgeMath is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions. \nKnowledgeMath includes 1200 QA examples across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.\n\n- Paper: URL\n- Code: URL\n- Leaderboard: will be released soon!",
"## KnowledgeMath Dataset Information\nAll the data examples were divided into two subsets: *validation* and *test*.\n\n- validation: 200 examples used for model development, validation, or for those with limited computing resources.\n- test: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.\n\nYou can download this dataset by the following command:\n\n\n\nThe dataset is provided in json format and contains the following attributes:",
"## Automated Evaluation\n\nTo automatically evaluate a model on KnowledgeMath, please refer to our GitHub repository here.\n\nIf you use the KnowledgeMath dataset in your work, please kindly cite the paper:"
] | [
"TAGS\n#license-mit #arxiv-2311.09797 #region-us \n",
"## KnowledgeMath Benchmark Description\n\nKnowledgeMath is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions. \nKnowledgeMath includes 1200 QA examples across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.\n\n- Paper: URL\n- Code: URL\n- Leaderboard: will be released soon!",
"## KnowledgeMath Dataset Information\nAll the data examples were divided into two subsets: *validation* and *test*.\n\n- validation: 200 examples used for model development, validation, or for those with limited computing resources.\n- test: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.\n\nYou can download this dataset by the following command:\n\n\n\nThe dataset is provided in json format and contains the following attributes:",
"## Automated Evaluation\n\nTo automatically evaluate a model on KnowledgeMath, please refer to our GitHub repository here.\n\nIf you use the KnowledgeMath dataset in your work, please kindly cite the paper:"
] | [
20,
105,
109,
46
] | [
"passage: TAGS\n#license-mit #arxiv-2311.09797 #region-us \n## KnowledgeMath Benchmark Description\n\nKnowledgeMath is a knowledge-intensive dataset focused on mathematical reasoning within the domain of finance. It requires the model to comprehend specialized financial terminology and to interpret tabular data presented in the questions. \nKnowledgeMath includes 1200 QA examples across 7 key areas in finance. These examples were collected from financial experts and feature detailed solution annotations in Python format.\n\n- Paper: URL\n- Code: URL\n- Leaderboard: will be released soon!## KnowledgeMath Dataset Information\nAll the data examples were divided into two subsets: *validation* and *test*.\n\n- validation: 200 examples used for model development, validation, or for those with limited computing resources.\n- test: 1000 examples for standard evaluation. We will not publicly release the annotated solution and answer for the test set.\n\nYou can download this dataset by the following command:\n\n\n\nThe dataset is provided in json format and contains the following attributes:## Automated Evaluation\n\nTo automatically evaluate a model on KnowledgeMath, please refer to our GitHub repository here.\n\nIf you use the KnowledgeMath dataset in your work, please kindly cite the paper:"
] |
61414881fbf6934df1a3efc82ed048c8411da2cb | # Dataset Card for "poetica"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | mii-llm/poetica | [
"region:us"
] | 2024-01-02T19:17:36+00:00 | {"dataset_info": {"features": [{"name": "title", "dtype": "string"}, {"name": "author", "dtype": "string"}, {"name": "author_info", "dtype": "string"}, {"name": "poem", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 3014606, "num_examples": 2241}], "download_size": 1783194, "dataset_size": 3014606}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-02T19:17:39+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "poetica"
More Information needed | [
"# Dataset Card for \"poetica\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"poetica\"\n\nMore Information needed"
] | [
6,
13
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"poetica\"\n\nMore Information needed"
] |
e310a0e2acfab9456a48ebbe263e854f7576e4a9 | # Dataset Card for Phi-2 Alignment
### Dataset Description
**Creator:** Mahdi Ranjbar
- **Notebook:** [Colab Notebook](https://colab.research.google.com/drive/10ZSi2806svkVRpQlX75Rovz9PDninDia?usp=sharing)
#### Dataset Summary
This dataset was developed for the alignment internship take-home assignment with the goal of assessing alignment
across three dimensions: Helpfulness, Honesty, and Harmlessness (3H). I crafted 10 prompts covering various tasks
and generated 8 answers for each prompt using the new Microsoft Phi-2 model.
Subsequently, I employed the Open Assistant reward model to evaluate the quality of each answer. The dataset is created
by selecting the answer with the highest score for each prompt.
#### Language
The language of dataset is English.
#### Uses
This dataset can be used to fine-tune a better model or improve the quality of answers in deployment.
| mahdi-ranjbar/phi2-alignment | [
"language:en",
"region:us"
] | 2024-01-02T19:18:44+00:00 | {"language": ["en"], "pretty_name": "b", "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 7660, "num_examples": 10}], "download_size": 12858, "dataset_size": 7660}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T01:33:48+00:00 | [] | [
"en"
] | TAGS
#language-English #region-us
| # Dataset Card for Phi-2 Alignment
### Dataset Description
Creator: Mahdi Ranjbar
- Notebook: Colab Notebook
#### Dataset Summary
This dataset was developed for the alignment internship take-home assignment with the goal of assessing alignment
across three dimensions: Helpfulness, Honesty, and Harmlessness (3H). I crafted 10 prompts covering various tasks
and generated 8 answers for each prompt using the new Microsoft Phi-2 model.
Subsequently, I employed the Open Assistant reward model to evaluate the quality of each answer. The dataset is created
by selecting the answer with the highest score for each prompt.
#### Language
The language of dataset is English.
#### Uses
This dataset can be used to fine-tune a better model or improve the quality of answers in deployment.
| [
"# Dataset Card for Phi-2 Alignment",
"### Dataset Description\nCreator: Mahdi Ranjbar\n\n- Notebook: Colab Notebook",
"#### Dataset Summary\nThis dataset was developed for the alignment internship take-home assignment with the goal of assessing alignment\nacross three dimensions: Helpfulness, Honesty, and Harmlessness (3H). I crafted 10 prompts covering various tasks\nand generated 8 answers for each prompt using the new Microsoft Phi-2 model.\nSubsequently, I employed the Open Assistant reward model to evaluate the quality of each answer. The dataset is created\nby selecting the answer with the highest score for each prompt.",
"#### Language\nThe language of dataset is English.",
"#### Uses\nThis dataset can be used to fine-tune a better model or improve the quality of answers in deployment."
] | [
"TAGS\n#language-English #region-us \n",
"# Dataset Card for Phi-2 Alignment",
"### Dataset Description\nCreator: Mahdi Ranjbar\n\n- Notebook: Colab Notebook",
"#### Dataset Summary\nThis dataset was developed for the alignment internship take-home assignment with the goal of assessing alignment\nacross three dimensions: Helpfulness, Honesty, and Harmlessness (3H). I crafted 10 prompts covering various tasks\nand generated 8 answers for each prompt using the new Microsoft Phi-2 model.\nSubsequently, I employed the Open Assistant reward model to evaluate the quality of each answer. The dataset is created\nby selecting the answer with the highest score for each prompt.",
"#### Language\nThe language of dataset is English.",
"#### Uses\nThis dataset can be used to fine-tune a better model or improve the quality of answers in deployment."
] | [
10,
11,
18,
121,
11,
30
] | [
"passage: TAGS\n#language-English #region-us \n# Dataset Card for Phi-2 Alignment### Dataset Description\nCreator: Mahdi Ranjbar\n\n- Notebook: Colab Notebook#### Dataset Summary\nThis dataset was developed for the alignment internship take-home assignment with the goal of assessing alignment\nacross three dimensions: Helpfulness, Honesty, and Harmlessness (3H). I crafted 10 prompts covering various tasks\nand generated 8 answers for each prompt using the new Microsoft Phi-2 model.\nSubsequently, I employed the Open Assistant reward model to evaluate the quality of each answer. The dataset is created\nby selecting the answer with the highest score for each prompt.#### Language\nThe language of dataset is English.#### Uses\nThis dataset can be used to fine-tune a better model or improve the quality of answers in deployment."
] |
ca893606ec231e138756276c1ba06b2d3c1d61ef |
# Description
Dataset listing 27,328 languages and dialects (also includes macrolanguage names).
For each language, either the [ISO 639 code](https://www.iso.org/iso-639-language-code), the [Glottolog code](https://glottolog.org/meta/downloads) or both are provided.
# Columns
- `English_Name`: Language name in English (e.g. `"French"`).
- `Native_Name`: If value is not `0`, corresponds to the name of the language by native speakers (e.g. `"Français"`) which may have been found in Wikipedia's `nativename` field.
- `Glottocode`: The language tag in the Glottolog convention (e.g. `stan1290`).
- `near_ISO6393`: the ISO 639-3 code closest to the Glottolog convention (e.g. `fra`) This information comes from [Glottolog](https://glottolog.org/meta/downloads) and may therefore be incomplete compared with column `639-3` from [ISO](https://www.iso.org/iso-639-language-code).
- `639-3`: The language tag in the ISO 639-3 convention (e.g. `fra`).
- `639-2_B`: The language tag in the ISO 639-2_B (B for bibliographic) convention (e.g. `fre`).
- `639-2_T`: The language tag in the ISO 639-2_T (T for terminological) convention (e.g. `fra`).
- `639-1`: The language tag in the ISO 639-1 convention (e.g. `fr`).
- `Scope`: If value is not `0`, `I` for an individual language (e.g. "French"), 'M' for a macrolanguage, 'S' for special i.e non-language codes (e.g. "und" for Undetermined)).
- `Language_Type`: If value is not `0`, `A` for ancient language that went extinct long ago (e.g. `got` for Gothic), `C` for constructed i.e artificial languages, excluding programming languages (e.g. `epo` for Esperanto), `E` for extinct i.e. language that went extinct recently (e.g. `rbp` for Barababaraba), `H` for historical i.e. extinct language distinct from modern languages that descended from it (e.g. `ofs` for Old Frisian), `L` for living i.e. currently spoken language (e.g. `fra` for French), `S` for special i.e. non-language codes (e.g. `und` for Undetermined).
- `#L1_Speakers`: Indicates a (rounded) estimate of the number of speakers (L1) per language; the estimate comes from [Writing System and Speaker Metadata for 2,800+ Language Varieties](https://aclanthology.org/2022.lrec-1.538/). | lbourdois/language_tags | [
"size_categories:1K<n<10K",
"language:aal",
"language:aap",
"language:aar",
"language:abj",
"language:abo",
"language:abq",
"language:abw",
"language:aby",
"language:abz",
"language:aci",
"language:ack",
"language:acl",
"language:acn",
"language:acr",
"language:acv",
"language:ade",
"language:adr",
"language:adt",
"language:ady",
"language:aek",
"language:aeq",
"language:aew",
"language:aey",
"language:afd",
"language:afi",
"language:afn",
"language:afo",
"language:afz",
"language:agc",
"language:age",
"language:agg",
"language:agh",
"language:agl",
"language:ago",
"language:agq",
"language:agr",
"language:agw",
"language:agx",
"language:ahg",
"language:aho",
"language:aik",
"language:ail",
"language:aio",
"language:akj",
"language:akk",
"language:akl",
"language:akm",
"language:akp",
"language:akv",
"language:akx",
"language:aky",
"language:akz",
"language:ala",
"language:ale",
"language:alf",
"language:alq",
"language:alt",
"language:alz",
"language:ame",
"language:ami",
"language:amj",
"language:amu",
"language:amv",
"language:ana",
"language:anh",
"language:ani",
"language:ann",
"language:ano",
"language:anv",
"language:any",
"language:aoc",
"language:aog",
"language:aoi",
"language:aoj",
"language:aos",
"language:aox",
"language:aoz",
"language:apn",
"language:apq",
"language:apt",
"language:apw",
"language:apz",
"language:aqc",
"language:aqm",
"language:aqp",
"language:aqt",
"language:arg",
"language:arh",
"language:ari",
"language:ark",
"language:arl",
"language:arp",
"language:arw",
"language:asb",
"language:asc",
"language:asm",
"language:ass",
"language:ast",
"language:asx",
"language:atb",
"language:atj",
"language:atq",
"language:atu",
"language:atv",
"language:atx",
"language:auc",
"language:aug",
"language:auh",
"language:auk",
"language:aup",
"language:auq",
"language:aux",
"language:auy",
"language:avn",
"language:avv",
"language:awa",
"language:axg",
"language:ayg",
"language:aym",
"language:aze",
"language:bak",
"language:bam",
"language:ban",
"language:bap",
"language:bav",
"language:bbg",
"language:bbk",
"language:bbl",
"language:bbn",
"language:bbq",
"language:bbr",
"language:bbw",
"language:bcm",
"language:bco",
"language:bcq",
"language:bdk",
"language:bdn",
"language:bdq",
"language:bdt",
"language:bdu",
"language:bdv",
"language:bdw",
"language:bdx",
"language:bec",
"language:bej",
"language:bel",
"language:ben",
"language:beu",
"language:bew",
"language:bfa",
"language:bfb",
"language:bfe",
"language:bff",
"language:bfh",
"language:bfm",
"language:bfq",
"language:bft",
"language:bfx",
"language:bfy",
"language:bga",
"language:bgc",
"language:bgd",
"language:bgq",
"language:bgw",
"language:bhb",
"language:bho",
"language:bhp",
"language:bhs",
"language:bhw",
"language:bhy",
"language:bib",
"language:bil",
"language:bio",
"language:bip",
"language:bit",
"language:biv",
"language:bja",
"language:bji",
"language:bjr",
"language:bjz",
"language:bkf",
"language:bkj",
"language:bku",
"language:bkv",
"language:bky",
"language:bld",
"language:blf",
"language:bll",
"language:bln",
"language:blq",
"language:blr",
"language:blt",
"language:bly",
"language:blz",
"language:bma",
"language:bmh",
"language:bmi",
"language:bmq",
"language:bmr",
"language:bnb",
"language:bnf",
"language:bng",
"language:bni",
"language:bnn",
"language:bny",
"language:boa",
"language:boh",
"language:boj",
"language:bol",
"language:bom",
"language:bos",
"language:box",
"language:bpe",
"language:bph",
"language:bpk",
"language:bpn",
"language:bpt",
"language:bpx",
"language:bpz",
"language:bqh",
"language:bqj",
"language:bqq",
"language:bqt",
"language:bqv",
"language:bqx",
"language:bre",
"language:brf",
"language:brh",
"language:bro",
"language:bsa",
"language:bsc",
"language:bse",
"language:bsg",
"language:bsj",
"language:bsl",
"language:bsn",
"language:bsq",
"language:bsx",
"language:bta",
"language:bte",
"language:btn",
"language:bto",
"language:bts",
"language:btt",
"language:btu",
"language:btv",
"language:btx",
"language:buc",
"language:bud",
"language:bue",
"language:bug",
"language:bul",
"language:buo",
"language:buu",
"language:bvd",
"language:bvi",
"language:bvj",
"language:bvo",
"language:bwe",
"language:bwt",
"language:bww",
"language:bwy",
"language:bxp",
"language:byh",
"language:bys",
"language:byv",
"language:byx",
"language:bzb",
"language:bzd",
"language:bzh",
"language:cac",
"language:cad",
"language:cag",
"language:cak",
"language:cal",
"language:cap",
"language:cat",
"language:cax",
"language:cay",
"language:cbc",
"language:cbd",
"language:cbg",
"language:cbt",
"language:cbu",
"language:cby",
"language:ccc",
"language:cce",
"language:cch",
"language:ccp",
"language:cda",
"language:cde",
"language:cdf",
"language:cdi",
"language:cdm",
"language:cea",
"language:ceb",
"language:ceg",
"language:ces",
"language:cfd",
"language:cha",
"language:chb",
"language:chc",
"language:che",
"language:chg",
"language:chk",
"language:chl",
"language:cho",
"language:chp",
"language:chr",
"language:cht",
"language:chv",
"language:chw",
"language:chy",
"language:cia",
"language:cic",
"language:cih",
"language:cik",
"language:cim",
"language:cjh",
"language:cji",
"language:cjk",
"language:cjs",
"language:ckl",
"language:cku",
"language:ckv",
"language:clw",
"language:cme",
"language:cna",
"language:cng",
"language:cnh",
"language:cni",
"language:cnq",
"language:cnr",
"language:cob",
"language:coe",
"language:cog",
"language:com",
"language:con",
"language:coo",
"language:cop",
"language:cor",
"language:cos",
"language:cot",
"language:cou",
"language:cox",
"language:cps",
"language:crc",
"language:crd",
"language:cre",
"language:crh",
"language:crk",
"language:crm",
"language:cro",
"language:crr",
"language:crv",
"language:crx",
"language:crz",
"language:csb",
"language:csw",
"language:ctg",
"language:ctm",
"language:cub",
"language:cuj",
"language:cuo",
"language:cup",
"language:cuu",
"language:cwe",
"language:cym",
"language:daa",
"language:dag",
"language:dah",
"language:dak",
"language:dan",
"language:dar",
"language:dba",
"language:dbd",
"language:dby",
"language:ddd",
"language:dec",
"language:deh",
"language:dem",
"language:der",
"language:des",
"language:deu",
"language:dev",
"language:dgr",
"language:dgs",
"language:dhd",
"language:dhi",
"language:dhm",
"language:dia",
"language:dig",
"language:dil",
"language:din",
"language:dio",
"language:dis",
"language:diz",
"language:dje",
"language:djn",
"language:djo",
"language:dlg",
"language:dlk",
"language:dlm",
"language:dmc",
"language:dml",
"language:dmr",
"language:dmy",
"language:dng",
"language:dnj",
"language:dnk",
"language:dnu",
"language:dnw",
"language:doa",
"language:dof",
"language:dox",
"language:drc",
"language:drd",
"language:drl",
"language:drn",
"language:dru",
"language:dsb",
"language:dtd",
"language:dui",
"language:dyo",
"language:dyu",
"language:dza",
"language:ebk",
"language:ebr",
"language:ebu",
"language:eee",
"language:efi",
"language:ego",
"language:eiv",
"language:ekg",
"language:eko",
"language:ekr",
"language:ele",
"language:eli",
"language:emm",
"language:emx",
"language:ena",
"language:enl",
"language:enn",
"language:enx",
"language:era",
"language:eri",
"language:ero",
"language:ert",
"language:ese",
"language:esq",
"language:ess",
"language:est",
"language:esy",
"language:etx",
"language:eus",
"language:eve",
"language:evh",
"language:evn",
"language:ewe",
"language:ext",
"language:eyo",
"language:faa",
"language:fad",
"language:fao",
"language:fas",
"language:ffi",
"language:fgr",
"language:fia",
"language:fif",
"language:fij",
"language:fil",
"language:fin",
"language:fip",
"language:fir",
"language:fkk",
"language:fni",
"language:fon",
"language:fqs",
"language:fra",
"language:frd",
"language:frk",
"language:fuc",
"language:fur",
"language:fuu",
"language:fvr",
"language:fwe",
"language:gaa",
"language:gag",
"language:gah",
"language:gak",
"language:gao",
"language:gaw",
"language:gay",
"language:gbk",
"language:gbm",
"language:gbz",
"language:gcc",
"language:gce",
"language:gdj",
"language:gdl",
"language:gdm",
"language:gdn",
"language:gdr",
"language:gea",
"language:geb",
"language:gei",
"language:gej",
"language:gew",
"language:gex",
"language:gey",
"language:gfk",
"language:ggk",
"language:ghn",
"language:gid",
"language:gil",
"language:git",
"language:gju",
"language:gko",
"language:gld",
"language:gle",
"language:glg",
"language:glk",
"language:glv",
"language:glw",
"language:gmb",
"language:gna",
"language:gng",
"language:gnt",
"language:goe",
"language:gog",
"language:goi",
"language:gon",
"language:gor",
"language:gov",
"language:gqi",
"language:grb",
"language:grh",
"language:grn",
"language:grt",
"language:gua",
"language:guc",
"language:guh",
"language:gui",
"language:guj",
"language:gun",
"language:guo",
"language:guq",
"language:gur",
"language:guu",
"language:guw",
"language:guz",
"language:gve",
"language:gvj",
"language:gvl",
"language:gwc",
"language:gwe",
"language:gwi",
"language:gwr",
"language:gyo",
"language:gyr",
"language:gza",
"language:hai",
"language:haj",
"language:han",
"language:haq",
"language:har",
"language:has",
"language:hau",
"language:hav",
"language:haw",
"language:hay",
"language:hbb",
"language:hbn",
"language:hch",
"language:heb",
"language:heh",
"language:her",
"language:hhi",
"language:hid",
"language:hih",
"language:hii",
"language:hil",
"language:hit",
"language:hke",
"language:hlb",
"language:hle",
"language:hmn",
"language:hmt",
"language:hne",
"language:hni",
"language:hnn",
"language:hoc",
"language:hoe",
"language:hoi",
"language:hol",
"language:hoo",
"language:hop",
"language:hot",
"language:hra",
"language:hru",
"language:hrv",
"language:hsb",
"language:hto",
"language:hts",
"language:huh",
"language:hun",
"language:hup",
"language:hus",
"language:huw",
"language:hux",
"language:huz",
"language:hye",
"language:iai",
"language:ian",
"language:iba",
"language:ibb",
"language:ibl",
"language:ibm",
"language:ibo",
"language:idc",
"language:idu",
"language:igm",
"language:ihp",
"language:ijc",
"language:ijn",
"language:ikx",
"language:ikz",
"language:ilb",
"language:ili",
"language:imi",
"language:iml",
"language:imy",
"language:ind",
"language:inh",
"language:ior",
"language:irh",
"language:iri",
"language:irk",
"language:iru",
"language:irx",
"language:ish",
"language:isi",
"language:isk",
"language:isl",
"language:isn",
"language:ist",
"language:ita",
"language:itl",
"language:ito",
"language:itr",
"language:ium",
"language:ivv",
"language:iwo",
"language:iws",
"language:ixc",
"language:iyo",
"language:izh",
"language:izr",
"language:jab",
"language:jae",
"language:jal",
"language:jav",
"language:jbn",
"language:jbu",
"language:jct",
"language:jdg",
"language:jeb",
"language:jel",
"language:jet",
"language:jgb",
"language:jgo",
"language:jic",
"language:jig",
"language:jio",
"language:jit",
"language:jiv",
"language:jku",
"language:jle",
"language:jma",
"language:jmb",
"language:jml",
"language:jni",
"language:jow",
"language:jpn",
"language:jqr",
"language:jra",
"language:juk",
"language:jun",
"language:juo",
"language:jwi",
"language:kab",
"language:kad",
"language:kaj",
"language:kap",
"language:kas",
"language:kat",
"language:kau",
"language:kaz",
"language:kbd",
"language:kbj",
"language:kbr",
"language:kbu",
"language:kbz",
"language:kca",
"language:kcg",
"language:kck",
"language:kcn",
"language:kcq",
"language:kcr",
"language:kct",
"language:kcw",
"language:kcy",
"language:kde",
"language:kdh",
"language:kdk",
"language:kdn",
"language:kdr",
"language:kdt",
"language:kdx",
"language:ked",
"language:keg",
"language:keh",
"language:ken",
"language:ket",
"language:kev",
"language:kff",
"language:kfk",
"language:kfm",
"language:kfp",
"language:kfq",
"language:kft",
"language:kfy",
"language:kge",
"language:kgg",
"language:kgk",
"language:kgp",
"language:kgt",
"language:kgu",
"language:kgv",
"language:kha",
"language:khe",
"language:khl",
"language:khm",
"language:khr",
"language:kht",
"language:kib",
"language:kik",
"language:kil",
"language:kio",
"language:kiv",
"language:kiy",
"language:kjg",
"language:kjh",
"language:kjk",
"language:kjm",
"language:kjn",
"language:kju",
"language:kjx",
"language:kkd",
"language:kkh",
"language:kkk",
"language:kkm",
"language:kks",
"language:kkt",
"language:kkv",
"language:kkz",
"language:klb",
"language:klf",
"language:klj",
"language:klq",
"language:klr",
"language:kls",
"language:klu",
"language:kly",
"language:kma",
"language:kni",
"language:knp",
"language:knv",
"language:knx",
"language:knz",
"language:kom",
"language:kon",
"language:kop",
"language:kor",
"language:kot",
"language:koy",
"language:kpa",
"language:kpe",
"language:kpf",
"language:kpg",
"language:kpj",
"language:kpm",
"language:kps",
"language:kpu",
"language:kpy",
"language:kpz",
"language:kqa",
"language:kqg",
"language:kql",
"language:kqn",
"language:kqp",
"language:kqu",
"language:kqv",
"language:kre",
"language:krh",
"language:krl",
"language:kru",
"language:kry",
"language:ksb",
"language:ksk",
"language:ksm",
"language:ksp",
"language:ksr",
"language:ksw",
"language:kte",
"language:ktm",
"language:kuc",
"language:kuj",
"language:kum",
"language:kun",
"language:kus",
"language:kut",
"language:kuu",
"language:kuz",
"language:kva",
"language:kve",
"language:kvf",
"language:kvl",
"language:kvr",
"language:kvw",
"language:kwe",
"language:kwf",
"language:kwh",
"language:kwn",
"language:kws",
"language:kwz",
"language:kxi",
"language:kxv",
"language:kyt",
"language:kyx",
"language:kzl",
"language:kzm",
"language:kzr",
"language:lac",
"language:lai",
"language:lam",
"language:lan",
"language:lao",
"language:laq",
"language:lav",
"language:laz",
"language:lbe",
"language:lbf",
"language:lbj",
"language:lbk",
"language:lbq",
"language:lbz",
"language:lce",
"language:lcl",
"language:lcq",
"language:ldd",
"language:ldj",
"language:ldl",
"language:ldo",
"language:ldp",
"language:leb",
"language:lec",
"language:led",
"language:lee",
"language:lef",
"language:leh",
"language:lej",
"language:les",
"language:let",
"language:lex",
"language:ley",
"language:lgq",
"language:lgt",
"language:lhu",
"language:lif",
"language:lih",
"language:lij",
"language:lil",
"language:lis",
"language:lit",
"language:liw",
"language:lji",
"language:lkh",
"language:lki",
"language:lkj",
"language:lko",
"language:lkr",
"language:lkt",
"language:lky",
"language:lld",
"language:llg",
"language:lll",
"language:llp",
"language:llu",
"language:lmc",
"language:lmd",
"language:lmk",
"language:lmo",
"language:lmp",
"language:lnh",
"language:lnu",
"language:loa",
"language:lob",
"language:loe",
"language:lof",
"language:lok",
"language:lol",
"language:lon",
"language:lop",
"language:lot",
"language:loz",
"language:lpo",
"language:lpx",
"language:lri",
"language:lsi",
"language:lsr",
"language:ltg",
"language:lub",
"language:lun",
"language:lup",
"language:lwa",
"language:lyn",
"language:lzl",
"language:lzz",
"language:mad",
"language:mag",
"language:mah",
"language:mai",
"language:mam",
"language:mar",
"language:maw",
"language:mbl",
"language:mbn",
"language:mbu",
"language:mby",
"language:mcc",
"language:mcf",
"language:mcj",
"language:mck",
"language:mdf",
"language:mdj",
"language:mdq",
"language:mdt",
"language:meb",
"language:mef",
"language:mej",
"language:mer",
"language:mew",
"language:mez",
"language:mff",
"language:mfi",
"language:mfo",
"language:mfr",
"language:mgd",
"language:mgf",
"language:mgg",
"language:mgj",
"language:mgq",
"language:mgr",
"language:mgu",
"language:mgv",
"language:mgw",
"language:mhd",
"language:mhi",
"language:mhl",
"language:mhq",
"language:mhw",
"language:mic",
"language:mid",
"language:min",
"language:miw",
"language:mje",
"language:mjs",
"language:mjw",
"language:mka",
"language:mkb",
"language:mkc",
"language:mkd",
"language:mki",
"language:mkj",
"language:mkk",
"language:mko",
"language:mkp",
"language:mkq",
"language:mlc",
"language:mlf",
"language:mlk",
"language:mlp",
"language:mlr",
"language:mls",
"language:mlt",
"language:mlw",
"language:mmo",
"language:mmp",
"language:mmt",
"language:mmv",
"language:mmw",
"language:mnb",
"language:mnc",
"language:mnd",
"language:mnj",
"language:mns",
"language:mnw",
"language:moh",
"language:moi",
"language:mok",
"language:mom",
"language:mor",
"language:mot",
"language:mox",
"language:mpa",
"language:mpe",
"language:mpg",
"language:mph",
"language:mpz",
"language:mqp",
"language:mqs",
"language:mrc",
"language:mrf",
"language:mrg",
"language:mrv",
"language:mry",
"language:msf",
"language:msk",
"language:msq",
"language:msy",
"language:mtd",
"language:mtj",
"language:mtl",
"language:mtq",
"language:mtr",
"language:mty",
"language:mua",
"language:mug",
"language:muo",
"language:mup",
"language:muv",
"language:mvp",
"language:mvs",
"language:mvu",
"language:mwb",
"language:mwl",
"language:mwm",
"language:mwv",
"language:mxe",
"language:mxf",
"language:mxm",
"language:mxo",
"language:mya",
"language:myb",
"language:mye",
"language:myf",
"language:myg",
"language:myh",
"language:myp",
"language:myv",
"language:myy",
"language:mzm",
"language:mzn",
"language:mzp",
"language:mzt",
"language:mzw",
"language:nak",
"language:nap",
"language:naq",
"language:nav",
"language:nbb",
"language:nbo",
"language:nbp",
"language:nca",
"language:ncg",
"language:ncz",
"language:ndd",
"language:ndg",
"language:ndh",
"language:ndp",
"language:ndy",
"language:neg",
"language:neo",
"language:ner",
"language:nev",
"language:nez",
"language:nfa",
"language:nfd",
"language:ngh",
"language:ngl",
"language:ngn",
"language:ngp",
"language:ngv",
"language:ngy",
"language:nhb",
"language:nia",
"language:nie",
"language:nig",
"language:nii",
"language:nik",
"language:nin",
"language:nio",
"language:nir",
"language:niu",
"language:nix",
"language:niy",
"language:nka",
"language:nkd",
"language:nkr",
"language:nks",
"language:nlc",
"language:nld",
"language:nlj",
"language:nmb",
"language:nmc",
"language:nmg",
"language:nmk",
"language:nmq",
"language:nmr",
"language:nmy",
"language:nmz",
"language:nnb",
"language:nnh",
"language:nnq",
"language:nnu",
"language:nod",
"language:noe",
"language:nog",
"language:noj",
"language:nok",
"language:nol",
"language:nor",
"language:not",
"language:now",
"language:noy",
"language:nrb",
"language:nrm",
"language:nrn",
"language:nse",
"language:nsk",
"language:nsx",
"language:nsz",
"language:nti",
"language:ntr",
"language:nty",
"language:nuk",
"language:nus",
"language:nuy",
"language:nvo",
"language:nwr",
"language:nxq",
"language:nxr",
"language:nyj",
"language:nyk",
"language:nyo",
"language:nyp",
"language:nyu",
"language:nzb",
"language:nzd",
"language:nzy",
"language:oac",
"language:obi",
"language:oca",
"language:ogb",
"language:ogo",
"language:ogu",
"language:oka",
"language:okd",
"language:okj",
"language:oku",
"language:olr",
"language:omc",
"language:omo",
"language:omt",
"language:ona",
"language:one",
"language:ono",
"language:onp",
"language:opm",
"language:ore",
"language:orm",
"language:ory",
"language:osa",
"language:oso",
"language:oss",
"language:oti",
"language:otr",
"language:pae",
"language:pag",
"language:pai",
"language:paq",
"language:pau",
"language:paz",
"language:pbb",
"language:pbg",
"language:pbi",
"language:pbp",
"language:pbr",
"language:pbv",
"language:pcb",
"language:pcc",
"language:pcd",
"language:pcg",
"language:pci",
"language:pcl",
"language:pcn",
"language:pdn",
"language:peb",
"language:peh",
"language:phd",
"language:phg",
"language:phh",
"language:phk",
"language:pho",
"language:pht",
"language:phu",
"language:phv",
"language:pia",
"language:pib",
"language:pic",
"language:pid",
"language:pio",
"language:pip",
"language:piw",
"language:pkb",
"language:pkt",
"language:ple",
"language:plu",
"language:pmt",
"language:pnh",
"language:pnl",
"language:pol",
"language:pon",
"language:por",
"language:pot",
"language:pox",
"language:poy",
"language:ppi",
"language:ppk",
"language:ppt",
"language:pru",
"language:prw",
"language:psn",
"language:pta",
"language:pto",
"language:ptt",
"language:ptu",
"language:ptv",
"language:ptw",
"language:pue",
"language:pui",
"language:pum",
"language:puu",
"language:pwi",
"language:pwn",
"language:qua",
"language:qui",
"language:qun",
"language:rag",
"language:rah",
"language:ran",
"language:rao",
"language:raw",
"language:rbp",
"language:rei",
"language:rej",
"language:ren",
"language:res",
"language:rey",
"language:rgu",
"language:rhg",
"language:rhp",
"language:rin",
"language:rkb",
"language:rki",
"language:rkt",
"language:rma",
"language:rmb",
"language:rme",
"language:rmt",
"language:rmw",
"language:rmy",
"language:rnd",
"language:rnw",
"language:rof",
"language:roh",
"language:rol",
"language:ron",
"language:row",
"language:rsk",
"language:rtm",
"language:rub",
"language:ruc",
"language:rue",
"language:ruf",
"language:rus",
"language:rut",
"language:ruz",
"language:rwo",
"language:rys",
"language:sad",
"language:sag",
"language:sah",
"language:sak",
"language:sam",
"language:saq",
"language:sat",
"language:sau",
"language:say",
"language:saz",
"language:sbk",
"language:sbo",
"language:sbt",
"language:sby",
"language:sch",
"language:scn",
"language:sco",
"language:scq",
"language:sdj",
"language:sdp",
"language:sea",
"language:see",
"language:sei",
"language:sek",
"language:ser",
"language:sey",
"language:sfw",
"language:sgh",
"language:sgk",
"language:sgm",
"language:sgs",
"language:sgy",
"language:shb",
"language:shc",
"language:shd",
"language:shh",
"language:shj",
"language:shk",
"language:shn",
"language:shr",
"language:shs",
"language:shw",
"language:shx",
"language:sif",
"language:sig",
"language:sih",
"language:sik",
"language:sin",
"language:sip",
"language:sis",
"language:siu",
"language:siw",
"language:six",
"language:siy",
"language:siz",
"language:sjo",
"language:sjp",
"language:sjr",
"language:sjw",
"language:skb",
"language:skr",
"language:sks",
"language:skv",
"language:slk",
"language:sll",
"language:slr",
"language:slx",
"language:sly",
"language:smk",
"language:smo",
"language:smr",
"language:smt",
"language:smw",
"language:smy",
"language:sna",
"language:snd",
"language:snf",
"language:snk",
"language:snn",
"language:snx",
"language:snz",
"language:soa",
"language:sog",
"language:soh",
"language:som",
"language:soq",
"language:sor",
"language:sou",
"language:spa",
"language:spc",
"language:spm",
"language:spn",
"language:sps",
"language:spu",
"language:spv",
"language:spy",
"language:sqh",
"language:sqi",
"language:sqt",
"language:squ",
"language:srb",
"language:srd",
"language:srh",
"language:sri",
"language:srm",
"language:srp",
"language:srq",
"language:srr",
"language:srx",
"language:ssf",
"language:ssi",
"language:ssk",
"language:ssm",
"language:stn",
"language:sto",
"language:sty",
"language:sub",
"language:suk",
"language:sun",
"language:sus",
"language:suv",
"language:suw",
"language:sux",
"language:suy",
"language:suz",
"language:sva",
"language:swe",
"language:swi",
"language:swr",
"language:swv",
"language:sxe",
"language:sxr",
"language:syk",
"language:syl",
"language:syo",
"language:syr",
"language:sys",
"language:syw",
"language:syx",
"language:szb",
"language:szl",
"language:szn",
"language:szp",
"language:szw",
"language:taa",
"language:tag",
"language:tah",
"language:tam",
"language:tao",
"language:tap",
"language:taq",
"language:tat",
"language:tau",
"language:tav",
"language:taz",
"language:tba",
"language:tbe",
"language:tbi",
"language:tbk",
"language:tbp",
"language:tbt",
"language:tca",
"language:tcb",
"language:tcg",
"language:tcy",
"language:tda",
"language:tdh",
"language:tdv",
"language:tec",
"language:tef",
"language:teh",
"language:tei",
"language:tel",
"language:teo",
"language:teq",
"language:tet",
"language:teu",
"language:tez",
"language:tfr",
"language:tft",
"language:tgk",
"language:tgl",
"language:tgp",
"language:tgx",
"language:tha",
"language:thf",
"language:thp",
"language:ths",
"language:tht",
"language:thy",
"language:tig",
"language:tii",
"language:tij",
"language:til",
"language:tin",
"language:tir",
"language:tit",
"language:tiv",
"language:tjl",
"language:tjw",
"language:tkm",
"language:tkr",
"language:tkv",
"language:tlh",
"language:tli",
"language:tll",
"language:tlq",
"language:tlx",
"language:tly",
"language:tmd",
"language:tmf",
"language:tmj",
"language:tms",
"language:tmu",
"language:tmw",
"language:tnc",
"language:tng",
"language:tnk",
"language:tnl",
"language:tnm",
"language:tnx",
"language:tny",
"language:tol",
"language:tom",
"language:toq",
"language:tow",
"language:tox",
"language:tpg",
"language:tpy",
"language:tpz",
"language:tql",
"language:tqo",
"language:trr",
"language:tru",
"language:trw",
"language:tsa",
"language:tsb",
"language:tsc",
"language:tsd",
"language:tsg",
"language:tsn",
"language:tso",
"language:tsu",
"language:tsv",
"language:tsx",
"language:tta",
"language:ttb",
"language:tti",
"language:ttj",
"language:ttl",
"language:ttv",
"language:tua",
"language:tub",
"language:tuc",
"language:tue",
"language:tuk",
"language:tum",
"language:tun",
"language:tuo",
"language:tur",
"language:tus",
"language:tuu",
"language:tuv",
"language:tuy",
"language:tuz",
"language:tvk",
"language:tvx",
"language:twa",
"language:twh",
"language:twn",
"language:twq",
"language:twu",
"language:txc",
"language:txg",
"language:txi",
"language:txq",
"language:txx",
"language:tya",
"language:tyr",
"language:tyz",
"language:tzh",
"language:tzo",
"language:tzx",
"language:uan",
"language:uar",
"language:uby",
"language:udi",
"language:udm",
"language:ugh",
"language:ukr",
"language:ukw",
"language:ulb",
"language:ulc",
"language:ule",
"language:ulf",
"language:uli",
"language:ull",
"language:ump",
"language:umu",
"language:une",
"language:ung",
"language:unr",
"language:ura",
"language:ure",
"language:urk",
"language:urw",
"language:usu",
"language:uum",
"language:uuu",
"language:uve",
"language:uvh",
"language:uzb",
"language:uzs",
"language:vai",
"language:var",
"language:vas",
"language:vau",
"language:vav",
"language:vec",
"language:ven",
"language:veo",
"language:vep",
"language:vie",
"language:vif",
"language:vkk",
"language:vmg",
"language:vmw",
"language:vot",
"language:vro",
"language:vum",
"language:wan",
"language:was",
"language:wat",
"language:wbe",
"language:wbh",
"language:wbi",
"language:wbl",
"language:wbm",
"language:wdj",
"language:wgy",
"language:wic",
"language:wii",
"language:win",
"language:wiv",
"language:wja",
"language:wkd",
"language:wln",
"language:wls",
"language:wme",
"language:wmi",
"language:wmw",
"language:wnc",
"language:wnm",
"language:wnp",
"language:wnu",
"language:wnw",
"language:wol",
"language:won",
"language:wrh",
"language:wsa",
"language:wtf",
"language:wti",
"language:wtk",
"language:wtm",
"language:wul",
"language:wur",
"language:wut",
"language:wwa",
"language:wym",
"language:wyn",
"language:wyr",
"language:xad",
"language:xan",
"language:xaw",
"language:xbc",
"language:xbw",
"language:xch",
"language:xdq",
"language:xed",
"language:xem",
"language:xgw",
"language:xho",
"language:xka",
"language:xkl",
"language:xko",
"language:xkv",
"language:xla",
"language:xlc",
"language:xmd",
"language:xmf",
"language:xmg",
"language:xno",
"language:xnr",
"language:xnz",
"language:xog",
"language:xon",
"language:xpq",
"language:xpr",
"language:xqa",
"language:xso",
"language:xsr",
"language:xsu",
"language:xsy",
"language:xte",
"language:xub",
"language:xug",
"language:xuo",
"language:xwa",
"language:xwc",
"language:xwr",
"language:xww",
"language:xyy",
"language:xzh",
"language:yad",
"language:yao",
"language:yap",
"language:yaq",
"language:yba",
"language:ybb",
"language:ybj",
"language:ybl",
"language:ycl",
"language:ycn",
"language:ydg",
"language:yej",
"language:yer",
"language:yes",
"language:yev",
"language:yey",
"language:yiu",
"language:yko",
"language:yla",
"language:yle",
"language:ylg",
"language:yme",
"language:ymi",
"language:ymk",
"language:ymn",
"language:ymz",
"language:ynk",
"language:yno",
"language:yns",
"language:yoi",
"language:yox",
"language:ypg",
"language:yph",
"language:ysn",
"language:yss",
"language:yuc",
"language:yuk",
"language:yul",
"language:yum",
"language:yup",
"language:yur",
"language:yux",
"language:ywa",
"language:yxu",
"language:zag",
"language:zen",
"language:zga",
"language:zhb",
"language:zhd",
"language:zhi",
"language:zhn",
"language:zho",
"language:zil",
"language:zim",
"language:zin",
"language:ziw",
"language:ziz",
"language:zkk",
"language:zkr",
"language:zku",
"language:zmb",
"language:zmf",
"language:zmn",
"language:zmp",
"language:zmv",
"language:zrp",
"language:zul",
"language:zun",
"language:zwa",
"language:zyg",
"language:kgr",
"language:anz",
"language:blb",
"language:boq",
"language:bzu",
"language:bsk",
"language:kbh",
"language:caz",
"language:xcy",
"language:cyb",
"language:cid",
"language:xcw",
"language:xcn",
"language:cuy",
"language:uhn",
"language:duc",
"language:elx",
"language:ett",
"language:fun",
"language:fuy",
"language:gta",
"language:gly",
"language:guk",
"language:grx",
"language:xht",
"language:xib",
"language:tbd",
"language:khp",
"language:xar",
"language:kyh",
"language:khh",
"language:xbn",
"language:prm",
"language:kla",
"language:kol",
"language:vkj",
"language:kto",
"language:laf",
"language:lrg",
"language:lvk",
"language:xak",
"language:mgk",
"language:xmr",
"language:xxm",
"language:mbe",
"language:msl",
"language:moq",
"language:akc",
"language:myr",
"language:nll",
"language:bhf",
"language:omu",
"language:ppe",
"language:pwa",
"language:ata",
"language:yae",
"language:puq",
"language:iar",
"language:sln",
"language:sao",
"language:svs",
"language:sii",
"language:sua",
"language:gpn",
"language:xxt",
"language:tcm",
"language:tdm",
"language:ttd",
"language:tjm",
"language:tiw",
"language:tqw",
"language:tqu",
"language:tsi",
"language:tud",
"language:umr",
"language:vil",
"language:wba",
"language:wiu",
"language:xoo",
"language:nce",
"language:yag",
"language:ynn",
"language:yra",
"language:yet",
"language:hti",
"language:auj",
"language:mzb",
"language:sds",
"language:shi",
"language:zgh",
"language:gho",
"language:sjs",
"language:thv",
"language:ttq",
"language:thz",
"language:gnc",
"language:mqb",
"language:mpk",
"language:hya",
"language:kvj",
"language:bcw",
"language:hig",
"language:bdm",
"language:jia",
"language:xmj",
"language:kqx",
"language:msv",
"language:mpi",
"language:hia",
"language:vem",
"language:mrt",
"language:mfm",
"language:bwr",
"language:ngx",
"language:mfl",
"language:dgh",
"language:ngs",
"language:cie",
"language:gdf",
"language:mfh",
"language:dme",
"language:meq",
"language:gnd",
"language:mif",
"language:mfk",
"language:mxu",
"language:muy",
"language:udl",
"language:gis",
"language:giz",
"language:bcy",
"language:gdu",
"language:ngw",
"language:jim",
"language:fli",
"language:gde",
"language:hod",
"language:nja",
"language:swq",
"language:tsh",
"language:hna",
"language:gou",
"language:dkx",
"language:dbq",
"language:bvw",
"language:gqa",
"language:hwo",
"language:jaf",
"language:ttr",
"language:cuv",
"language:maf",
"language:mfj",
"language:jie",
"language:moz",
"language:muj",
"language:btf",
"language:mou",
"language:trj",
"language:bid",
"language:mmy",
"language:jeu",
"language:ckq",
"language:mes",
"language:mub",
"language:mcw",
"language:ubi",
"language:bvf",
"language:mlj",
"language:saa",
"language:sok",
"language:tax",
"language:ker",
"language:kvi",
"language:lln",
"language:nnc",
"language:gab",
"language:ndm",
"language:tmc",
"language:gdk",
"language:swy",
"language:mse",
"language:mcn",
"language:zuy",
"language:nnn",
"language:fie",
"language:tdk",
"language:kul",
"language:cla",
"language:gwn",
"language:kai",
"language:glo",
"language:nbh",
"language:bxq",
"language:dbb",
"language:kof",
"language:bvh",
"language:ktc",
"language:nmi",
"language:kna",
"language:kuh",
"language:piy",
"language:tan",
"language:ksq",
"language:sur",
"language:anc",
"language:ank",
"language:tal",
"language:kcs",
"language:pcw",
"language:jrt",
"language:nqt",
"language:dbp",
"language:ngi",
"language:bde",
"language:auo",
"language:twc",
"language:ajw",
"language:tgd",
"language:dwa",
"language:bbt",
"language:pqa",
"language:sir",
"language:mkf",
"language:wji",
"language:bux",
"language:kkr",
"language:zns",
"language:grd",
"language:jmi",
"language:juu",
"language:tak",
"language:zah",
"language:gyz",
"language:dot",
"language:zua",
"language:zaz",
"language:awn",
"language:byn",
"language:dal",
"language:hdy",
"language:liq",
"language:ktb",
"language:drs",
"language:sid",
"language:ssy",
"language:kxc",
"language:gaz",
"language:gax",
"language:orc",
"language:hae",
"language:ssn",
"language:gii",
"language:ymm",
"language:rel",
"language:bsw",
"language:jii",
"language:dbr",
"language:tqq",
"language:bob",
"language:arv",
"language:dsh",
"language:elo",
"language:muu",
"language:bnl",
"language:wka",
"language:bds",
"language:wbj",
"language:gow",
"language:egy",
"language:xna",
"language:ara",
"language:arb",
"language:ayh",
"language:acw",
"language:jye",
"language:ayn",
"language:ssh",
"language:acq",
"language:abv",
"language:adf",
"language:afb",
"language:ars",
"language:acx",
"language:abh",
"language:auz",
"language:yhd",
"language:ayp",
"language:avl",
"language:arz",
"language:aec",
"language:shu",
"language:apd",
"language:acy",
"language:apc",
"language:ajp",
"language:arq",
"language:aao",
"language:mey",
"language:yud",
"language:aju",
"language:ayl",
"language:aeb",
"language:xaa",
"language:ary",
"language:syc",
"language:aii",
"language:cld",
"language:tmr",
"language:syn",
"language:bjf",
"language:lsd",
"language:huy",
"language:trg",
"language:aij",
"language:myz",
"language:amw",
"language:jpa",
"language:oar",
"language:hbo",
"language:smp",
"language:xdm",
"language:obm",
"language:uga",
"language:phn",
"language:xpu",
"language:xhd",
"language:inm",
"language:xqt",
"language:gez",
"language:amh",
"language:agj",
"language:stv",
"language:wle",
"language:gft",
"language:gru",
"language:mvz",
"language:sgw",
"language:mys",
"language:hoh",
"language:bhm",
"language:hss",
"language:gdq",
"language:wiy",
"language:bla",
"language:nwa",
"language:ats",
"language:crl",
"language:crj",
"language:cwd",
"language:crg",
"language:pqm",
"language:pim",
"language:unm",
"language:nnt",
"language:psy",
"language:xlo",
"language:wam",
"language:mia",
"language:kic",
"language:sac",
"language:oji",
"language:otw",
"language:ojc",
"language:ciw",
"language:ojg",
"language:ojb",
"language:ojw",
"language:ojs",
"language:aes",
"language:amt",
"language:agm",
"language:ygw",
"language:byr",
"language:smb",
"language:mcr",
"language:kcb",
"language:klp",
"language:ssu",
"language:aak",
"language:ipo",
"language:kvg",
"language:zik",
"language:bpv",
"language:mrz",
"language:bgv",
"language:jaq",
"language:aob",
"language:bmz",
"language:afp",
"language:arn",
"language:yvt",
"language:bae",
"language:tnq",
"language:cab",
"language:crb",
"language:unk",
"language:pab",
"language:sar",
"language:yaw",
"language:mmh",
"language:wau",
"language:cbb",
"language:tae",
"language:kpc",
"language:aca",
"language:mht",
"language:rgr",
"language:xir",
"language:wap",
"language:brg",
"language:pnk",
"language:ign",
"language:trn",
"language:caj",
"language:cpc",
"language:prq",
"language:cpu",
"language:cpb",
"language:cjo",
"language:cpy",
"language:mcb",
"language:apu",
"language:inp",
"language:mpd",
"language:aru",
"language:swx",
"language:grg",
"language:cul",
"language:afh",
"language:zbl",
"language:bzt",
"language:dws",
"language:ina",
"language:igs",
"language:ile",
"language:avk",
"language:ldn",
"language:lfn",
"language:jbo",
"language:lws",
"language:nqo",
"language:nov",
"language:qya",
"language:rmv",
"language:sjn",
"language:tzl",
"language:tok",
"language:vol",
"language:epo",
"language:ido",
"language:eya",
"language:srs",
"language:apk",
"language:apj",
"language:apl",
"language:apm",
"language:caf",
"language:haa",
"language:ing",
"language:ttm",
"language:tce",
"language:bea",
"language:scs",
"language:xsl",
"language:ktw",
"language:mvb",
"language:wlk",
"language:xup",
"language:coq",
"language:aht",
"language:gol",
"language:msw",
"language:lma",
"language:lia",
"language:bun",
"language:bmf",
"language:buy",
"language:kqs",
"language:kss",
"language:bmd",
"language:bsp",
"language:bgo",
"language:ldm",
"language:tem",
"language:ndv",
"language:sav",
"language:cae",
"language:ble",
"language:bjt",
"language:bda",
"language:eja",
"language:cwt",
"language:krx",
"language:mlo",
"language:gsl",
"language:knf",
"language:mfv",
"language:pbo",
"language:bif",
"language:mbv",
"language:naj",
"language:fue",
"language:ffm",
"language:fuf",
"language:fuh",
"language:fuq",
"language:fub",
"language:fui",
"language:ccj",
"language:kcj",
"language:wof",
"language:ega",
"language:ged",
"language:oks",
"language:kcf",
"language:ibe",
"language:epi",
"language:deg",
"language:aaa",
"language:ets",
"language:bin",
"language:ema",
"language:env",
"language:ikp",
"language:atg",
"language:igw",
"language:sxs",
"language:iya",
"language:uha",
"language:ehu",
"language:uku",
"language:opa",
"language:olm",
"language:ayk",
"language:okx",
"language:erh",
"language:iso",
"language:oke",
"language:urh",
"language:tik",
"language:ccg",
"language:dir",
"language:ldh",
"language:doh",
"language:ndr",
"language:bqd",
"language:luw",
"language:njr",
"language:yei",
"language:bgu",
"language:nuh",
"language:vut",
"language:www",
"language:bwh",
"language:bju",
"language:byb",
"language:buz",
"language:jms",
"language:nhu",
"language:bpc",
"language:ncr",
"language:byp",
"language:bzy",
"language:byf",
"language:uba",
"language:ukp",
"language:bqw",
"language:etu",
"language:ofu",
"language:abm",
"language:eka",
"language:kvm",
"language:syi",
"language:kbs",
"language:sbw",
"language:buw",
"language:dii",
"language:ksf",
"language:lfa",
"language:abb",
"language:bbi",
"language:bkh",
"language:bas",
"language:hij",
"language:bum",
"language:fan",
"language:mct",
"language:beb",
"language:ewo",
"language:koq",
"language:mhb",
"language:nda",
"language:wum",
"language:keb",
"language:nra",
"language:nxo",
"language:bvg",
"language:nkc",
"language:bri",
"language:bsi",
"language:mbo",
"language:bss",
"language:bqz",
"language:kkj",
"language:kwu",
"language:bmw",
"language:mcx",
"language:ukh",
"language:ozm",
"language:njy",
"language:mcp",
"language:biw",
"language:gyi",
"language:pmm",
"language:bnm",
"language:bxc",
"language:nui",
"language:dua",
"language:mzd",
"language:kme",
"language:szv",
"language:mho",
"language:nye",
"language:sie",
"language:sng",
"language:kny",
"language:bnx",
"language:lua",
"language:bpj",
"language:luj",
"language:sop",
"language:zla",
"language:mxg",
"language:pem",
"language:mdp",
"language:blv",
"language:kmb",
"language:pnd",
"language:lue",
"language:lch",
"language:nkn",
"language:nba",
"language:lum",
"language:mfu",
"language:kcv",
"language:umb",
"language:olu",
"language:xdo",
"language:nql",
"language:kua",
"language:kwm",
"language:ndo",
"language:lnb",
"language:nne",
"language:khu",
"language:ndq",
"language:zms",
"language:loo",
"language:pof",
"language:mwz",
"language:soc",
"language:zmw",
"language:ndk",
"language:szg",
"language:bli",
"language:nto",
"language:lal",
"language:nxd",
"language:oml",
"language:buf",
"language:lel",
"language:dez",
"language:nkw",
"language:ksv",
"language:kel",
"language:akw",
"language:mdu",
"language:koh",
"language:mdw",
"language:bvx",
"language:mdn",
"language:ndn",
"language:axk",
"language:zmx",
"language:bui",
"language:ngd",
"language:lse",
"language:bmg",
"language:dzn",
"language:ndl",
"language:bws",
"language:bml",
"language:bzo",
"language:bcp",
"language:rwm",
"language:kzy",
"language:kmw",
"language:kty",
"language:nyc",
"language:hom",
"language:myc",
"language:boy",
"language:bqu",
"language:lgz",
"language:ngc",
"language:bwl",
"language:bzm",
"language:bbm",
"language:bkp",
"language:loq",
"language:bkt",
"language:mow",
"language:bxg",
"language:kxx",
"language:kwc",
"language:mmz",
"language:ndw",
"language:liz",
"language:smx",
"language:beq",
"language:xku",
"language:njx",
"language:dde",
"language:ldi",
"language:hng",
"language:mkw",
"language:ktu",
"language:kwy",
"language:yom",
"language:bwz",
"language:snq",
"language:swj",
"language:lnz",
"language:ppp",
"language:noq",
"language:tek",
"language:skt",
"language:ifm",
"language:tyx",
"language:kkw",
"language:tyi",
"language:tck",
"language:kzo",
"language:nmd",
"language:lli",
"language:iyx",
"language:dma",
"language:wdd",
"language:ngz",
"language:nzu",
"language:dov",
"language:shq",
"language:toi",
"language:sbs",
"language:wun",
"language:mwn",
"language:nkt",
"language:nkv",
"language:nyr",
"language:nih",
"language:nyy",
"language:lag",
"language:mgz",
"language:dhs",
"language:kam",
"language:cuh",
"language:thk",
"language:soz",
"language:mws",
"language:sxb",
"language:ssc",
"language:cwa",
"language:zak",
"language:reg",
"language:kya",
"language:luy",
"language:ida",
"language:bxk",
"language:lkb",
"language:myx",
"language:nle",
"language:lks",
"language:lrm",
"language:nyd",
"language:lts",
"language:lto",
"language:lwg",
"language:lsm",
"language:nuj",
"language:lug",
"language:lke",
"language:tlj",
"language:cgg",
"language:nyn",
"language:xsj",
"language:nyg",
"language:flr",
"language:job",
"language:kin",
"language:run",
"language:vin",
"language:suj",
"language:koo",
"language:hka",
"language:old",
"language:vun",
"language:jmc",
"language:rwk",
"language:tga",
"language:dav",
"language:wlc",
"language:zdj",
"language:swb",
"language:wni",
"language:coh",
"language:dug",
"language:nyf",
"language:seg",
"language:swc",
"language:ccl",
"language:tvs",
"language:asa",
"language:kki",
"language:doe",
"language:kcu",
"language:kdc",
"language:zaj",
"language:bou",
"language:xma",
"language:sbm",
"language:vid",
"language:bez",
"language:egm",
"language:gmx",
"language:kiz",
"language:sbp",
"language:nym",
"language:kcz",
"language:rwl",
"language:bdp",
"language:bmb",
"language:sod",
"language:byi",
"language:lgm",
"language:khx",
"language:lea",
"language:zmq",
"language:ktf",
"language:nim",
"language:rim",
"language:ndj",
"language:mgy",
"language:nww",
"language:dne",
"language:nxi",
"language:mvw",
"language:mwe",
"language:bwc",
"language:bem",
"language:kdg",
"language:ndc",
"language:mxc",
"language:twx",
"language:twl",
"language:dmx",
"language:toh",
"language:ssw",
"language:rng",
"language:kzn",
"language:cwb",
"language:mny",
"language:nte",
"language:llb",
"language:vmr",
"language:tke",
"language:vmk",
"language:mgh",
"language:xmc",
"language:mhm",
"language:xsq",
"language:brl",
"language:nso",
"language:two",
"language:sot",
"language:kmy",
"language:mjh",
"language:nya",
"language:bwg",
"language:swk",
"language:seh",
"language:phm",
"language:tog",
"language:bvb",
"language:xmb",
"language:bbu",
"language:mma",
"language:dbo",
"language:bau",
"language:dbm",
"language:jjr",
"language:gwb",
"language:baf",
"language:btc",
"language:mlb",
"language:yav",
"language:mmu",
"language:ekm",
"language:yas",
"language:leo",
"language:bag",
"language:ttf",
"language:yat",
"language:lem",
"language:tvu",
"language:ags",
"language:bzz",
"language:uiv",
"language:uta",
"language:ckx",
"language:emn",
"language:amb",
"language:brt",
"language:ael",
"language:bby",
"language:nml",
"language:mtk",
"language:yam",
"language:kdz",
"language:fmp",
"language:bbj",
"language:bko",
"language:nnz",
"language:nla",
"language:nwe",
"language:bfj",
"language:bmo",
"language:bax",
"language:bgj",
"language:mhk",
"language:bce",
"language:azo",
"language:bfp",
"language:pny",
"language:bfd",
"language:baw",
"language:mfd",
"language:nge",
"language:koc",
"language:mnf",
"language:njj",
"language:ngj",
"language:nsh",
"language:mgo",
"language:nbv",
"language:lns",
"language:kfl",
"language:bkm",
"language:emz",
"language:bmv",
"language:kfn",
"language:lmx",
"language:isu",
"language:zhw",
"language:weh",
"language:bvm",
"language:ndb",
"language:bqo",
"language:bxs",
"language:ost",
"language:mea",
"language:vit",
"language:fak",
"language:kid",
"language:muc",
"language:mij",
"language:boe",
"language:fam",
"language:xab",
"language:mgi",
"language:cen",
"language:gne",
"language:sha",
"language:dbi",
"language:ikv",
"language:khj",
"language:mae",
"language:pym",
"language:tdl",
"language:tyy",
"language:jbm",
"language:dkg",
"language:ikl",
"language:aqk",
"language:ayu",
"language:nbr",
"language:kdp",
"language:ruk",
"language:mda",
"language:kdm",
"language:kci",
"language:xsh",
"language:ahs",
"language:vkn",
"language:klo",
"language:aku",
"language:bnz",
"language:ldq",
"language:aqg",
"language:ahn",
"language:aye",
"language:igl",
"language:its",
"language:mkl",
"language:cbj",
"language:ijj",
"language:luq",
"language:yor",
"language:nqk",
"language:idd",
"language:ica",
"language:ife",
"language:abn",
"language:odu",
"language:kes",
"language:ogg",
"language:obu",
"language:xoc",
"language:ebg",
"language:ibn",
"language:iki",
"language:ilv",
"language:okb",
"language:orx",
"language:usk",
"language:efa",
"language:anw",
"language:ukq",
"language:eke",
"language:etb",
"language:ibr",
"language:itw",
"language:itm",
"language:nkz",
"language:enw",
"language:uda",
"language:eki",
"language:ide",
"language:gkn",
"language:tkq",
"language:elm",
"language:akd",
"language:bbs",
"language:uya",
"language:iko",
"language:yaz",
"language:kcc",
"language:mfn",
"language:agb",
"language:ldg",
"language:ayi",
"language:org",
"language:kez",
"language:eze",
"language:byc",
"language:yay",
"language:bcs",
"language:umm",
"language:krp",
"language:igb",
"language:gbr",
"language:gby",
"language:aum",
"language:nup",
"language:kka",
"language:kug",
"language:kmi",
"language:gpa",
"language:vkz",
"language:ige",
"language:utr",
"language:akf",
"language:ekp",
"language:ikk",
"language:ikw",
"language:ogc",
"language:eza",
"language:iqw",
"language:kub",
"language:nza",
"language:juw",
"language:jib",
"language:juh",
"language:jub",
"language:cfg",
"language:jrr",
"language:bcv",
"language:ich",
"language:kpk",
"language:bzw",
"language:buj",
"language:bsr",
"language:amo",
"language:byj",
"language:klk",
"language:gnh",
"language:gye",
"language:kov",
"language:nar",
"language:jer",
"language:pwb",
"language:cbo",
"language:xsn",
"language:scv",
"language:dam",
"language:awc",
"language:tvd",
"language:kdl",
"language:rod",
"language:acp",
"language:sqa",
"language:bsf",
"language:ula",
"language:gvm",
"language:fah",
"language:tdq",
"language:ada",
"language:ajg",
"language:gbx",
"language:tfi",
"language:cib",
"language:gbh",
"language:mxl",
"language:wem",
"language:wud",
"language:ayb",
"language:gbs",
"language:kqk",
"language:sxw",
"language:xwl",
"language:xwe",
"language:adq",
"language:kef",
"language:wci",
"language:nyb",
"language:tcd",
"language:keu",
"language:anf",
"language:ahl",
"language:kpo",
"language:bov",
"language:blo",
"language:lip",
"language:snw",
"language:ati",
"language:aba",
"language:abi",
"language:adj",
"language:ald",
"language:avi",
"language:gwa",
"language:kxb",
"language:abr",
"language:aka",
"language:wss",
"language:twi",
"language:cko",
"language:bci",
"language:mtb",
"language:aha",
"language:nzi",
"language:doy",
"language:gjn",
"language:nkq",
"language:nko",
"language:naw",
"language:fod",
"language:acd",
"language:kph",
"language:kye",
"language:ncu",
"language:bqa",
"language:nlu",
"language:afu",
"language:lar",
"language:cpn",
"language:gwx",
"language:abu",
"language:eot",
"language:dai",
"language:tug",
"language:bub",
"language:glc",
"language:zna",
"language:glj",
"language:kou",
"language:bes",
"language:goy",
"language:kia",
"language:lla",
"language:yun",
"language:vor",
"language:gmd",
"language:pbl",
"language:bka",
"language:ldk",
"language:gwg",
"language:jen",
"language:mdd",
"language:kbn",
"language:pnz",
"language:gke",
"language:mcs",
"language:tui",
"language:mru",
"language:toz",
"language:pgs",
"language:rax",
"language:bcn",
"language:pbn",
"language:yot",
"language:tdo",
"language:wav",
"language:ynq",
"language:dow",
"language:kmp",
"language:gmn",
"language:ver",
"language:wok",
"language:dur",
"language:ndu",
"language:dae",
"language:klc",
"language:ndi",
"language:wom",
"language:zmz",
"language:nuu",
"language:bbp",
"language:yaj",
"language:bqk",
"language:bpd",
"language:liy",
"language:bfl",
"language:tor",
"language:gox",
"language:kuw",
"language:bjo",
"language:mnh",
"language:nue",
"language:lna",
"language:lnl",
"language:msj",
"language:doo",
"language:mfc",
"language:ndt",
"language:gyg",
"language:deq",
"language:mgn",
"language:ngb",
"language:nbw",
"language:yky",
"language:snj",
"language:muh",
"language:bbe",
"language:mdm",
"language:gdi",
"language:bme",
"language:bkc",
"language:gnz",
"language:gix",
"language:nbm",
"language:moj",
"language:kpl",
"language:yng",
"language:fer",
"language:myj",
"language:idr",
"language:tgy",
"language:ndz",
"language:swf",
"language:tbm",
"language:brm",
"language:pmb",
"language:geq",
"language:nzk",
"language:obl",
"language:gbv",
"language:mzv",
"language:aiy",
"language:ngg",
"language:gmm",
"language:gya",
"language:gbq",
"language:gbp",
"language:sqm",
"language:gso",
"language:vig",
"language:kfz",
"language:bwj",
"language:bwu",
"language:gux",
"language:bim",
"language:mfq",
"language:aks",
"language:pil",
"language:xkt",
"language:mos",
"language:saf",
"language:dgd",
"language:wlx",
"language:dgi",
"language:bfo",
"language:hag",
"language:jmr",
"language:beh",
"language:ntm",
"language:tbz",
"language:mql",
"language:bba",
"language:dos",
"language:kqm",
"language:las",
"language:dop",
"language:bqg",
"language:cll",
"language:pug",
"language:kst",
"language:vag",
"language:cli",
"language:tpm",
"language:sil",
"language:ssl",
"language:pnq",
"language:xsm",
"language:nuv",
"language:nnw",
"language:dya",
"language:cfa",
"language:awo",
"language:tul",
"language:kzc",
"language:nku",
"language:loi",
"language:lor",
"language:tsp",
"language:wib",
"language:xrb",
"language:kza",
"language:myk",
"language:sen",
"language:sep",
"language:spp",
"language:shz",
"language:seb",
"language:sev",
"language:plr",
"language:dyi",
"language:tgw",
"language:soy",
"language:ahp",
"language:fll",
"language:fal",
"language:jah",
"language:cwg",
"language:kns",
"language:knq",
"language:jhi",
"language:mnq",
"language:btq",
"language:tea",
"language:mhe",
"language:szc",
"language:sza",
"language:tmo",
"language:cua",
"language:kta",
"language:tkz",
"language:moo",
"language:tdr",
"language:hre",
"language:sed",
"language:kxy",
"language:hal",
"language:jeh",
"language:hld",
"language:rmx",
"language:alk",
"language:brb",
"language:oyb",
"language:krv",
"language:krr",
"language:lbo",
"language:sqq",
"language:cma",
"language:crw",
"language:mng",
"language:cmo",
"language:rka",
"language:mnn",
"language:stt",
"language:sti",
"language:hkn",
"language:tpu",
"language:tdf",
"language:stg",
"language:pac",
"language:ktv",
"language:kuf",
"language:tto",
"language:tth",
"language:bru",
"language:ncq",
"language:sct",
"language:sss",
"language:brv",
"language:nyl",
"language:aml",
"language:huo",
"language:mml",
"language:mqt",
"language:bgk",
"language:stu",
"language:lwl",
"language:lcp",
"language:rbb",
"language:pce",
"language:pll",
"language:kxm",
"language:okz",
"language:mra",
"language:khf",
"language:tyh",
"language:pnx",
"language:zng",
"language:ply",
"language:bbh",
"language:cbn",
"language:omx",
"language:gaq",
"language:gbj",
"language:bfw",
"language:biy",
"language:cdz",
"language:mmj",
"language:trd",
"language:asr",
"language:bix",
"language:ksz",
"language:ekl",
"language:mjx",
"language:juy",
"language:caq",
"language:ncb",
"language:aem",
"language:scb",
"language:hnu",
"language:tou",
"language:nuo",
"language:pyu",
"language:tay",
"language:szy",
"language:byq",
"language:kae",
"language:fos",
"language:atk",
"language:eno",
"language:nsy",
"language:bdb",
"language:duq",
"language:dun",
"language:apg",
"language:tjg",
"language:lbx",
"language:twy",
"language:kkx",
"language:otd",
"language:sya",
"language:abx",
"language:yka",
"language:slm",
"language:bdl",
"language:sjm",
"language:bdr",
"language:sse",
"language:sml",
"language:ssb",
"language:duw",
"language:mhy",
"language:pku",
"language:plt",
"language:bzc",
"language:xmv",
"language:bmm",
"language:xmw",
"language:tkg",
"language:bhr",
"language:txy",
"language:msh",
"language:bkr",
"language:nij",
"language:ivb",
"language:bgi",
"language:tiy",
"language:tbl",
"language:bpr",
"language:bps",
"language:bgz",
"language:bgb",
"language:zbt",
"language:mqn",
"language:bsu",
"language:bkz",
"language:xkq",
"language:vkl",
"language:xmz",
"language:tlk",
"language:wow",
"language:mzq",
"language:pdo",
"language:tdi",
"language:vko",
"language:raz",
"language:lbw",
"language:wru",
"language:xks",
"language:llm",
"language:bup",
"language:zka",
"language:ues",
"language:lix",
"language:pnp",
"language:bna",
"language:khc",
"language:bhq",
"language:dok",
"language:law",
"language:txm",
"language:bls",
"language:dms",
"language:ums",
"language:pee",
"language:tdj",
"language:toy",
"language:tvw",
"language:brs",
"language:kzf",
"language:lew",
"language:unz",
"language:myl",
"language:klw",
"language:pmf",
"language:ttp",
"language:sdu",
"language:wtw",
"language:kgx",
"language:wlo",
"language:pam",
"language:abc",
"language:sbl",
"language:blx",
"language:tre",
"language:txn",
"language:bay",
"language:mqi",
"language:lcd",
"language:lrn",
"language:woo",
"language:kvo",
"language:kpd",
"language:baj",
"language:kyd",
"language:udj",
"language:kvv",
"language:kvp",
"language:ksx",
"language:ski",
"language:slp",
"language:lwt",
"language:lmr",
"language:ila",
"language:lmj",
"language:lmq",
"language:lwe",
"language:kuk",
"language:kvh",
"language:mqy",
"language:riu",
"language:reb",
"language:rjg",
"language:end",
"language:ljl",
"language:nxe",
"language:nxg",
"language:ror",
"language:nea",
"language:xbr",
"language:mvd",
"language:akg",
"language:wnk",
"language:lmy",
"language:lur",
"language:bnd",
"language:wah",
"language:bvt",
"language:ges",
"language:bty",
"language:bgy",
"language:ste",
"language:sgu",
"language:hud",
"language:nni",
"language:nxl",
"language:spb",
"language:plh",
"language:kzb",
"language:lhh",
"language:hik",
"language:htu",
"language:tlu",
"language:kzx",
"language:hrk",
"language:amq",
"language:nul",
"language:ltu",
"language:spr",
"language:asl",
"language:bzn",
"language:alo",
"language:weo",
"language:huk",
"language:lcs",
"language:lox",
"language:alp",
"language:nae",
"language:kuv",
"language:tev",
"language:mhs",
"language:mqc",
"language:kzd",
"language:tlv",
"language:kei",
"language:jmd",
"language:oni",
"language:skz",
"language:urn",
"language:heg",
"language:idt",
"language:lka",
"language:hbu",
"language:tdt",
"language:krd",
"language:nxa",
"language:wmh",
"language:aaz",
"language:bkx",
"language:lva",
"language:dij",
"language:ddw",
"language:bcd",
"language:mxz",
"language:vme",
"language:sve",
"language:vbb",
"language:mss",
"language:emw",
"language:imr",
"language:tvm",
"language:kje",
"language:rmm",
"language:lti",
"language:slu",
"language:sws",
"language:tve",
"language:nil",
"language:srw",
"language:ilu",
"language:tzn",
"language:apx",
"language:wet",
"language:mgm",
"language:wlh",
"language:kem",
"language:tkd",
"language:pkg",
"language:anx",
"language:lek",
"language:ncc",
"language:lle",
"language:nss",
"language:twp",
"language:sbc",
"language:elu",
"language:los",
"language:mft",
"language:biq",
"language:llf",
"language:lid",
"language:sbh",
"language:npn",
"language:rak",
"language:lib",
"language:ler",
"language:ncn",
"language:pek",
"language:loj",
"language:pmn",
"language:ssg",
"language:wuv",
"language:ktk",
"language:goo",
"language:llx",
"language:lmv",
"language:aud",
"language:fud",
"language:mnv",
"language:tkp",
"language:num",
"language:nkp",
"language:tvl",
"language:pkp",
"language:tkl",
"language:sky",
"language:nuq",
"language:nur",
"language:nho",
"language:rap",
"language:mrq",
"language:mqm",
"language:mri",
"language:rkh",
"language:aut",
"language:fut",
"language:ton",
"language:bwb",
"language:wyy",
"language:pif",
"language:mpy",
"language:woe",
"language:mrl",
"language:puw",
"language:stw",
"language:nmt",
"language:pfa",
"language:tpv",
"language:sov",
"language:kos",
"language:nau",
"language:pma",
"language:mmg",
"language:lpa",
"language:etn",
"language:erk",
"language:bki",
"language:bnk",
"language:brj",
"language:mmm",
"language:lmu",
"language:lww",
"language:upv",
"language:aul",
"language:vrt",
"language:klv",
"language:ahb",
"language:psw",
"language:pgk",
"language:onu",
"language:mll",
"language:mvt",
"language:vao",
"language:lrv",
"language:mrs",
"language:dix",
"language:nvh",
"language:nms",
"language:rpn",
"language:app",
"language:sax",
"language:ske",
"language:sww",
"language:lml",
"language:omb",
"language:nnd",
"language:mkv",
"language:tmi",
"language:plb",
"language:tls",
"language:gnj",
"language:aor",
"language:akr",
"language:sku",
"language:tlm",
"language:nkk",
"language:ptr",
"language:tmt",
"language:vlp",
"language:vnp",
"language:alm",
"language:mrp",
"language:nrg",
"language:lmb",
"language:nsw",
"language:mnl",
"language:tsr",
"language:btr",
"language:mwo",
"language:urr",
"language:mrm",
"language:mtt",
"language:tgs",
"language:msn",
"language:hiw",
"language:lht",
"language:lkn",
"language:krf",
"language:lrz",
"language:vra",
"language:bgt",
"language:nlg",
"language:gri",
"language:lgr",
"language:mln",
"language:brr",
"language:tlr",
"language:lgu",
"language:apb",
"language:kwd",
"language:lgl",
"language:bvc",
"language:far",
"language:mlu",
"language:alu",
"language:dor",
"language:ora",
"language:aia",
"language:faf",
"language:dhv",
"language:nen",
"language:nee",
"language:jaz",
"language:pme",
"language:piz",
"language:fwa",
"language:nem",
"language:cam",
"language:pri",
"language:mrk",
"language:mkt",
"language:wmn",
"language:hvk",
"language:bwa",
"language:duf",
"language:nek",
"language:ane",
"language:aji",
"language:aqr",
"language:aok",
"language:cir",
"language:aty",
"language:iff",
"language:erg",
"language:uur",
"language:tnn",
"language:tnp",
"language:nwi",
"language:emi",
"language:tns",
"language:nlz",
"language:ntu",
"language:mla",
"language:neu",
"language:tkw",
"language:utp",
"language:aua",
"language:tqp",
"language:bjk",
"language:lbv",
"language:mmx",
"language:koa",
"language:sgz",
"language:kqw",
"language:rai",
"language:bxf",
"language:lbb",
"language:rri",
"language:baa",
"language:tva",
"language:vrs",
"language:ttu",
"language:urv",
"language:sol",
"language:nsn",
"language:ppn",
"language:pex",
"language:hao",
"language:hla",
"language:hah",
"language:tio",
"language:kzk",
"language:uge",
"language:mvo",
"language:mpr",
"language:rug",
"language:hoa",
"language:ksg",
"language:nke",
"language:sbb",
"language:lga",
"language:tgi",
"language:blp",
"language:jaj",
"language:mrn",
"language:gga",
"language:lgb",
"language:kji",
"language:grz",
"language:ksd",
"language:bjp",
"language:hrw",
"language:hrc",
"language:tbf",
"language:ncf",
"language:leu",
"language:nal",
"language:tbj",
"language:tgc",
"language:lcm",
"language:bnp",
"language:bjl",
"language:sij",
"language:lbu",
"language:ylu",
"language:msu",
"language:srf",
"language:adz",
"language:hob",
"language:zsa",
"language:zsu",
"language:waz",
"language:mpl",
"language:una",
"language:mcy",
"language:buk",
"language:kcl",
"language:kbm",
"language:tbx",
"language:pix",
"language:val",
"language:goc",
"language:dac",
"language:ksl",
"language:ptp",
"language:zeg",
"language:ymp",
"language:bch",
"language:kvc",
"language:ggt",
"language:mgl",
"language:mna",
"language:xsi",
"language:tmy",
"language:met",
"language:roe",
"language:bcu",
"language:mpn",
"language:wab",
"language:gdd",
"language:dad",
"language:mjk",
"language:tbc",
"language:apr",
"language:bbv",
"language:uvl",
"language:kdf",
"language:mee",
"language:aie",
"language:akt",
"language:avb",
"language:mwg",
"language:gip",
"language:aaw",
"language:bek",
"language:mbh",
"language:aix",
"language:xkx",
"language:pss",
"language:mpo",
"language:ssz",
"language:lmg",
"language:mwh",
"language:kzu",
"language:orz",
"language:bpg",
"language:kbi",
"language:ism",
"language:tpf",
"language:lio",
"language:sob",
"language:kxa",
"language:kbw",
"language:trb",
"language:mjm",
"language:bmc",
"language:mva",
"language:spe",
"language:kis",
"language:woc",
"language:svb",
"language:ykm",
"language:tmq",
"language:sry",
"language:aps",
"language:mbk",
"language:sso",
"language:aui",
"language:gvs",
"language:mbq",
"language:aai",
"language:ubr",
"language:mwc",
"language:dgg",
"language:pwg",
"language:bmk",
"language:mvn",
"language:tbo",
"language:grw",
"language:hgw",
"language:mum",
"language:tpa",
"language:wag",
"language:ylb",
"language:wed",
"language:ykk",
"language:klx",
"language:bwd",
"language:viv",
"language:yml",
"language:mzz",
"language:dob",
"language:dva",
"language:sew",
"language:bwf",
"language:gar",
"language:bdd",
"language:mwa",
"language:dww",
"language:kqf",
"language:kud",
"language:bxh",
"language:tte",
"language:oyy",
"language:unu",
"language:wgb",
"language:sbe",
"language:swp",
"language:oum",
"language:bmn",
"language:zgr",
"language:yob",
"language:snc",
"language:hul",
"language:khz",
"language:kbt",
"language:meu",
"language:kse",
"language:nrz",
"language:mek",
"language:don",
"language:rro",
"language:btp",
"language:kij",
"language:myw",
"language:nmw",
"language:tgo",
"language:nuw",
"language:mhz",
"language:tni",
"language:wrp",
"language:agf",
"language:bed",
"language:erw",
"language:dsn",
"language:mvx",
"language:rnn",
"language:gop",
"language:jau",
"language:amk",
"language:and",
"language:mvr",
"language:wbw",
"language:wad",
"language:mth",
"language:ppm",
"language:pmo",
"language:bsm",
"language:seu",
"language:kjr",
"language:wbb",
"language:yki",
"language:asz",
"language:bhc",
"language:wgo",
"language:xmt",
"language:kgb",
"language:lcc",
"language:wuy",
"language:xmx",
"language:bzq",
"language:mqa",
"language:ptn",
"language:mky",
"language:gzn",
"language:due",
"language:bik",
"language:mmn",
"language:dul",
"language:agk",
"language:agz",
"language:atl",
"language:bno",
"language:prh",
"language:msb",
"language:bvy",
"language:cbw",
"language:war",
"language:kyn",
"language:mtw",
"language:btw",
"language:sgd",
"language:tgn",
"language:atm",
"language:loc",
"language:srg",
"language:cyo",
"language:clu",
"language:daw",
"language:kyk",
"language:kll",
"language:kqe",
"language:ksn",
"language:mrw",
"language:bne",
"language:kzp",
"language:llq",
"language:swu",
"language:mog",
"language:pns",
"language:atd",
"language:mbt",
"language:msm",
"language:mbd",
"language:mqk",
"language:obo",
"language:mbi",
"language:mbb",
"language:bgs",
"language:mta",
"language:mbs",
"language:cgc",
"language:mba",
"language:tbw",
"language:bya",
"language:tgt",
"language:pwm",
"language:plc",
"language:plw",
"language:plv",
"language:bnj",
"language:twb",
"language:syb",
"language:sfe",
"language:stb",
"language:skn",
"language:suc",
"language:kaw",
"language:jvn",
"language:jas",
"language:osi",
"language:tes",
"language:agn",
"language:abl",
"language:ljp",
"language:byd",
"language:lra",
"language:bth",
"language:trx",
"language:sdo",
"language:rir",
"language:scg",
"language:sdq",
"language:sas",
"language:hro",
"language:cjm",
"language:cja",
"language:roc",
"language:cje",
"language:rgs",
"language:rog",
"language:huq",
"language:ibh",
"language:rad",
"language:dup",
"language:hji",
"language:xdy",
"language:omy",
"language:knl",
"language:sbx",
"language:ebc",
"language:gef",
"language:coa",
"language:pea",
"language:kvb",
"language:mui",
"language:mqg",
"language:bjn",
"language:bvu",
"language:bve",
"language:msi",
"language:btj",
"language:kxd",
"language:jax",
"language:mfb",
"language:lcf",
"language:zmi",
"language:pel",
"language:mhp",
"language:jak",
"language:pse",
"language:orn",
"language:ors",
"language:vkt",
"language:meo",
"language:mfa",
"language:zsm",
"language:mbf",
"language:mfp",
"language:ccm",
"language:mkn",
"language:lrt",
"language:pmy",
"language:abs",
"language:bpq",
"language:goq",
"language:xmm",
"language:max",
"language:bac",
"language:tnw",
"language:tnt",
"language:tdn",
"language:txs",
"language:mwt",
"language:mkm",
"language:skh",
"language:btz",
"language:btd",
"language:bbc",
"language:akb",
"language:btm",
"language:alj",
"language:iry",
"language:tdy",
"language:atz",
"language:ilo",
"language:isd",
"language:tiu",
"language:ibg",
"language:azt",
"language:att",
"language:atp",
"language:agt",
"language:itv",
"language:yog",
"language:gdg",
"language:gad",
"language:aqn",
"language:agy",
"language:itb",
"language:iti",
"language:knb",
"language:kyb",
"language:kml",
"language:tis",
"language:ity",
"language:kmk",
"language:bjx",
"language:kkg",
"language:blw",
"language:inn",
"language:bnc",
"language:obk",
"language:kne",
"language:itt",
"language:xnn",
"language:ifa",
"language:ifk",
"language:ifb",
"language:ifu",
"language:ilk",
"language:iwk",
"language:kak",
"language:kyj",
"language:duo",
"language:prf",
"language:duy",
"language:mxr",
"language:bhv",
"language:kys",
"language:xkn",
"language:xkd",
"language:bfg",
"language:xay",
"language:ree",
"language:mxd",
"language:sge",
"language:zbw",
"language:zbc",
"language:zbe",
"language:kyi",
"language:ttg",
"language:llk",
"language:kzi",
"language:lgi",
"language:lnd",
"language:snv",
"language:tgq",
"language:ulu",
"language:xky",
"language:pez",
"language:sib",
"language:pne",
"language:blj",
"language:bdg",
"language:dbj",
"language:dtr",
"language:bsy",
"language:bsb",
"language:kqr",
"language:kqt",
"language:grm",
"language:dkr",
"language:tgb",
"language:dtp",
"language:mqq",
"language:kzs",
"language:drg",
"language:dmv",
"language:dtb",
"language:abf",
"language:srk",
"language:txa",
"language:ruu",
"language:low",
"language:dmg",
"language:dpp",
"language:slg",
"language:sbr",
"language:gnq",
"language:plz",
"language:tih",
"language:mvv",
"language:bqr",
"language:ntd",
"language:itd",
"language:skp",
"language:kag",
"language:lhn",
"language:mel",
"language:dro",
"language:kxn",
"language:sdx",
"language:pni",
"language:xke",
"language:pud",
"language:puf",
"language:pnm",
"language:snr",
"language:bvk",
"language:bkn",
"language:umi",
"language:puj",
"language:pna",
"language:tld",
"language:sxn",
"language:snl",
"language:bnq",
"language:rth",
"language:cml",
"language:emb",
"language:tmn",
"language:kjc",
"language:bnu",
"language:mak",
"language:mqx",
"language:mdr",
"language:wmm",
"language:mli",
"language:dkk",
"language:pnc",
"language:ulm",
"language:kli",
"language:mqj",
"language:rob",
"language:tln",
"language:sda",
"language:lje",
"language:bhz",
"language:bep",
"language:npy",
"language:sko",
"language:skx",
"language:bzl",
"language:txe",
"language:uon",
"language:pzh",
"language:bzg",
"language:ppu",
"language:ayr",
"language:ayc",
"language:bbf",
"language:ckr",
"language:smg",
"language:uro",
"language:zmh",
"language:gum",
"language:ttk",
"language:kwi",
"language:awh",
"language:byl",
"language:adu",
"language:ahr",
"language:bpo",
"language:acb",
"language:rkw",
"language:xss",
"language:bqf",
"language:bsv",
"language:bcb",
"language:bhx",
"language:bbx",
"language:bvp",
"language:bkg",
"language:bso",
"language:ctc",
"language:cqd",
"language:cno",
"language:dso",
"language:fom",
"language:fum",
"language:geg",
"language:gok",
"language:goj",
"language:ids",
"language:ihi",
"language:nkf",
"language:irr",
"language:jya",
"language:jbe",
"language:kyp",
"language:kyv",
"language:kfj",
"language:xao",
"language:xhv",
"language:kqh",
"language:kso",
"language:okg",
"language:kkn",
"language:kze",
"language:kym",
"language:xnh",
"language:kex",
"language:xmq",
"language:wkb",
"language:lau",
"language:kvt",
"language:lmh",
"language:yne",
"language:lbg",
"language:lso",
"language:len",
"language:lrk",
"language:lov",
"language:luu",
"language:zlm",
"language:mzx",
"language:zrg",
"language:unx",
"language:ned",
"language:njd",
"language:nmj",
"language:nom",
"language:nrr",
"language:faz",
"language:tmk",
"language:kav",
"language:npb",
"language:oda",
"language:otk",
"language:olk",
"language:ont",
"language:prp",
"language:prd",
"language:phw",
"language:pok",
"language:npu",
"language:puc",
"language:put",
"language:pxm",
"language:rui",
"language:slj",
"language:szd",
"language:sdt",
"language:sls",
"language:nsv",
"language:ysp",
"language:npl",
"language:tgr",
"language:twm",
"language:teb",
"language:tyl",
"language:tgv",
"language:urf",
"language:whu",
"language:xin",
"language:ymg",
"language:yrs",
"language:yax",
"language:nqy",
"language:dwk",
"language:cey",
"language:clj",
"language:nlq",
"language:npg",
"language:rtc",
"language:csj",
"language:nby",
"language:aic",
"language:kih",
"language:pgi",
"language:auw",
"language:amn",
"language:smf",
"language:dnd",
"language:imn",
"language:snu",
"language:wrs",
"language:sow",
"language:upi",
"language:umo",
"language:otu",
"language:khs",
"language:onn",
"language:siq",
"language:beo",
"language:etr",
"language:gni",
"language:kii",
"language:paw",
"language:apy",
"language:car",
"language:ako",
"language:tri",
"language:way",
"language:kui",
"language:mzo",
"language:kbb",
"language:hix",
"language:waw",
"language:bkq",
"language:tmz",
"language:ciy",
"language:mcg",
"language:pev",
"language:yar",
"language:mbc",
"language:pbc",
"language:ake",
"language:atr",
"language:jru",
"language:dno",
"language:lmi",
"language:asv",
"language:mdi",
"language:mdk",
"language:bct",
"language:efe",
"language:mxh",
"language:bvq",
"language:luc",
"language:avu",
"language:log",
"language:lgg",
"language:kbo",
"language:omi",
"language:lul",
"language:snm",
"language:bot",
"language:bdh",
"language:blm",
"language:mwu",
"language:gbn",
"language:mgc",
"language:bex",
"language:nwm",
"language:kcm",
"language:kah",
"language:vae",
"language:kyq",
"language:jyy",
"language:glu",
"language:bdo",
"language:bxv",
"language:mne",
"language:hor",
"language:sba",
"language:lap",
"language:gqr",
"language:mge",
"language:dgk",
"language:sbz",
"language:kwv",
"language:kwg",
"language:kxj",
"language:trz",
"language:ite",
"language:orw",
"language:pay",
"language:sab",
"language:gym",
"language:kvn",
"language:cuk",
"language:brn",
"language:cjp",
"language:kog",
"language:mbp",
"language:tnd",
"language:tbn",
"language:tuf",
"language:tnb",
"language:gut",
"language:wac",
"language:noa",
"language:cto",
"language:bdc",
"language:emp",
"language:sja",
"language:tdc",
"language:cmi",
"language:ans",
"language:crf",
"language:alr",
"language:krk",
"language:boi",
"language:inz",
"language:puy",
"language:coj",
"language:coc",
"language:yuf",
"language:mov",
"language:xcm",
"language:xgr",
"language:onj",
"language:trh",
"language:mti",
"language:dgz",
"language:mnm",
"language:gnm",
"language:liu",
"language:djc",
"language:dau",
"language:njl",
"language:byg",
"language:daj",
"language:mdx",
"language:noz",
"language:she",
"language:dds",
"language:dto",
"language:dts",
"language:dbw",
"language:dbt",
"language:dbg",
"language:dtu",
"language:dti",
"language:dym",
"language:djm",
"language:dtt",
"language:dtm",
"language:tde",
"language:aqd",
"language:dgb",
"language:dmb",
"language:dol",
"language:tqm",
"language:kfb",
"language:nit",
"language:gau",
"language:gdb",
"language:kmj",
"language:mjt",
"language:xua",
"language:hoy",
"language:xuj",
"language:sle",
"language:kan",
"language:kfe",
"language:tcx",
"language:pkr",
"language:udg",
"language:kfa",
"language:all",
"language:aaf",
"language:kej",
"language:kfh",
"language:mjo",
"language:mjr",
"language:mal",
"language:mjq",
"language:kpb",
"language:thn",
"language:vis",
"language:ctt",
"language:wkl",
"language:wku",
"language:pty",
"language:yea",
"language:ima",
"language:mjp",
"language:oty",
"language:ymr",
"language:mjv",
"language:pcf",
"language:kep",
"language:ptq",
"language:yeu",
"language:kfd",
"language:vmd",
"language:brw",
"language:kfg",
"language:gno",
"language:emu",
"language:mut",
"language:wsg",
"language:esg",
"language:fmu",
"language:mrr",
"language:daq",
"language:kfc",
"language:uki",
"language:mha",
"language:peg",
"language:mmk",
"language:wbq",
"language:mju",
"language:kwx",
"language:xmu",
"language:xel",
"language:zmo",
"language:kxw",
"language:kkc",
"language:jko",
"language:smq",
"language:fiw",
"language:foi",
"language:bon",
"language:tof",
"language:mud",
"language:ike",
"language:kal",
"language:esi",
"language:ikt",
"language:ems",
"language:wrk",
"language:wny",
"language:bvz",
"language:dei",
"language:tfo",
"language:wor",
"language:brp",
"language:kpi",
"language:srt",
"language:bti",
"language:trt",
"language:zme",
"language:err",
"language:urc",
"language:jnj",
"language:myo",
"language:bwo",
"language:moy",
"language:cra",
"language:kqy",
"language:zay",
"language:bst",
"language:mdy",
"language:doz",
"language:mfx",
"language:oyd",
"language:wal",
"language:dwr",
"language:gmv",
"language:gof",
"language:gac",
"language:cui",
"language:gob",
"language:kbc",
"language:axb",
"language:moc",
"language:plg",
"language:tob",
"language:nid",
"language:wlg",
"language:hdn",
"language:hax",
"language:amr",
"language:hug",
"language:had",
"language:fuj",
"language:wrn",
"language:tic",
"language:hib",
"language:pnu",
"language:hmq",
"language:hea",
"language:hms",
"language:muq",
"language:mmr",
"language:bwx",
"language:hmj",
"language:hml",
"language:mww",
"language:hrm",
"language:hnj",
"language:hmf",
"language:hmv",
"language:huj",
"language:hmy",
"language:hmg",
"language:hmc",
"language:hme",
"language:hmi",
"language:hmh",
"language:hmm",
"language:hmp",
"language:hma",
"language:hmw",
"language:pha",
"language:bwn",
"language:buh",
"language:bje",
"language:bmt",
"language:mji",
"language:huu",
"language:xhu",
"language:xur",
"language:ijs",
"language:nkx",
"language:iby",
"language:okr",
"language:orr",
"language:ije",
"language:dbn",
"language:plq",
"language:xcr",
"language:xlu",
"language:hlu",
"language:xps",
"language:xld",
"language:xsd",
"language:xve",
"language:aln",
"language:aae",
"language:aat",
"language:xcl",
"language:axm",
"language:hyw",
"language:lvs",
"language:olt",
"language:orv",
"language:chu",
"language:svm",
"language:slv",
"language:xce",
"language:xga",
"language:xcg",
"language:xlp",
"language:xtg",
"language:wlm",
"language:owl",
"language:xbm",
"language:obt",
"language:oco",
"language:gla",
"language:ghc",
"language:nrc",
"language:got",
"language:ovd",
"language:jut",
"language:non",
"language:nob",
"language:nno",
"language:yid",
"language:sli",
"language:sxu",
"language:ydd",
"language:yih",
"language:ksh",
"language:lim",
"language:hrx",
"language:pdc",
"language:goh",
"language:gct",
"language:swg",
"language:wae",
"language:bar",
"language:geh",
"language:uln",
"language:jvd",
"language:pey",
"language:afr",
"language:oor",
"language:brc",
"language:dcr",
"language:skw",
"language:zea",
"language:odt",
"language:osx",
"language:nds",
"language:gml",
"language:pdt",
"language:gos",
"language:act",
"language:drt",
"language:sdz",
"language:stl",
"language:twd",
"language:vel",
"language:ang",
"language:yol",
"language:pih",
"language:eng",
"language:vic",
"language:bjs",
"language:gyn",
"language:trf",
"language:aig",
"language:afs",
"language:gul",
"language:bah",
"language:tch",
"language:svc",
"language:gcl",
"language:tgh",
"language:jam",
"language:bzj",
"language:bzk",
"language:srn",
"language:kww",
"language:kri",
"language:gpe",
"language:wes",
"language:pcm",
"language:hwc",
"language:rop",
"language:bis",
"language:pis",
"language:tpi",
"language:tcs",
"language:frr",
"language:ofs",
"language:fry",
"language:xpg",
"language:gmy",
"language:rge",
"language:cpg",
"language:pnt",
"language:yms",
"language:khw",
"language:san",
"language:gwt",
"language:sts",
"language:nli",
"language:bhu",
"language:keq",
"language:nhh",
"language:ksy",
"language:lbm",
"language:tnv",
"language:kfv",
"language:nag",
"language:rjs",
"language:key",
"language:lah",
"language:pnb",
"language:hno",
"language:hnd",
"language:phj",
"language:xhe",
"language:luv",
"language:sbn",
"language:lss",
"language:kfu",
"language:gom",
"language:omr",
"language:smv",
"language:vah",
"language:anr",
"language:raj",
"language:dub",
"language:gjk",
"language:vgr",
"language:kxp",
"language:wry",
"language:jnd",
"language:hoj",
"language:gda",
"language:gdx",
"language:rwr",
"language:bhe",
"language:gig",
"language:lmn",
"language:mve",
"language:kvx",
"language:bge",
"language:duh",
"language:gbl",
"language:mke",
"language:vaa",
"language:wbr",
"language:gas",
"language:gra",
"language:bhi",
"language:rtw",
"language:noi",
"language:dty",
"language:jns",
"language:mjl",
"language:bht",
"language:kfs",
"language:cdh",
"language:pgg",
"language:cdj",
"language:bhd",
"language:lhl",
"language:kfx",
"language:bfz",
"language:dhn",
"language:khn",
"language:pli",
"language:anp",
"language:hns",
"language:xis",
"language:kyw",
"language:tdb",
"language:sdr",
"language:sck",
"language:thr",
"language:the",
"language:tkt",
"language:thq",
"language:thl",
"language:soi",
"language:tkb",
"language:mjz",
"language:smm",
"language:kra",
"language:dry",
"language:dwz",
"language:pwr",
"language:sgj",
"language:dmk",
"language:rmn",
"language:rml",
"language:rmq",
"language:rmf",
"language:bra",
"language:bjj",
"language:bha",
"language:bns",
"language:hca",
"language:hif",
"language:hin",
"language:urd",
"language:ghr",
"language:ggg",
"language:odk",
"language:hkh",
"language:wsv",
"language:mvy",
"language:clh",
"language:gwf",
"language:nlm",
"language:tra",
"language:bkk",
"language:scl",
"language:plk",
"language:ush",
"language:sdg",
"language:div",
"language:ved",
"language:ave",
"language:bgp",
"language:ktl",
"language:bcc",
"language:bgn",
"language:rdb",
"language:srz",
"language:gzi",
"language:ntz",
"language:soj",
"language:nyq",
"language:lsa",
"language:sgr",
"language:sqo",
"language:kur",
"language:ckb",
"language:kmr",
"language:sdh",
"language:zza",
"language:hac",
"language:bjm",
"language:sdf",
"language:xkc",
"language:vmh",
"language:xkj",
"language:xkp",
"language:tov",
"language:hrz",
"language:avd",
"language:esh",
"language:rat",
"language:tks",
"language:atn",
"language:vaf",
"language:oos",
"language:yai",
"language:yah",
"language:oru",
"language:prc",
"language:wne",
"language:pst",
"language:pbu",
"language:pbt",
"language:kho",
"language:xtq",
"language:peo",
"language:pal",
"language:zum",
"language:jdt",
"language:ttt",
"language:jpr",
"language:aiq",
"language:prs",
"language:haz",
"language:bhh",
"language:lrl",
"language:def",
"language:lrc",
"language:bqi",
"language:luz",
"language:ask",
"language:xvi",
"language:trm",
"language:xfa",
"language:lat",
"language:ruo",
"language:ruq",
"language:itk",
"language:sdc",
"language:rgn",
"language:pms",
"language:fro",
"language:frc",
"language:rcf",
"language:cks",
"language:hat",
"language:gcr",
"language:acf",
"language:gcf",
"language:scf",
"language:mfe",
"language:crs",
"language:frp",
"language:osp",
"language:lad",
"language:pln",
"language:cbk",
"language:tmg",
"language:fax",
"language:aoa",
"language:pre",
"language:cri",
"language:mzs",
"language:tvy",
"language:kea",
"language:pap",
"language:pov",
"language:mxi",
"language:sdn",
"language:sro",
"language:src",
"language:osc",
"language:xum",
"language:xhr",
"language:umc",
"language:pgn",
"language:xvs",
"language:sbv",
"language:spx",
"language:xae",
"language:ims",
"language:xvo",
"language:xto",
"language:txb",
"language:xdc",
"language:xls",
"language:cms",
"language:txh",
"language:irn",
"language:lre",
"language:sqn",
"language:ntw",
"language:wdt",
"language:amg",
"language:ilg",
"language:ibd",
"language:ojp",
"language:kzg",
"language:okn",
"language:tkn",
"language:ryn",
"language:ams",
"language:ryu",
"language:mvi",
"language:anq",
"language:oon",
"language:acu",
"language:hub",
"language:kec",
"language:tey",
"language:kgo",
"language:tbr",
"language:kcp",
"language:xtc",
"language:mbr",
"language:vkm",
"language:awi",
"language:oge",
"language:jge",
"language:xat",
"language:kiq",
"language:alc",
"language:kbx",
"language:kee",
"language:kjq",
"language:kqz",
"language:xii",
"language:shg",
"language:tyu",
"language:xuu",
"language:nhr",
"language:pie",
"language:lax",
"language:tix",
"language:bcf",
"language:kiw",
"language:kjd",
"language:kmx",
"language:kxz",
"language:mdb",
"language:mcq",
"language:aom",
"language:nvm",
"language:bbb",
"language:bdf",
"language:kpx",
"language:kbk",
"language:kqi",
"language:nqm",
"language:kig",
"language:udu",
"language:jje",
"language:aja",
"language:bjw",
"language:hwa",
"language:btg",
"language:kyf",
"language:bev",
"language:god",
"language:bet",
"language:ney",
"language:gud",
"language:dic",
"language:kwp",
"language:blh",
"language:ahm",
"language:ahi",
"language:grj",
"language:gbo",
"language:gry",
"language:grv",
"language:gec",
"language:pye",
"language:ktj",
"language:ted",
"language:dee",
"language:ggb",
"language:tja",
"language:nwb",
"language:das",
"language:glr",
"language:oub",
"language:krn",
"language:krw",
"language:gxx",
"language:wec",
"language:big",
"language:kup",
"language:wer",
"language:mfw",
"language:huf",
"language:ksj",
"language:srl",
"language:bqb",
"language:xau",
"language:tip",
"language:air",
"language:kwo",
"language:huc",
"language:awr",
"language:rac",
"language:spi",
"language:duv",
"language:dbf",
"language:tty",
"language:tds",
"language:tcq",
"language:kkb",
"language:pas",
"language:tad",
"language:fau",
"language:owi",
"language:amm",
"language:nax",
"language:niw",
"language:bpw",
"language:xkw",
"language:lpe",
"language:rmh",
"language:wux",
"language:can",
"language:yee",
"language:xop",
"language:mtf",
"language:byz",
"language:ado",
"language:grq",
"language:aki",
"language:anj",
"language:brq",
"language:rmk",
"language:igg",
"language:xoi",
"language:aod",
"language:tbs",
"language:tgu",
"language:gai",
"language:aya",
"language:bqs",
"language:wax",
"language:mdg",
"language:sbj",
"language:kth",
"language:mde",
"language:kie",
"language:rou",
"language:kgw",
"language:mjd",
"language:nmu",
"language:vmv",
"language:luf",
"language:mze",
"language:bwk",
"language:mnu",
"language:zrs",
"language:etz",
"language:bqc",
"language:bus",
"language:bqp",
"language:sho",
"language:stj",
"language:sym",
"language:sbd",
"language:lda",
"language:neb",
"language:goa",
"language:yre",
"language:xgb",
"language:moa",
"language:bxl",
"language:lig",
"language:tjn",
"language:bof",
"language:rkm",
"language:emk",
"language:mku",
"language:mzj",
"language:msc",
"language:mxx",
"language:jod",
"language:jud",
"language:kfo",
"language:kga",
"language:mnk",
"language:xkg",
"language:mwk",
"language:jad",
"language:mlq",
"language:kao",
"language:kke",
"language:knk",
"language:llc",
"language:kno",
"language:yal",
"language:gkp",
"language:knu",
"language:xpe",
"language:lom",
"language:tod",
"language:bza",
"language:men",
"language:bbo",
"language:bwq",
"language:sos",
"language:bxw",
"language:dux",
"language:dnn",
"language:cpo",
"language:bze",
"language:boo",
"language:boz",
"language:skq",
"language:mpc",
"language:alh",
"language:mec",
"language:wnd",
"language:djj",
"language:bvr",
"language:kqc",
"language:mds",
"language:hoz",
"language:sze",
"language:mhg",
"language:mca",
"language:crt",
"language:crq",
"language:mtp",
"language:wlv",
"language:mzh",
"language:kek",
"language:usp",
"language:quv",
"language:qum",
"language:tzj",
"language:ckz",
"language:quc",
"language:poc",
"language:poh",
"language:agu",
"language:ixl",
"language:ttc",
"language:emy",
"language:ctu",
"language:chf",
"language:caa",
"language:toj",
"language:mhc",
"language:jac",
"language:kjb",
"language:itz",
"language:mop",
"language:nug",
"language:nji",
"language:wmb",
"language:miq",
"language:ccr",
"language:mtn",
"language:yan",
"language:ulw",
"language:krb",
"language:pmw",
"language:csm",
"language:nsq",
"language:skd",
"language:csi",
"language:lmw",
"language:plo",
"language:pos",
"language:mto",
"language:mxp",
"language:mco",
"language:mir",
"language:mzl",
"language:mxq",
"language:neq",
"language:zoh",
"language:zoc",
"language:zos",
"language:zor",
"language:poi",
"language:zoq",
"language:poq",
"language:yec",
"language:gjr",
"language:mue",
"language:kdw",
"language:mso",
"language:zkt",
"language:mhj",
"language:bua",
"language:mon",
"language:bxu",
"language:bxm",
"language:bxr",
"language:khk",
"language:mvf",
"language:xal",
"language:yuy",
"language:sce",
"language:kxs",
"language:mxk",
"language:kxq",
"language:krz",
"language:jei",
"language:nkm",
"language:ncm",
"language:nex",
"language:nqn",
"language:nmx",
"language:mxw",
"language:stk",
"language:bow",
"language:tci",
"language:mus",
"language:mik",
"language:xap",
"language:mbj",
"language:kwa",
"language:yab",
"language:kpt",
"language:xag",
"language:sae",
"language:nab",
"language:wmd",
"language:lkd",
"language:ltn",
"language:xtw",
"language:naa",
"language:tlg",
"language:acz",
"language:tqr",
"language:bzf",
"language:nud",
"language:abt",
"language:wos",
"language:mle",
"language:kxt",
"language:spk",
"language:bry",
"language:gbf",
"language:sdk",
"language:keo",
"language:mqu",
"language:ukv",
"language:imt",
"language:lgo",
"language:lqr",
"language:oie",
"language:nsg",
"language:mas",
"language:kdj",
"language:nnj",
"language:kln",
"language:sgc",
"language:niq",
"language:enb",
"language:pko",
"language:oki",
"language:bdi",
"language:jum",
"language:mfz",
"language:dip",
"language:diw",
"language:dik",
"language:dib",
"language:dks",
"language:anu",
"language:bxb",
"language:lwo",
"language:thu",
"language:ach",
"language:adh",
"language:luo",
"language:kdi",
"language:laj",
"language:kja",
"language:grs",
"language:kmt",
"language:tby",
"language:gbi",
"language:mqo",
"language:kax",
"language:pgu",
"language:tlb",
"language:tuj",
"language:ibu",
"language:saj",
"language:wli",
"language:tvo",
"language:roo",
"language:onw",
"language:mei",
"language:brk",
"language:drb",
"language:kdu",
"language:elh",
"language:kko",
"language:wll",
"language:xeu",
"language:opo",
"language:oro",
"language:bey",
"language:lkl",
"language:uri",
"language:wmo",
"language:avt",
"language:elk",
"language:ong",
"language:urt",
"language:aon",
"language:aah",
"language:ape",
"language:ymb",
"language:eit",
"language:xbi",
"language:aur",
"language:bvn",
"language:but",
"language:kms",
"language:urx",
"language:niz",
"language:yll",
"language:aof",
"language:aag",
"language:ygl",
"language:ymo",
"language:yde",
"language:gnu",
"language:stf",
"language:sbi",
"language:okk",
"language:osu",
"language:oin",
"language:onk",
"language:aun",
"language:onr",
"language:aif",
"language:yyu",
"language:yis",
"language:ghs",
"language:ykr",
"language:sue",
"language:zia",
"language:bhg",
"language:nou",
"language:dgx",
"language:gcn",
"language:kpr",
"language:aez",
"language:hkk",
"language:okv",
"language:kgq",
"language:xse",
"language:cns",
"language:asy",
"language:txt",
"language:diy",
"language:tml",
"language:asi",
"language:psa",
"language:awy",
"language:yir",
"language:aws",
"language:ahh",
"language:awu",
"language:ktt",
"language:wms",
"language:aax",
"language:bwp",
"language:tyn",
"language:wng",
"language:saw",
"language:kzv",
"language:opk",
"language:aip",
"language:kwr",
"language:kti",
"language:kts",
"language:bhl",
"language:fai",
"language:stm",
"language:tlf",
"language:tif",
"language:urm",
"language:mpt",
"language:sug",
"language:nkj",
"language:tkx",
"language:imo",
"language:ubu",
"language:mux",
"language:med",
"language:mbw",
"language:gam",
"language:nac",
"language:cjv",
"language:nof",
"language:gvf",
"language:sst",
"language:whg",
"language:wgi",
"language:nbq",
"language:wno",
"language:dnt",
"language:hap",
"language:dni",
"language:dna",
"language:wlw",
"language:ndx",
"language:yli",
"language:nlk",
"language:yac",
"language:enq",
"language:ipi",
"language:kyc",
"language:leq",
"language:mme",
"language:asj",
"language:bir",
"language:net",
"language:hui",
"language:ssx",
"language:akh",
"language:aoe",
"language:kew",
"language:kjs",
"language:kjy",
"language:mpv",
"language:nop",
"language:nif",
"language:noc",
"language:fag",
"language:mhf",
"language:nis",
"language:skc",
"language:nkg",
"language:nej",
"language:ufi",
"language:nnf",
"language:klt",
"language:smc",
"language:klh",
"language:yuw",
"language:iou",
"language:awx",
"language:frq",
"language:dge",
"language:mtv",
"language:bmp",
"language:gka",
"language:ygm",
"language:nnk",
"language:mjn",
"language:bop",
"language:yut",
"language:ytw",
"language:ons",
"language:slw",
"language:kqb",
"language:sej",
"language:kmg",
"language:mlh",
"language:mpp",
"language:msz",
"language:noh",
"language:kco",
"language:kuo",
"language:tim",
"language:spl",
"language:mci",
"language:naf",
"language:ded",
"language:tbv",
"language:gaf",
"language:for",
"language:gim",
"language:aso",
"language:zuh",
"language:bef",
"language:snp",
"language:yby",
"language:ino",
"language:kbq",
"language:kmu",
"language:kyg",
"language:ygr",
"language:abg",
"language:isa",
"language:usa",
"language:awb",
"language:agd",
"language:gaj",
"language:tbg",
"language:omw",
"language:waj",
"language:kyy",
"language:gat",
"language:ali",
"language:koz",
"language:wsk",
"language:tnh",
"language:ped",
"language:pla",
"language:bie",
"language:mvq",
"language:xow",
"language:mjj",
"language:ybm",
"language:ukg",
"language:yrw",
"language:kmf",
"language:gmu",
"language:bbd",
"language:igo",
"language:pnr",
"language:bmx",
"language:gap",
"language:gyb",
"language:rmp",
"language:ydk",
"language:bpi",
"language:mcz",
"language:sra",
"language:xsp",
"language:utu",
"language:mqe",
"language:nbk",
"language:rpt",
"language:mqv",
"language:mqw",
"language:swm",
"language:wmc",
"language:mtc",
"language:kpw",
"language:kmh",
"language:taw",
"language:wdg",
"language:pda",
"language:msx",
"language:xes",
"language:ssj",
"language:awm",
"language:lei",
"language:pup",
"language:ssd",
"language:bpu",
"language:mdc",
"language:jil",
"language:rea",
"language:ynl",
"language:dnr",
"language:urg",
"language:bpm",
"language:gsp",
"language:ggl",
"language:spd",
"language:ybo",
"language:eip",
"language:mtg",
"language:kpq",
"language:kkl",
"language:nps",
"language:mnz",
"language:wod",
"language:auu",
"language:daz",
"language:opy",
"language:kqq",
"language:acs",
"language:xkr",
"language:xav",
"language:xer",
"language:xok",
"language:zkp",
"language:txu",
"language:xra",
"language:pth",
"language:xxr",
"language:aft",
"language:nyi",
"language:wwr",
"language:xnm",
"language:dyd",
"language:ywr",
"language:nmp",
"language:bcj",
"language:djw",
"language:dyb",
"language:nyv",
"language:azm",
"language:azg",
"language:cux",
"language:cut",
"language:mbz",
"language:mix",
"language:mxb",
"language:mxa",
"language:mks",
"language:mih",
"language:vmj",
"language:mxt",
"language:mjc",
"language:mtu",
"language:mio",
"language:mza",
"language:xtd",
"language:vmm",
"language:mil",
"language:mqh",
"language:mxs",
"language:xtp",
"language:xts",
"language:vmx",
"language:mab",
"language:mim",
"language:xta",
"language:mxv",
"language:xty",
"language:mip",
"language:mxy",
"language:vmq",
"language:miz",
"language:xtu",
"language:mtx",
"language:miu",
"language:xtb",
"language:mii",
"language:mit",
"language:miy",
"language:vmc",
"language:jmx",
"language:mib",
"language:mce",
"language:xtm",
"language:xtn",
"language:mie",
"language:xtj",
"language:mig",
"language:mdv",
"language:xti",
"language:meh",
"language:xtl",
"language:mpm",
"language:mvg",
"language:trs",
"language:trc",
"language:trq",
"language:coz",
"language:pbe",
"language:poe",
"language:pps",
"language:pbf",
"language:pow",
"language:pca",
"language:vmp",
"language:maa",
"language:maq",
"language:maj",
"language:vmy",
"language:mzi",
"language:mau",
"language:vmz",
"language:zap",
"language:czn",
"language:cta",
"language:cly",
"language:cya",
"language:ctp",
"language:ctz",
"language:zoo",
"language:zaf",
"language:zpy",
"language:zaw",
"language:zpf",
"language:ztn",
"language:zas",
"language:ztt",
"language:ztl",
"language:zpi",
"language:zpr",
"language:zax",
"language:ztg",
"language:zpm",
"language:zpg",
"language:zpe",
"language:zpa",
"language:zpj",
"language:zpv",
"language:ztu",
"language:zab",
"language:zai",
"language:zac",
"language:ztx",
"language:zpn",
"language:zts",
"language:zpb",
"language:ztp",
"language:zao",
"language:ztm",
"language:zpc",
"language:zad",
"language:zat",
"language:zpu",
"language:zav",
"language:zpq",
"language:zar",
"language:zty",
"language:zcd",
"language:zsr",
"language:zaq",
"language:zaa",
"language:zpd",
"language:zae",
"language:zca",
"language:zpo",
"language:zpk",
"language:zpt",
"language:zps",
"language:zpx",
"language:zte",
"language:zpz",
"language:zpw",
"language:zph",
"language:zpp",
"language:zpl",
"language:chj",
"language:cso",
"language:cuc",
"language:csa",
"language:ctl",
"language:cpa",
"language:cnt",
"language:chz",
"language:cvn",
"language:cnl",
"language:cle",
"language:cte",
"language:cco",
"language:chq",
"language:pei",
"language:ocu",
"language:mat",
"language:maz",
"language:mmc",
"language:otm",
"language:otn",
"language:otx",
"language:ote",
"language:otq",
"language:otz",
"language:otl",
"language:ots",
"language:ott",
"language:pbs",
"language:pmq",
"language:pmz",
"language:cip",
"language:sut",
"language:tpc",
"language:tcf",
"language:tpx",
"language:tpl",
"language:idi",
"language:atw",
"language:dbl",
"language:mwp",
"language:gbb",
"language:axl",
"language:aly",
"language:adg",
"language:amx",
"language:aer",
"language:are",
"language:axe",
"language:wgu",
"language:bjb",
"language:gvy",
"language:nnr",
"language:nwo",
"language:jui",
"language:nnv",
"language:wrm",
"language:mem",
"language:nna",
"language:wbp",
"language:wrl",
"language:wmt",
"language:gue",
"language:dmw",
"language:ddj",
"language:rxd",
"language:mpj",
"language:kux",
"language:piu",
"language:ntj",
"language:pjt",
"language:kdd",
"language:ant",
"language:ktd",
"language:jan",
"language:yxg",
"language:xbe",
"language:yub",
"language:ktg",
"language:ylr",
"language:yda",
"language:bzr",
"language:gnl",
"language:gdc",
"language:gyf",
"language:gwu",
"language:kgl",
"language:zmk",
"language:wdu",
"language:xyb",
"language:gyy",
"language:zmc",
"language:xpt",
"language:xwk",
"language:bxi",
"language:dif",
"language:nmv",
"language:yry",
"language:ynd",
"language:yww",
"language:hrp",
"language:ard",
"language:pit",
"language:xpa",
"language:dyn",
"language:nyx",
"language:jao",
"language:xtv",
"language:wga",
"language:yil",
"language:nyt",
"language:ljx",
"language:ggd",
"language:ikr",
"language:tgz",
"language:typ",
"language:pkn",
"language:wua",
"language:kbe",
"language:kuy",
"language:umd",
"language:fln",
"language:wie",
"language:wih",
"language:wij",
"language:wim",
"language:uwa",
"language:ugb",
"language:xmp",
"language:wik",
"language:lby",
"language:xmy",
"language:nxn",
"language:xyt",
"language:xyj",
"language:xyk",
"language:wnn",
"language:mvl",
"language:nlw",
"language:xut",
"language:aea",
"language:yxm",
"language:awg",
"language:gwm",
"language:dgt",
"language:xgd",
"language:amz",
"language:avm",
"language:aid",
"language:xpj",
"language:kkp",
"language:uky",
"language:bjy",
"language:xgm",
"language:gmr",
"language:yia",
"language:nha",
"language:bia",
"language:vml",
"language:wbv",
"language:lkm",
"language:nju",
"language:kba",
"language:xbp",
"language:xgg",
"language:pnj",
"language:xwj",
"language:wxw",
"language:bxj",
"language:pnv",
"language:bxn",
"language:dhl",
"language:dze",
"language:iin",
"language:dhr",
"language:wri",
"language:nhf",
"language:tju",
"language:vka",
"language:nrl",
"language:ywg",
"language:vku",
"language:yij",
"language:nrk",
"language:nly",
"language:bdy",
"language:zmu",
"language:nbn",
"language:awk",
"language:kda",
"language:xbj",
"language:xrd",
"language:xul",
"language:dhu",
"language:xjt",
"language:xni",
"language:kgs",
"language:xya",
"language:gnr",
"language:dhx",
"language:wkw",
"language:wlu",
"language:ddr",
"language:pmd",
"language:yxy",
"language:wth",
"language:llj",
"language:dmd",
"language:rnr",
"language:xwd",
"language:xwt",
"language:weg",
"language:dgw",
"language:wyi",
"language:xbg",
"language:dda",
"language:xth",
"language:yga",
"language:wdk",
"language:yxl",
"language:kky",
"language:djf",
"language:gvn",
"language:vmu",
"language:dax",
"language:dhg",
"language:djr",
"language:guf",
"language:dwu",
"language:gnn",
"language:dwy",
"language:djb",
"language:dji",
"language:lja",
"language:jay",
"language:cbr",
"language:ktx",
"language:tux",
"language:cao",
"language:kuq",
"language:pcp",
"language:pno",
"language:sni",
"language:kaq",
"language:shp",
"language:amc",
"language:cbs",
"language:swo",
"language:mcd",
"language:yaa",
"language:ywn",
"language:mts",
"language:atc",
"language:mzr",
"language:knt",
"language:isc",
"language:nuc",
"language:pyn",
"language:mpq",
"language:xor",
"language:xpk",
"language:cav",
"language:tna",
"language:aro",
"language:tno",
"language:enr",
"language:yuj",
"language:wfg",
"language:dmu",
"language:ttn",
"language:pnn",
"language:nef",
"language:mod",
"language:dep",
"language:cpi",
"language:tas",
"language:bxo",
"language:gib",
"language:bpl",
"language:hmo",
"language:njt",
"language:fng",
"language:pom",
"language:poo",
"language:pej",
"language:peq",
"language:prr",
"language:qvp",
"language:qvl",
"language:qxa",
"language:qub",
"language:qvm",
"language:qxh",
"language:qvh",
"language:qwh",
"language:qxn",
"language:qxo",
"language:qwa",
"language:qws",
"language:qvw",
"language:qxw",
"language:qva",
"language:qvn",
"language:qxt",
"language:qvc",
"language:quf",
"language:qwc",
"language:quk",
"language:qvs",
"language:qxu",
"language:quy",
"language:qul",
"language:qus",
"language:quh",
"language:qud",
"language:qxl",
"language:qvj",
"language:qxr",
"language:qvi",
"language:qvo",
"language:quw",
"language:qvz",
"language:qup",
"language:quz",
"language:qve",
"language:qxp",
"language:qxc",
"language:qux",
"language:ras",
"language:tqn",
"language:uma",
"language:byt",
"language:kgf",
"language:kbl",
"language:txj",
"language:krt",
"language:knc",
"language:bms",
"language:kby",
"language:dzg",
"language:tuq",
"language:blc",
"language:hur",
"language:sec",
"language:str",
"language:slh",
"language:ska",
"language:sno",
"language:clm",
"language:cow",
"language:col",
"language:fla",
"language:spo",
"language:slc",
"language:wpc",
"language:kbv",
"language:nxx",
"language:set",
"language:aau",
"language:aad",
"language:iwm",
"language:cjn",
"language:wog",
"language:kmo",
"language:kwj",
"language:sim",
"language:kmn",
"language:xrw",
"language:bye",
"language:ayq",
"language:psq",
"language:nux",
"language:bjh",
"language:bnw",
"language:mbx",
"language:siv",
"language:dju",
"language:amp",
"language:knr",
"language:sny",
"language:ham",
"language:gbe",
"language:pin",
"language:akq",
"language:nnm",
"language:sht",
"language:aen",
"language:asw",
"language:mzg",
"language:psd",
"language:afg",
"language:sqk",
"language:aed",
"language:csx",
"language:gsm",
"language:hsl",
"language:mdl",
"language:lsy",
"language:mzy",
"language:ncs",
"language:psg",
"language:sqs",
"language:tza",
"language:lsn",
"language:tsm",
"language:zsl",
"language:zib",
"language:esl",
"language:lbs",
"language:sdl",
"language:nsr",
"language:bfi",
"language:nzs",
"language:asf",
"language:pgz",
"language:nbs",
"language:sfs",
"language:csg",
"language:pys",
"language:ugy",
"language:hab",
"language:hos",
"language:csl",
"language:gsg",
"language:isr",
"language:pso",
"language:sgg",
"language:nsp",
"language:ins",
"language:pks",
"language:jsl",
"language:kvk",
"language:tss",
"language:asp",
"language:asq",
"language:bzs",
"language:eso",
"language:fsl",
"language:gss",
"language:isg",
"language:lsl",
"language:mfs",
"language:psp",
"language:ssr",
"language:doq",
"language:eth",
"language:gse",
"language:gus",
"language:xms",
"language:psl",
"language:fcs",
"language:esn",
"language:sgx",
"language:tsq",
"language:lst",
"language:ase",
"language:jls",
"language:csr",
"language:hds",
"language:lsp",
"language:xml",
"language:kgi",
"language:cds",
"language:nsi",
"language:rsn",
"language:ugn",
"language:bvl",
"language:csn",
"language:ecs",
"language:prl",
"language:csc",
"language:vsv",
"language:bqn",
"language:cse",
"language:hsh",
"language:rms",
"language:svk",
"language:dse",
"language:sfb",
"language:vgt",
"language:ise",
"language:slf",
"language:tse",
"language:dsl",
"language:icl",
"language:mzc",
"language:nsl",
"language:ysl",
"language:haf",
"language:csd",
"language:lls",
"language:vsi",
"language:msr",
"language:ukl",
"language:rsl",
"language:ssp",
"language:vsl",
"language:psr",
"language:swl",
"language:fss",
"language:fse",
"language:csf",
"language:ils",
"language:ads",
"language:lsc",
"language:syy",
"language:bfk",
"language:rib",
"language:rnb",
"language:gds",
"language:iks",
"language:jcs",
"language:jhs",
"language:jus",
"language:dsz",
"language:mre",
"language:rsm",
"language:ehs",
"language:okl",
"language:lsw",
"language:lsv",
"language:szs",
"language:tsy",
"language:uks",
"language:msd",
"language:prz",
"language:ole",
"language:dka",
"language:dzl",
"language:tgf",
"language:kjz",
"language:xkf",
"language:xkz",
"language:xct",
"language:zau",
"language:prx",
"language:bod",
"language:hut",
"language:lhm",
"language:ola",
"language:dre",
"language:tcn",
"language:ttz",
"language:kgy",
"language:muk",
"language:jul",
"language:nao",
"language:khg",
"language:tsk",
"language:nes",
"language:sbu",
"language:jda",
"language:spt",
"language:sgt",
"language:cgk",
"language:gro",
"language:dzo",
"language:lya",
"language:luk",
"language:kbg",
"language:adx",
"language:kzq",
"language:ghh",
"language:ghe",
"language:tge",
"language:skj",
"language:gvr",
"language:npa",
"language:chx",
"language:taj",
"language:tdg",
"language:rnp",
"language:rgk",
"language:cdn",
"language:bee",
"language:xns",
"language:tpq",
"language:jna",
"language:scu",
"language:lae",
"language:kkf",
"language:tsj",
"language:trp",
"language:ria",
"language:tpe",
"language:usi",
"language:xac",
"language:aot",
"language:kdq",
"language:ruh",
"language:ckh",
"language:zkd",
"language:tcl",
"language:nbc",
"language:nbe",
"language:nph",
"language:nnp",
"language:kix",
"language:lzn",
"language:umn",
"language:njb",
"language:tvt",
"language:ugo",
"language:hpo",
"language:mhx",
"language:bxd",
"language:tco",
"language:dnv",
"language:int",
"language:obr",
"language:tvn",
"language:rmz",
"language:yip",
"language:phq",
"language:bzi",
"language:lwm",
"language:pyy",
"language:cnc",
"language:how",
"language:byo",
"language:enu",
"language:ktp",
"language:aeu",
"language:ahk",
"language:ycp",
"language:ymd",
"language:slt",
"language:jiy",
"language:jiu",
"language:lkc",
"language:lhi",
"language:kaf",
"language:ysd",
"language:lwu",
"language:yiq",
"language:ylm",
"language:ymh",
"language:ysg",
"language:yku",
"language:ykn",
"language:yik",
"language:ywl",
"language:ywt",
"language:yit",
"language:llh",
"language:ylo",
"language:lgh",
"language:ytp",
"language:ymq",
"language:ybk",
"language:ypm",
"language:ymx",
"language:ymc",
"language:ypn",
"language:ypb",
"language:yhl",
"language:ykl",
"language:yzk",
"language:nsd",
"language:nos",
"language:yiv",
"language:iii",
"language:ygp",
"language:smh",
"language:ysy",
"language:ywq",
"language:yyz",
"language:ych",
"language:ywu",
"language:yig",
"language:yna",
"language:yif",
"language:aub",
"language:ypp",
"language:ypz",
"language:ypa",
"language:ypo",
"language:aza",
"language:yix",
"language:yiz",
"language:yso",
"language:nuf",
"language:zal",
"language:ers",
"language:nru",
"language:qvy",
"language:pmi",
"language:pmj",
"language:qxs",
"language:tji",
"language:tjs",
"language:txo",
"language:lep",
"language:lhp",
"language:drq",
"language:kgj",
"language:kip",
"language:kif",
"language:kjl",
"language:mgp",
"language:mrd",
"language:raq",
"language:rav",
"language:cuw",
"language:kle",
"language:ncd",
"language:rab",
"language:raa",
"language:wly",
"language:cur",
"language:aph",
"language:byw",
"language:lbr",
"language:lrr",
"language:ybi",
"language:emg",
"language:raf",
"language:jee",
"language:bhj",
"language:vay",
"language:dus",
"language:brd",
"language:jkm",
"language:kvq",
"language:kxf",
"language:kvy",
"language:eky",
"language:kyu",
"language:ghk",
"language:kvu",
"language:blk",
"language:kjp",
"language:pwo",
"language:kjt",
"language:pww",
"language:jkp",
"language:wea",
"language:bgg",
"language:mni",
"language:nkh",
"language:njm",
"language:nri",
"language:nbi",
"language:pmx",
"language:nnl",
"language:npo",
"language:nre",
"language:nsm",
"language:njo",
"language:njh",
"language:nsa",
"language:pzn",
"language:yim",
"language:lpn",
"language:jmn",
"language:ajz",
"language:bgr",
"language:cbl",
"language:cfm",
"language:biu",
"language:dln",
"language:hmr",
"language:sez",
"language:czt",
"language:mrh",
"language:shl",
"language:aim",
"language:anm",
"language:kmm",
"language:nmh",
"language:rnl",
"language:cek",
"language:cnk",
"language:cnw",
"language:zom",
"language:gnb",
"language:vap",
"language:kfw",
"language:pck",
"language:pub",
"language:ral",
"language:ctd",
"language:tcz",
"language:csh",
"language:csv",
"language:cnb",
"language:dao",
"language:ckn",
"language:mwq",
"language:nng",
"language:nma",
"language:nbu",
"language:nki",
"language:njn",
"language:nme",
"language:nzm",
"language:adl",
"language:nbt",
"language:tgj",
"language:bca",
"language:bfs",
"language:mro",
"language:duu",
"language:rji",
"language:rau",
"language:jnl",
"language:och",
"language:wxa",
"language:lzh",
"language:gan",
"language:hak",
"language:hsn",
"language:cjy",
"language:cmn",
"language:wuh",
"language:wuu",
"language:yue",
"language:cdo",
"language:cpx",
"language:mnp",
"language:czo",
"language:oma",
"language:iow",
"language:ofo",
"language:uni",
"language:suo",
"language:pux",
"language:rwa",
"language:wmx",
"language:vam",
"language:mmb",
"language:mqf",
"language:hmb",
"language:ses",
"language:tst",
"language:ddn",
"language:khq",
"language:dsq",
"language:uka",
"language:xod",
"language:bzp",
"language:jbj",
"language:dim",
"language:aiw",
"language:gyl",
"language:amf",
"language:kxh",
"language:uis",
"language:smz",
"language:nas",
"language:lni",
"language:kqj",
"language:lbi",
"language:rmi",
"language:ngm",
"language:rmd",
"language:rmu",
"language:rmg",
"language:sth",
"language:caw",
"language:cmt",
"language:sui",
"language:ggw",
"language:aac",
"language:wrv",
"language:xwg",
"language:mym",
"language:muz",
"language:mur",
"language:tex",
"language:did",
"language:loh",
"language:cuq",
"language:lic",
"language:yzg",
"language:enc",
"language:yln",
"language:yha",
"language:lha",
"language:aou",
"language:gir",
"language:gqu",
"language:lbt",
"language:lwh",
"language:onb",
"language:zgm",
"language:nut",
"language:tys",
"language:khb",
"language:tyt",
"language:tpo",
"language:nyw",
"language:tyj",
"language:thi",
"language:ksu",
"language:try",
"language:tdd",
"language:tiz",
"language:pdi",
"language:tmm",
"language:tts",
"language:yoy",
"language:zzj",
"language:zch",
"language:zeh",
"language:zgn",
"language:zgb",
"language:zln",
"language:zlj",
"language:zlq",
"language:zqe",
"language:tnu",
"language:tsl",
"language:zyj",
"language:zyn",
"language:zyb",
"language:mlm",
"language:kmc",
"language:cov",
"language:doc",
"language:tct",
"language:aih",
"language:mkg",
"language:cdy",
"language:mmd",
"language:lbc",
"language:mgb",
"language:sjg",
"language:tma",
"language:gcd",
"language:gyd",
"language:tsz",
"language:pua",
"language:tuh",
"language:mps",
"language:ppo",
"language:chd",
"language:clo",
"language:bfn",
"language:swt",
"language:kvd",
"language:woi",
"language:adn",
"language:hmu",
"language:klz",
"language:jka",
"language:twg",
"language:nec",
"language:ddg",
"language:oia",
"language:ury",
"language:bkl",
"language:itx",
"language:kwt",
"language:mqr",
"language:mrx",
"language:bnv",
"language:dbe",
"language:jbr",
"language:kdy",
"language:vto",
"language:tee",
"language:tpp",
"language:tpt",
"language:tlc",
"language:top",
"language:toc",
"language:tos",
"language:too",
"language:tcw",
"language:tku",
"language:bao",
"language:yui",
"language:arj",
"language:ynu",
"language:ten",
"language:mcl",
"language:ude",
"language:oaa",
"language:juc",
"language:nco",
"language:orh",
"language:kpn",
"language:ait",
"language:ktn",
"language:mav",
"language:awe",
"language:kay",
"language:xet",
"language:nhd",
"language:gug",
"language:gnw",
"language:tpj",
"language:jor",
"language:yuq",
"language:yrl",
"language:tpn",
"language:cod",
"language:omg",
"language:pog",
"language:tpk",
"language:asn",
"language:ama",
"language:aan",
"language:awt",
"language:taf",
"language:pak",
"language:mdz",
"language:asu",
"language:twt",
"language:gub",
"language:jua",
"language:paf",
"language:wir",
"language:pah",
"language:api",
"language:kgm",
"language:kyz",
"language:adw",
"language:urz",
"language:urb",
"language:oym",
"language:sru",
"language:cin",
"language:gvo",
"language:kyr",
"language:myu",
"language:pur",
"language:arr",
"language:uru",
"language:mpu",
"language:aqz",
"language:tpr",
"language:jur",
"language:xiy",
"language:msp",
"language:jbk",
"language:jmw",
"language:xbo",
"language:tyv",
"language:aib",
"language:ybe",
"language:uig",
"language:uzn",
"language:kir",
"language:kaa",
"language:xpc",
"language:krc",
"language:qxq",
"language:slq",
"language:azj",
"language:azb",
"language:giy",
"language:wma",
"language:vms",
"language:pax",
"language:rer",
"language:std",
"language:tme",
"language:tka",
"language:waf",
"language:wsu",
"language:woy",
"language:avo",
"language:aga",
"language:hir",
"language:dek",
"language:dbv",
"language:esm",
"language:kce",
"language:ruy",
"language:nsc",
"language:ksa",
"language:kku",
"language:kch",
"language:ays",
"language:dyg",
"language:agi",
"language:nbg",
"language:pch",
"language:bdz",
"language:znk",
"language:ygu",
"language:apv",
"language:xyl",
"language:wif",
"language:pig",
"language:wai",
"language:xmo",
"language:tkf",
"language:nrx",
"language:bfr",
"language:xcc",
"language:xly",
"language:ecr",
"language:ecy",
"language:gic",
"language:hvc",
"language:xil",
"language:xai",
"language:xpn",
"language:kzw",
"language:ktq",
"language:zkg",
"language:xle",
"language:omn",
"language:nrp",
"language:nxm",
"language:pkc",
"language:xpi",
"language:pij",
"language:pld",
"language:quq",
"language:xrr",
"language:txr",
"language:trl",
"language:uam",
"language:urp",
"language:wwb",
"language:liv",
"language:olo",
"language:lud",
"language:fkv",
"language:mvh",
"language:mhr",
"language:mrj",
"language:kpv",
"language:koi",
"language:yrk",
"language:enf",
"language:enh",
"language:sel",
"language:par",
"language:ute",
"language:mnr",
"language:pao",
"language:tbu",
"language:mfy",
"language:azz",
"language:nhq",
"language:nhy",
"language:nht",
"language:ppl",
"language:nch",
"language:nhe",
"language:nhw",
"language:nhk",
"language:nhp",
"language:nhx",
"language:nhc",
"language:nlv",
"language:ncx",
"language:nhz",
"language:nsu",
"language:nhi",
"language:nhn",
"language:nci",
"language:nhm",
"language:ncj",
"language:nhg",
"language:xpo",
"language:nhv",
"language:naz",
"language:nuz",
"language:ncl",
"language:azd",
"language:azn",
"language:crn",
"language:cok",
"language:tar",
"language:tac",
"language:thh",
"language:twr",
"language:tcu",
"language:ood",
"language:ntp",
"language:stp",
"language:tla",
"language:tep",
"language:hei",
"language:tww",
"language:ybx",
"language:wla",
"language:ppq",
"language:mxn",
"language:sbg",
"language:kzz",
"language:msg",
"language:zmm",
"language:zmt",
"language:zmg",
"language:zmj",
"language:zmd",
"language:zmy",
"language:xru",
"language:zmr",
"language:amy",
"language:zma",
"language:wil",
"language:wub",
"language:gma",
"language:gww",
"language:vmi",
"language:xgu",
"language:wro",
"language:xud",
"language:xun",
"language:jbw",
"language:dgn",
"language:wrr",
"language:jng",
"language:bjc",
"language:yrb",
"language:yva",
"language:xrn",
"language:xpm",
"language:cga",
"language:mvk",
"language:bwm",
"language:buv",
"language:ykg",
"language:xcv",
"language:wao",
"language:ayo",
"language:anb",
"language:cah",
"language:iqu",
"language:avs",
"language:zro",
"language:aab",
"language:aaq",
"language:aas",
"language:abd",
"language:abe",
"language:abk",
"language:abp",
"language:ace",
"language:acm",
"language:adb",
"language:add",
"language:adi",
"language:aee",
"language:afe",
"language:afk",
"language:agv",
"language:ain",
"language:ajn",
"language:ajs",
"language:als",
"language:alw",
"language:alx",
"language:anl",
"language:aol",
"language:apf",
"language:apo",
"language:arc",
"language:arx",
"language:asg",
"language:ash",
"language:ate",
"language:ato",
"language:ava",
"language:awv",
"language:aww",
"language:axx",
"language:ayd",
"language:ayt",
"language:ayz",
"language:bab",
"language:bal",
"language:bcg",
"language:bck",
"language:bcl",
"language:bcr",
"language:bcz",
"language:bdj",
"language:beg",
"language:bei",
"language:bfc",
"language:bfu",
"language:bgf",
"language:bgl",
"language:bgx",
"language:bhn",
"language:biz",
"language:bjg",
"language:bjv",
"language:bkd",
"language:bks",
"language:bkw",
"language:bmj",
"language:bmu",
"language:bnr",
"language:bog",
"language:bok",
"language:bor",
"language:bpa",
"language:bpp",
"language:bpy",
"language:bql",
"language:bqm",
"language:bqy",
"language:brx",
"language:brz",
"language:bsh",
"language:buq",
"language:bva",
"language:bvv",
"language:bwi",
"language:bxa",
"language:bxe",
"language:bxz",
"language:byk",
"language:bym",
"language:bzv",
"language:bzx",
"language:cas",
"language:cbi",
"language:cbq",
"language:cbv",
"language:ccd",
"language:cdr",
"language:cet",
"language:chh",
"language:chm",
"language:chn",
"language:ckm",
"language:ckt",
"language:cky",
"language:clc",
"language:clk",
"language:clt",
"language:cmg",
"language:cmm",
"language:cmr",
"language:cnp",
"language:cnu",
"language:cnx",
"language:cof",
"language:cry",
"language:csk",
"language:csp",
"language:csq",
"language:css",
"language:cst",
"language:csy",
"language:csz",
"language:cth",
"language:ctn",
"language:cts",
"language:cty",
"language:cvg",
"language:czh",
"language:czk",
"language:dbu",
"language:dcc",
"language:ddi",
"language:ddo",
"language:del",
"language:den",
"language:dga",
"language:dgc",
"language:dgl",
"language:dgo",
"language:dho",
"language:dhw",
"language:dih",
"language:diq",
"language:diu",
"language:dja",
"language:djd",
"language:djk",
"language:dmf",
"language:dmm",
"language:dmo",
"language:dny",
"language:doi",
"language:dri",
"language:dsi",
"language:dta",
"language:dth",
"language:dtk",
"language:dtn",
"language:duk",
"language:dum",
"language:duz",
"language:dyy",
"language:eaa",
"language:ebo",
"language:egl",
"language:ekk",
"language:ell",
"language:eme",
"language:emq",
"language:enm",
"language:esk",
"language:esu",
"language:etc",
"language:eto",
"language:fab",
"language:faj",
"language:fap",
"language:fat",
"language:fay",
"language:fbl",
"language:fit",
"language:flh",
"language:fly",
"language:fnb",
"language:fpe",
"language:frm",
"language:frs",
"language:frt",
"language:ful",
"language:fuv",
"language:gae",
"language:gal",
"language:gba",
"language:gbd",
"language:gbg",
"language:gbu",
"language:gbw",
"language:gdh",
"language:gdo",
"language:gdt",
"language:gek",
"language:gel",
"language:gev",
"language:gge",
"language:ggu",
"language:gha",
"language:ghl",
"language:ght",
"language:gia",
"language:gie",
"language:gih",
"language:gin",
"language:giq",
"language:giu",
"language:giw",
"language:gjm",
"language:gkd",
"language:gku",
"language:glb",
"language:glh",
"language:gll",
"language:gmg",
"language:gmh",
"language:gmz",
"language:gnk",
"language:goz",
"language:gqn",
"language:grc",
"language:grr",
"language:gsn",
"language:gsw",
"language:gtu",
"language:gup",
"language:gva",
"language:gvc",
"language:gvp",
"language:gwd",
"language:gwj",
"language:hba",
"language:hbs",
"language:hed",
"language:hem",
"language:hgm",
"language:hhr",
"language:hhy",
"language:hio",
"language:hks",
"language:hlt",
"language:hmd",
"language:hmk",
"language:hmz",
"language:hnh",
"language:hov",
"language:hps",
"language:hrt",
"language:htx",
"language:hue",
"language:hum",
"language:huv",
"language:hve",
"language:hvn",
"language:hvv",
"language:icr",
"language:idb",
"language:ify",
"language:ihb",
"language:ihw",
"language:iku",
"language:ilm",
"language:ilp",
"language:inb",
"language:inj",
"language:inl",
"language:ipk",
"language:ire",
"language:izz",
"language:jaa",
"language:jat",
"language:jbi",
"language:jbt",
"language:jek",
"language:jgk",
"language:jid",
"language:jih",
"language:jiq",
"language:jkr",
"language:jks",
"language:jog",
"language:jos",
"language:jrb",
"language:jup",
"language:kac",
"language:kbp",
"language:kcd",
"language:kcx",
"language:kfi",
"language:kfr",
"language:kgn",
"language:khd",
"language:khv",
"language:khy",
"language:kim",
"language:kit",
"language:kiu",
"language:kjj",
"language:kjo",
"language:kjv",
"language:kkq",
"language:kld",
"language:klg",
"language:klm",
"language:kmd",
"language:kmq",
"language:kmv",
"language:kmz",
"language:knd",
"language:kng",
"language:knj",
"language:knm",
"language:knn",
"language:knw",
"language:kod",
"language:koe",
"language:kok",
"language:kow",
"language:kqd",
"language:kqo",
"language:krj",
"language:krs",
"language:ksc",
"language:ksi",
"language:ktz",
"language:kue",
"language:kvz",
"language:kwb",
"language:kwk",
"language:kwl",
"language:kxk",
"language:kxo",
"language:kxr",
"language:kyl",
"language:kyo",
"language:laa",
"language:lab",
"language:lay",
"language:lbl",
"language:lbn",
"language:ldb",
"language:lev",
"language:lez",
"language:lgk",
"language:lgn",
"language:lhs",
"language:lie",
"language:lik",
"language:lin",
"language:lir",
"language:ljw",
"language:lku",
"language:lme",
"language:lmf",
"language:lng",
"language:lnj",
"language:lnm",
"language:lnn",
"language:lnw",
"language:lou",
"language:loy",
"language:lro",
"language:lsb",
"language:lsh",
"language:ltc",
"language:lth",
"language:ltz",
"language:lui",
"language:lus",
"language:lut",
"language:lvi",
"language:lvu",
"language:lxm",
"language:lyg",
"language:man",
"language:mbm",
"language:mch",
"language:mcm",
"language:mcu",
"language:mcv",
"language:mdh",
"language:mep",
"language:mev",
"language:mfg",
"language:mga",
"language:mgs",
"language:mgt",
"language:mhn",
"language:mhu",
"language:mis",
"language:mjb",
"language:mjg",
"language:mjy",
"language:mkr",
"language:mkx",
"language:mkz",
"language:mlg",
"language:mlv",
"language:mlx",
"language:mlz",
"language:mmf",
"language:mmi",
"language:mmq",
"language:mnx",
"language:moe",
"language:mpb",
"language:mpw",
"language:mpx",
"language:mqz",
"language:mrb",
"language:msa",
"language:mte",
"language:mtm",
"language:mul",
"language:mwf",
"language:mwi",
"language:mwr",
"language:mxj",
"language:mzk",
"language:mzu",
"language:nam",
"language:nat",
"language:nay",
"language:nbd",
"language:nbj",
"language:nbl",
"language:nck",
"language:nct",
"language:nde",
"language:ndf",
"language:neh",
"language:nei",
"language:nep",
"language:new",
"language:nfl",
"language:nfr",
"language:nfu",
"language:nga",
"language:ngk",
"language:ngq",
"language:ngr",
"language:ngt",
"language:ngu",
"language:nib",
"language:niv",
"language:njs",
"language:njz",
"language:nkb",
"language:nlo",
"language:nlx",
"language:nmf",
"language:nmm",
"language:nmn",
"language:nmo",
"language:nny",
"language:npi",
"language:npx",
"language:nqg",
"language:nqq",
"language:nrf",
"language:nrt",
"language:nsb",
"language:nsf",
"language:nst",
"language:ntg",
"language:ntk",
"language:ntx",
"language:nua",
"language:nun",
"language:nwc",
"language:nwg",
"language:nwx",
"language:nwy",
"language:nxk",
"language:nyh",
"language:nys",
"language:nzz",
"language:oav",
"language:oci",
"language:ocm",
"language:oht",
"language:ohu",
"language:ojv",
"language:okc",
"language:okh",
"language:okm",
"language:oko",
"language:omk",
"language:omp",
"language:onx",
"language:oog",
"language:opt",
"language:ori",
"language:ort",
"language:osn",
"language:ota",
"language:otb",
"language:oua",
"language:oue",
"language:oui",
"language:pad",
"language:pan",
"language:pav",
"language:pbh",
"language:pbm",
"language:pby",
"language:pcj",
"language:pdu",
"language:pef",
"language:pep",
"language:pes",
"language:pfe",
"language:pfl",
"language:pga",
"language:pgd",
"language:pgl",
"language:phl",
"language:phr",
"language:pir",
"language:piv",
"language:pka",
"language:pkh",
"language:plj",
"language:pls",
"language:pmh",
"language:pmk",
"language:pml",
"language:pmr",
"language:png",
"language:pnw",
"language:pop",
"language:prg",
"language:prk",
"language:prn",
"language:pro",
"language:prt",
"language:psc",
"language:psh",
"language:psi",
"language:psm",
"language:psu",
"language:pti",
"language:puo",
"language:pus",
"language:pyx",
"language:que",
"language:qug",
"language:qur",
"language:qwm",
"language:qwt",
"language:qyp",
"language:ram",
"language:rar",
"language:ray",
"language:rbk",
"language:rbl",
"language:rem",
"language:ret",
"language:rga",
"language:rif",
"language:ril",
"language:rit",
"language:rmc",
"language:rmo",
"language:rom",
"language:rrt",
"language:rsb",
"language:rts",
"language:rup",
"language:rxw",
"language:rzh",
"language:sbf",
"language:sbq",
"language:sci",
"language:scp",
"language:scw",
"language:scx",
"language:sdb",
"language:sde",
"language:sef",
"language:seo",
"language:seq",
"language:sfm",
"language:sga",
"language:sgb",
"language:sgi",
"language:sgp",
"language:shm",
"language:shv",
"language:shy",
"language:sia",
"language:sjb",
"language:sjd",
"language:sje",
"language:sjk",
"language:sjl",
"language:sjt",
"language:sju",
"language:skf",
"language:skg",
"language:skm",
"language:sld",
"language:slz",
"language:sma",
"language:sme",
"language:smj",
"language:smn",
"language:sms",
"language:smu",
"language:sne",
"language:sns",
"language:soe",
"language:soo",
"language:sox",
"language:spg",
"language:spq",
"language:sqr",
"language:sqx",
"language:sre",
"language:srv",
"language:ssq",
"language:ssv",
"language:sta",
"language:stq",
"language:suq",
"language:svx",
"language:swa",
"language:swh",
"language:swn",
"language:sxc",
"language:sxg",
"language:sxk",
"language:sxl",
"language:sxm",
"language:sxo",
"language:tab",
"language:tbh",
"language:tcc",
"language:tcp",
"language:tdx",
"language:teg",
"language:ter",
"language:tew",
"language:tfn",
"language:thd",
"language:thm",
"language:tia",
"language:tiq",
"language:tjj",
"language:tjo",
"language:tjp",
"language:tlo",
"language:tlp",
"language:tlt",
"language:tmb",
"language:tmh",
"language:tmv",
"language:tnr",
"language:tnz",
"language:tpw",
"language:tqb",
"language:tqt",
"language:tro",
"language:trv",
"language:tsw",
"language:ttw",
"language:twe",
"language:twf",
"language:tye",
"language:tzm",
"language:ubl",
"language:uji",
"language:ukk",
"language:ulk",
"language:umg",
"language:und",
"language:unn",
"language:url",
"language:uss",
"language:uth",
"language:vaj",
"language:van",
"language:vbk",
"language:vkp",
"language:vls",
"language:vma",
"language:vmb",
"language:vmf",
"language:vnk",
"language:vnm",
"language:vwa",
"language:waa",
"language:waq",
"language:wbf",
"language:wbk",
"language:wbs",
"language:wbt",
"language:wca",
"language:wdy",
"language:wei",
"language:wep",
"language:weu",
"language:wew",
"language:wgg",
"language:wha",
"language:whk",
"language:wig",
"language:wkr",
"language:wky",
"language:wlr",
"language:wmg",
"language:wnb",
"language:woa",
"language:wob",
"language:wrb",
"language:wrg",
"language:wrw",
"language:wrx",
"language:wrz",
"language:wsi",
"language:wsr",
"language:wwo",
"language:wyb",
"language:xaj",
"language:xam",
"language:xaq",
"language:xas",
"language:xbb",
"language:xbd",
"language:xby",
"language:xcb",
"language:xco",
"language:xcu",
"language:xda",
"language:xdk",
"language:xeb",
"language:xeg",
"language:xep",
"language:xgf",
"language:xgi",
"language:xgl",
"language:xha",
"language:xhc",
"language:xhm",
"language:xiv",
"language:xjb",
"language:xkb",
"language:xki",
"language:xkk",
"language:xlb",
"language:xlg",
"language:xli",
"language:xln",
"language:xme",
"language:xmh",
"language:xmk",
"language:xmn",
"language:xnb",
"language:xng",
"language:xnj",
"language:xnk",
"language:xnq",
"language:xnt",
"language:xnu",
"language:xny",
"language:xom",
"language:xpb",
"language:xpd",
"language:xpf",
"language:xph",
"language:xpl",
"language:xpp",
"language:xpv",
"language:xpw",
"language:xpx",
"language:xpy",
"language:xpz",
"language:xre",
"language:xrg",
"language:xri",
"language:xrm",
"language:xrt",
"language:xsa",
"language:xsb",
"language:xsc",
"language:xsv",
"language:xtr",
"language:xtt",
"language:xvn",
"language:xwo",
"language:xxb",
"language:xxk",
"language:xzm",
"language:xzp",
"language:yaf",
"language:yak",
"language:yau",
"language:ybh",
"language:ybn",
"language:yel",
"language:ygi",
"language:ygs",
"language:yhs",
"language:yii",
"language:yin",
"language:ykt",
"language:yly",
"language:yok",
"language:yon",
"language:yrm",
"language:yrn",
"language:yro",
"language:ysc",
"language:ysm",
"language:ysr",
"language:yta",
"language:ytl",
"language:yty",
"language:yua",
"language:yug",
"language:yuz",
"language:yxa",
"language:yyr",
"language:zam",
"language:zba",
"language:zbu",
"language:zha",
"language:zkb",
"language:zkh",
"language:zkn",
"language:zko",
"language:zkv",
"language:zkz",
"language:zml",
"language:zne",
"language:zra",
"language:zrn",
"language:zsk",
"language:ztq",
"language:zxx",
"language:zyp",
"license:cc-by-4.0",
"region:us"
] | 2024-01-02T19:36:27+00:00 | {"language": ["aal", "aap", "aar", "abj", "abo", "abq", "abw", "aby", "abz", "aci", "ack", "acl", "acn", "acr", "acv", "ade", "adr", "adt", "ady", "aek", "aeq", "aew", "aey", "afd", "afi", "afn", "afo", "afz", "agc", "age", "agg", "agh", "agl", "ago", "agq", "agr", "agw", "agx", "ahg", "aho", "aik", "ail", "aio", "akj", "akk", "akl", "akm", "akp", "akv", "akx", "aky", "akz", "ala", "ale", "alf", "alq", "alt", "alz", "ame", "ami", "amj", "amu", "amv", "ana", "anh", "ani", "ann", "ano", "anv", "any", "aoc", "aog", "aoi", "aoj", "aos", "aox", "aoz", "apn", "apq", "apt", "apw", "apz", "aqc", "aqm", "aqp", "aqt", "arg", "arh", "ari", "ark", "arl", "arp", "arw", "asb", "asc", "asm", "ass", "ast", "asx", "atb", "atj", "atq", "atu", "atv", "atx", "auc", "aug", "auh", "auk", "aup", "auq", "aux", "auy", "avn", "avv", "awa", "axg", "ayg", "aym", "aze", "bak", "bam", "ban", "bap", "bav", "bbg", "bbk", "bbl", "bbn", "bbq", "bbr", "bbw", "bcm", "bco", "bcq", "bdk", "bdn", "bdq", "bdt", "bdu", "bdv", "bdw", "bdx", "bec", "bej", "bel", "ben", "beu", "bew", "bfa", "bfb", "bfe", "bff", "bfh", "bfm", "bfq", "bft", "bfx", "bfy", "bga", "bgc", "bgd", "bgq", "bgw", "bhb", "bho", "bhp", "bhs", "bhw", "bhy", "bib", "bil", "bio", "bip", "bit", "biv", "bja", "bji", "bjr", "bjz", "bkf", "bkj", "bku", "bkv", "bky", "bld", "blf", "bll", "bln", "blq", "blr", "blt", "bly", "blz", "bma", "bmh", "bmi", "bmq", "bmr", "bnb", "bnf", "bng", "bni", "bnn", "bny", "boa", "boh", "boj", "bol", "bom", "bos", "box", "bpe", "bph", "bpk", "bpn", "bpt", "bpx", "bpz", "bqh", "bqj", "bqq", "bqt", "bqv", "bqx", "bre", "brf", "brh", "bro", "bsa", "bsc", "bse", "bsg", "bsj", "bsl", "bsn", "bsq", "bsx", "bta", "bte", "btn", "bto", "bts", "btt", "btu", "btv", "btx", "buc", "bud", "bue", "bug", "bul", "buo", "buu", "bvd", "bvi", "bvj", "bvo", "bwe", "bwt", "bww", "bwy", "bxp", "byh", "bys", "byv", "byx", "bzb", "bzd", "bzh", "cac", "cad", "cag", "cak", "cal", "cap", "cat", "cax", "cay", "cbc", "cbd", "cbg", "cbt", "cbu", "cby", "ccc", "cce", "cch", "ccp", "cda", "cde", "cdf", "cdi", "cdm", "cea", "ceb", "ceg", "ces", "cfd", "cha", "chb", "chc", "che", "chg", "chk", "chl", "cho", "chp", "chr", "cht", "chv", "chw", "chy", "cia", "cic", "cih", "cik", "cim", "cjh", "cji", "cjk", "cjs", "ckl", "cku", "ckv", "clw", "cme", "cna", "cng", "cnh", "cni", "cnq", "cnr", "cob", "coe", "cog", "com", "con", "coo", "cop", "cor", "cos", "cot", "cou", "cox", "cps", "crc", "crd", "cre", "crh", "crk", "crm", "cro", "crr", "crv", "crx", "crz", "csb", "csw", "ctg", "ctm", "cub", "cuj", "cuo", "cup", "cuu", "cwe", "cym", "daa", "dag", "dah", "dak", "dan", "dar", "dba", "dbd", "dby", "ddd", "dec", "deh", "dem", "der", "des", "deu", "dev", "dgr", "dgs", "dhd", "dhi", "dhm", "dia", "dig", "dil", "din", "dio", "dis", "diz", "dje", "djn", "djo", "dlg", "dlk", "dlm", "dmc", "dml", "dmr", "dmy", "dng", "dnj", "dnk", "dnu", "dnw", "doa", "dof", "dox", "drc", "drd", "drl", "drn", "dru", "dsb", "dtd", "dui", "dyo", "dyu", "dza", "ebk", "ebr", "ebu", "eee", "efi", "ego", "eiv", "ekg", "eko", "ekr", "ele", "eli", "emm", "emx", "ena", "enl", "enn", "enx", "era", "eri", "ero", "ert", "ese", "esq", "ess", "est", "esy", "etx", "eus", "eve", "evh", "evn", "ewe", "ext", "eyo", "faa", "fad", "fao", "fas", "ffi", "fgr", "fia", "fif", "fij", "fil", "fin", "fip", "fir", "fkk", "fni", "fon", "fqs", "fra", "frd", "frk", "fuc", "fur", "fuu", "fvr", "fwe", "gaa", "gag", "gah", "gak", "gao", "gaw", "gay", "gbk", "gbm", "gbz", "gcc", "gce", "gdj", "gdl", "gdm", "gdn", "gdr", "gea", "geb", "gei", "gej", "gew", "gex", "gey", "gfk", "ggk", "ghn", "gid", "gil", "git", "gju", "gko", "gld", "gle", "glg", "glk", "glv", "glw", "gmb", "gna", "gng", "gnt", "goe", "gog", "goi", "gon", "gor", "gov", "gqi", "grb", "grh", "grn", "grt", "gua", "guc", "guh", "gui", "guj", "gun", "guo", "guq", "gur", "guu", "guw", "guz", "gve", "gvj", "gvl", "gwc", "gwe", "gwi", "gwr", "gyo", "gyr", "gza", "hai", "haj", "han", "haq", "har", "has", "hau", "hav", "haw", "hay", "hbb", "hbn", "hch", "heb", "heh", "her", "hhi", "hid", "hih", "hii", "hil", "hit", "hke", "hlb", "hle", "hmn", "hmt", "hne", "hni", "hnn", "hoc", "hoe", "hoi", "hol", "hoo", "hop", "hot", "hra", "hru", "hrv", "hsb", "hto", "hts", "huh", "hun", "hup", "hus", "huw", "hux", "huz", "hye", "iai", "ian", "iba", "ibb", "ibl", "ibm", "ibo", "idc", "idu", "igm", "ihp", "ijc", "ijn", "ikx", "ikz", "ilb", "ili", "imi", "iml", "imy", "ind", "inh", "ior", "irh", "iri", "irk", "iru", "irx", "ish", "isi", "isk", "isl", "isn", "ist", "ita", "itl", "ito", "itr", "ium", "ivv", "iwo", "iws", "ixc", "iyo", "izh", "izr", "jab", "jae", "jal", "jav", "jbn", "jbu", "jct", "jdg", "jeb", "jel", "jet", "jgb", "jgo", "jic", "jig", "jio", "jit", "jiv", "jku", "jle", "jma", "jmb", "jml", "jni", "jow", "jpn", "jqr", "jra", "juk", "jun", "juo", "jwi", "kab", "kad", "kaj", "kap", "kas", "kat", "kau", "kaz", "kbd", "kbj", "kbr", "kbu", "kbz", "kca", "kcg", "kck", "kcn", "kcq", "kcr", "kct", "kcw", "kcy", "kde", "kdh", "kdk", "kdn", "kdr", "kdt", "kdx", "ked", "keg", "keh", "ken", "ket", "kev", "kff", "kfk", "kfm", "kfp", "kfq", "kft", "kfy", "kge", "kgg", "kgk", "kgp", "kgt", "kgu", "kgv", "kha", "khe", "khl", "khm", "khr", "kht", "kib", "kik", "kil", "kio", "kiv", "kiy", "kjg", "kjh", "kjk", "kjm", "kjn", "kju", "kjx", "kkd", "kkh", "kkk", "kkm", "kks", "kkt", "kkv", "kkz", "klb", "klf", "klj", "klq", "klr", "kls", "klu", "kly", "kma", "kni", "knp", "knv", "knx", "knz", "kom", "kon", "kop", "kor", "kot", "koy", "kpa", "kpe", "kpf", "kpg", "kpj", "kpm", "kps", "kpu", "kpy", "kpz", "kqa", "kqg", "kql", "kqn", "kqp", "kqu", "kqv", "kre", "krh", "krl", "kru", "kry", "ksb", "ksk", "ksm", "ksp", "ksr", "ksw", "kte", "ktm", "kuc", "kuj", "kum", "kun", "kus", "kut", "kuu", "kuz", "kva", "kve", "kvf", "kvl", "kvr", "kvw", "kwe", "kwf", "kwh", "kwn", "kws", "kwz", "kxi", "kxv", "kyt", "kyx", "kzl", "kzm", "kzr", "lac", "lai", "lam", "lan", "lao", "laq", "lav", "laz", "lbe", "lbf", "lbj", "lbk", "lbq", "lbz", "lce", "lcl", "lcq", "ldd", "ldj", "ldl", "ldo", "ldp", "leb", "lec", "led", "lee", "lef", "leh", "lej", "les", "let", "lex", "ley", "lgq", "lgt", "lhu", "lif", "lih", "lij", "lil", "lis", "lit", "liw", "lji", "lkh", "lki", "lkj", "lko", "lkr", "lkt", "lky", "lld", "llg", "lll", "llp", "llu", "lmc", "lmd", "lmk", "lmo", "lmp", "lnh", "lnu", "loa", "lob", "loe", "lof", "lok", "lol", "lon", "lop", "lot", "loz", "lpo", "lpx", "lri", "lsi", "lsr", "ltg", "lub", "lun", "lup", "lwa", "lyn", "lzl", "lzz", "mad", "mag", "mah", "mai", "mam", "mar", "maw", "mbl", "mbn", "mbu", "mby", "mcc", "mcf", "mcj", "mck", "mdf", "mdj", "mdq", "mdt", "meb", "mef", "mej", "mer", "mew", "mez", "mff", "mfi", "mfo", "mfr", "mgd", "mgf", "mgg", "mgj", "mgq", "mgr", "mgu", "mgv", "mgw", "mhd", "mhi", "mhl", "mhq", "mhw", "mic", "mid", "min", "miw", "mje", "mjs", "mjw", "mka", "mkb", "mkc", "mkd", "mki", "mkj", "mkk", "mko", "mkp", "mkq", "mlc", "mlf", "mlk", "mlp", "mlr", "mls", "mlt", "mlw", "mmo", "mmp", "mmt", "mmv", "mmw", "mnb", "mnc", "mnd", "mnj", "mns", "mnw", "moh", "moi", "mok", "mom", "mor", "mot", "mox", "mpa", "mpe", "mpg", "mph", "mpz", "mqp", "mqs", "mrc", "mrf", "mrg", "mrv", "mry", "msf", "msk", "msq", "msy", "mtd", "mtj", "mtl", "mtq", "mtr", "mty", "mua", "mug", "muo", "mup", "muv", "mvp", "mvs", "mvu", "mwb", "mwl", "mwm", "mwv", "mxe", "mxf", "mxm", "mxo", "mya", "myb", "mye", "myf", "myg", "myh", "myp", "myv", "myy", "mzm", "mzn", "mzp", "mzt", "mzw", "nak", "nap", "naq", "nav", "nbb", "nbo", "nbp", "nca", "ncg", "ncz", "ndd", "ndg", "ndh", "ndp", "ndy", "neg", "neo", "ner", "nev", "nez", "nfa", "nfd", "ngh", "ngl", "ngn", "ngp", "ngv", "ngy", "nhb", "nia", "nie", "nig", "nii", "nik", "nin", "nio", "nir", "niu", "nix", "niy", "nka", "nkd", "nkr", "nks", "nlc", "nld", "nlj", "nmb", "nmc", "nmg", "nmk", "nmq", "nmr", "nmy", "nmz", "nnb", "nnh", "nnq", "nnu", "nod", "noe", "nog", "noj", "nok", "nol", "nor", "not", "now", "noy", "nrb", "nrm", "nrn", "nse", "nsk", "nsx", "nsz", "nti", "ntr", "nty", "nuk", "nus", "nuy", "nvo", "nwr", "nxq", "nxr", "nyj", "nyk", "nyo", "nyp", "nyu", "nzb", "nzd", "nzy", "oac", "obi", "oca", "ogb", "ogo", "ogu", "oka", "okd", "okj", "oku", "olr", "omc", "omo", "omt", "ona", "one", "ono", "onp", "opm", "ore", "orm", "ory", "osa", "oso", "oss", "oti", "otr", "pae", "pag", "pai", "paq", "pau", "paz", "pbb", "pbg", "pbi", "pbp", "pbr", "pbv", "pcb", "pcc", "pcd", "pcg", "pci", "pcl", "pcn", "pdn", "peb", "peh", "phd", "phg", "phh", "phk", "pho", "pht", "phu", "phv", "pia", "pib", "pic", "pid", "pio", "pip", "piw", "pkb", "pkt", "ple", "plu", "pmt", "pnh", "pnl", "pol", "pon", "por", "pot", "pox", "poy", "ppi", "ppk", "ppt", "pru", "prw", "psn", "pta", "pto", "ptt", "ptu", "ptv", "ptw", "pue", "pui", "pum", "puu", "pwi", "pwn", "qua", "qui", "qun", "rag", "rah", "ran", "rao", "raw", "rbp", "rei", "rej", "ren", "res", "rey", "rgu", "rhg", "rhp", "rin", "rkb", "rki", "rkt", "rma", "rmb", "rme", "rmt", "rmw", "rmy", "rnd", "rnw", "rof", "roh", "rol", "ron", "row", "rsk", "rtm", "rub", "ruc", "rue", "ruf", "rus", "rut", "ruz", "rwo", "rys", "sad", "sag", "sah", "sak", "sam", "saq", "sat", "sau", "say", "saz", "sbk", "sbo", "sbt", "sby", "sch", "scn", "sco", "scq", "sdj", "sdp", "sea", "see", "sei", "sek", "ser", "sey", "sfw", "sgh", "sgk", "sgm", "sgs", "sgy", "shb", "shc", "shd", "shh", "shj", "shk", "shn", "shr", "shs", "shw", "shx", "sif", "sig", "sih", "sik", "sin", "sip", "sis", "siu", "siw", "six", "siy", "siz", "sjo", "sjp", "sjr", "sjw", "skb", "skr", "sks", "skv", "slk", "sll", "slr", "slx", "sly", "smk", "smo", "smr", "smt", "smw", "smy", "sna", "snd", "snf", "snk", "snn", "snx", "snz", "soa", "sog", "soh", "som", "soq", "sor", "sou", "spa", "spc", "spm", "spn", "sps", "spu", "spv", "spy", "sqh", "sqi", "sqt", "squ", "srb", "srd", "srh", "sri", "srm", "srp", "srq", "srr", "srx", "ssf", "ssi", "ssk", "ssm", "stn", "sto", "sty", "sub", "suk", "sun", "sus", "suv", "suw", "sux", "suy", "suz", "sva", "swe", "swi", "swr", "swv", "sxe", "sxr", "syk", "syl", "syo", "syr", "sys", "syw", "syx", "szb", "szl", "szn", "szp", "szw", "taa", "tag", "tah", "tam", "tao", "tap", "taq", "tat", "tau", "tav", "taz", "tba", "tbe", "tbi", "tbk", "tbp", "tbt", "tca", "tcb", "tcg", "tcy", "tda", "tdh", "tdv", "tec", "tef", "teh", "tei", "tel", "teo", "teq", "tet", "teu", "tez", "tfr", "tft", "tgk", "tgl", "tgp", "tgx", "tha", "thf", "thp", "ths", "tht", "thy", "tig", "tii", "tij", "til", "tin", "tir", "tit", "tiv", "tjl", "tjw", "tkm", "tkr", "tkv", "tlh", "tli", "tll", "tlq", "tlx", "tly", "tmd", "tmf", "tmj", "tms", "tmu", "tmw", "tnc", "tng", "tnk", "tnl", "tnm", "tnx", "tny", "tol", "tom", "toq", "tow", "tox", "tpg", "tpy", "tpz", "tql", "tqo", "trr", "tru", "trw", "tsa", "tsb", "tsc", "tsd", "tsg", "tsn", "tso", "tsu", "tsv", "tsx", "tta", "ttb", "tti", "ttj", "ttl", "ttv", "tua", "tub", "tuc", "tue", "tuk", "tum", "tun", "tuo", "tur", "tus", "tuu", "tuv", "tuy", "tuz", "tvk", "tvx", "twa", "twh", "twn", "twq", "twu", "txc", "txg", "txi", "txq", "txx", "tya", "tyr", "tyz", "tzh", "tzo", "tzx", "uan", "uar", "uby", "udi", "udm", "ugh", "ukr", "ukw", "ulb", "ulc", "ule", "ulf", "uli", "ull", "ump", "umu", "une", "ung", "unr", "ura", "ure", "urk", "urw", "usu", "uum", "uuu", "uve", "uvh", "uzb", "uzs", "vai", "var", "vas", "vau", "vav", "vec", "ven", "veo", "vep", "vie", "vif", "vkk", "vmg", "vmw", "vot", "vro", "vum", "wan", "was", "wat", "wbe", "wbh", "wbi", "wbl", "wbm", "wdj", "wgy", "wic", "wii", "win", "wiv", "wja", "wkd", "wln", "wls", "wme", "wmi", "wmw", "wnc", "wnm", "wnp", "wnu", "wnw", "wol", "won", "wrh", "wsa", "wtf", "wti", "wtk", "wtm", "wul", "wur", "wut", "wwa", "wym", "wyn", "wyr", "xad", "xan", "xaw", "xbc", "xbw", "xch", "xdq", "xed", "xem", "xgw", "xho", "xka", "xkl", "xko", "xkv", "xla", "xlc", "xmd", "xmf", "xmg", "xno", "xnr", "xnz", "xog", "xon", "xpq", "xpr", "xqa", "xso", "xsr", "xsu", "xsy", "xte", "xub", "xug", "xuo", "xwa", "xwc", "xwr", "xww", "xyy", "xzh", "yad", "yao", "yap", "yaq", "yba", "ybb", "ybj", "ybl", "ycl", "ycn", "ydg", "yej", "yer", true, "yev", "yey", "yiu", "yko", "yla", "yle", "ylg", "yme", "ymi", "ymk", "ymn", "ymz", "ynk", "yno", "yns", "yoi", "yox", "ypg", "yph", "ysn", "yss", "yuc", "yuk", "yul", "yum", "yup", "yur", "yux", "ywa", "yxu", "zag", "zen", "zga", "zhb", "zhd", "zhi", "zhn", "zho", "zil", "zim", "zin", "ziw", "ziz", "zkk", "zkr", "zku", "zmb", "zmf", "zmn", "zmp", "zmv", "zrp", "zul", "zun", "zwa", "zyg", "kgr", "anz", "blb", "boq", "bzu", "bsk", "kbh", "caz", "xcy", "cyb", "cid", "xcw", "xcn", "cuy", "uhn", "duc", "elx", "ett", "fun", "fuy", "gta", "gly", "guk", "grx", "xht", "xib", "tbd", "khp", "xar", "kyh", "khh", "xbn", "prm", "kla", "kol", "vkj", "kto", "laf", "lrg", "lvk", "xak", "mgk", "xmr", "xxm", "mbe", "msl", "moq", "akc", "myr", "nll", "bhf", "omu", "ppe", "pwa", "ata", "yae", "puq", "iar", "sln", "sao", "svs", "sii", "sua", "gpn", "xxt", "tcm", "tdm", "ttd", "tjm", "tiw", "tqw", "tqu", "tsi", "tud", "umr", "vil", "wba", "wiu", "xoo", "nce", "yag", "ynn", "yra", "yet", "hti", "auj", "mzb", "sds", "shi", "zgh", "gho", "sjs", "thv", "ttq", "thz", "gnc", "mqb", "mpk", "hya", "kvj", "bcw", "hig", "bdm", "jia", "xmj", "kqx", "msv", "mpi", "hia", "vem", "mrt", "mfm", "bwr", "ngx", "mfl", "dgh", "ngs", "cie", "gdf", "mfh", "dme", "meq", "gnd", "mif", "mfk", "mxu", "muy", "udl", "gis", "giz", "bcy", "gdu", "ngw", "jim", "fli", "gde", "hod", "nja", "swq", "tsh", "hna", "gou", "dkx", "dbq", "bvw", "gqa", "hwo", "jaf", "ttr", "cuv", "maf", "mfj", "jie", "moz", "muj", "btf", "mou", "trj", "bid", "mmy", "jeu", "ckq", "mes", "mub", "mcw", "ubi", "bvf", "mlj", "saa", "sok", "tax", "ker", "kvi", "lln", "nnc", "gab", "ndm", "tmc", "gdk", "swy", "mse", "mcn", "zuy", "nnn", "fie", "tdk", "kul", "cla", "gwn", "kai", "glo", "nbh", "bxq", "dbb", "kof", "bvh", "ktc", "nmi", "kna", "kuh", "piy", "tan", "ksq", "sur", "anc", "ank", "tal", "kcs", "pcw", "jrt", "nqt", "dbp", "ngi", "bde", "auo", "twc", "ajw", "tgd", "dwa", "bbt", "pqa", "sir", "mkf", "wji", "bux", "kkr", "zns", "grd", "jmi", "juu", "tak", "zah", "gyz", "dot", "zua", "zaz", "awn", "byn", "dal", "hdy", "liq", "ktb", "drs", "sid", "ssy", "kxc", "gaz", "gax", "orc", "hae", "ssn", "gii", "ymm", "rel", "bsw", "jii", "dbr", "tqq", "bob", "arv", "dsh", "elo", "muu", "bnl", "wka", "bds", "wbj", "gow", "egy", "xna", "ara", "arb", "ayh", "acw", "jye", "ayn", "ssh", "acq", "abv", "adf", "afb", "ars", "acx", "abh", "auz", "yhd", "ayp", "avl", "arz", "aec", "shu", "apd", "acy", "apc", "ajp", "arq", "aao", "mey", "yud", "aju", "ayl", "aeb", "xaa", "ary", "syc", "aii", "cld", "tmr", "syn", "bjf", "lsd", "huy", "trg", "aij", "myz", "amw", "jpa", "oar", "hbo", "smp", "xdm", "obm", "uga", "phn", "xpu", "xhd", "inm", "xqt", "gez", "amh", "agj", "stv", "wle", "gft", "gru", "mvz", "sgw", "mys", "hoh", "bhm", "hss", "gdq", "wiy", "bla", "nwa", "ats", "crl", "crj", "cwd", "crg", "pqm", "pim", "unm", "nnt", "psy", "xlo", "wam", "mia", "kic", "sac", "oji", "otw", "ojc", "ciw", "ojg", "ojb", "ojw", "ojs", "aes", "amt", "agm", "ygw", "byr", "smb", "mcr", "kcb", "klp", "ssu", "aak", "ipo", "kvg", "zik", "bpv", "mrz", "bgv", "jaq", "aob", "bmz", "afp", "arn", "yvt", "bae", "tnq", "cab", "crb", "unk", "pab", "sar", "yaw", "mmh", "wau", "cbb", "tae", "kpc", "aca", "mht", "rgr", "xir", "wap", "brg", "pnk", "ign", "trn", "caj", "cpc", "prq", "cpu", "cpb", "cjo", "cpy", "mcb", "apu", "inp", "mpd", "aru", "swx", "grg", "cul", "afh", "zbl", "bzt", "dws", "ina", "igs", "ile", "avk", "ldn", "lfn", "jbo", "lws", "nqo", "nov", "qya", "rmv", "sjn", "tzl", "tok", "vol", "epo", "ido", "eya", "srs", "apk", "apj", "apl", "apm", "caf", "haa", "ing", "ttm", "tce", "bea", "scs", "xsl", "ktw", "mvb", "wlk", "xup", "coq", "aht", "gol", "msw", "lma", "lia", "bun", "bmf", "buy", "kqs", "kss", "bmd", "bsp", "bgo", "ldm", "tem", "ndv", "sav", "cae", "ble", "bjt", "bda", "eja", "cwt", "krx", "mlo", "gsl", "knf", "mfv", "pbo", "bif", "mbv", "naj", "fue", "ffm", "fuf", "fuh", "fuq", "fub", "fui", "ccj", "kcj", "wof", "ega", "ged", "oks", "kcf", "ibe", "epi", "deg", "aaa", "ets", "bin", "ema", "env", "ikp", "atg", "igw", "sxs", "iya", "uha", "ehu", "uku", "opa", "olm", "ayk", "okx", "erh", "iso", "oke", "urh", "tik", "ccg", "dir", "ldh", "doh", "ndr", "bqd", "luw", "njr", "yei", "bgu", "nuh", "vut", "www", "bwh", "bju", "byb", "buz", "jms", "nhu", "bpc", "ncr", "byp", "bzy", "byf", "uba", "ukp", "bqw", "etu", "ofu", "abm", "eka", "kvm", "syi", "kbs", "sbw", "buw", "dii", "ksf", "lfa", "abb", "bbi", "bkh", "bas", "hij", "bum", "fan", "mct", "beb", "ewo", "koq", "mhb", "nda", "wum", "keb", "nra", "nxo", "bvg", "nkc", "bri", "bsi", "mbo", "bss", "bqz", "kkj", "kwu", "bmw", "mcx", "ukh", "ozm", "njy", "mcp", "biw", "gyi", "pmm", "bnm", "bxc", "nui", "dua", "mzd", "kme", "szv", "mho", "nye", "sie", "sng", "kny", "bnx", "lua", "bpj", "luj", "sop", "zla", "mxg", "pem", "mdp", "blv", "kmb", "pnd", "lue", "lch", "nkn", "nba", "lum", "mfu", "kcv", "umb", "olu", "xdo", "nql", "kua", "kwm", "ndo", "lnb", "nne", "khu", "ndq", "zms", "loo", "pof", "mwz", "soc", "zmw", "ndk", "szg", "bli", "nto", "lal", "nxd", "oml", "buf", "lel", "dez", "nkw", "ksv", "kel", "akw", "mdu", "koh", "mdw", "bvx", "mdn", "ndn", "axk", "zmx", "bui", "ngd", "lse", "bmg", "dzn", "ndl", "bws", "bml", "bzo", "bcp", "rwm", "kzy", "kmw", "kty", "nyc", "hom", "myc", "boy", "bqu", "lgz", "ngc", "bwl", "bzm", "bbm", "bkp", "loq", "bkt", "mow", "bxg", "kxx", "kwc", "mmz", "ndw", "liz", "smx", "beq", "xku", "njx", "dde", "ldi", "hng", "mkw", "ktu", "kwy", "yom", "bwz", "snq", "swj", "lnz", "ppp", "noq", "tek", "skt", "ifm", "tyx", "kkw", "tyi", "tck", "kzo", "nmd", "lli", "iyx", "dma", "wdd", "ngz", "nzu", "dov", "shq", "toi", "sbs", "wun", "mwn", "nkt", "nkv", "nyr", "nih", "nyy", "lag", "mgz", "dhs", "kam", "cuh", "thk", "soz", "mws", "sxb", "ssc", "cwa", "zak", "reg", "kya", "luy", "ida", "bxk", "lkb", "myx", "nle", "lks", "lrm", "nyd", "lts", "lto", "lwg", "lsm", "nuj", "lug", "lke", "tlj", "cgg", "nyn", "xsj", "nyg", "flr", "job", "kin", "run", "vin", "suj", "koo", "hka", "old", "vun", "jmc", "rwk", "tga", "dav", "wlc", "zdj", "swb", "wni", "coh", "dug", "nyf", "seg", "swc", "ccl", "tvs", "asa", "kki", "doe", "kcu", "kdc", "zaj", "bou", "xma", "sbm", "vid", "bez", "egm", "gmx", "kiz", "sbp", "nym", "kcz", "rwl", "bdp", "bmb", "sod", "byi", "lgm", "khx", "lea", "zmq", "ktf", "nim", "rim", "ndj", "mgy", "nww", "dne", "nxi", "mvw", "mwe", "bwc", "bem", "kdg", "ndc", "mxc", "twx", "twl", "dmx", "toh", "ssw", "rng", "kzn", "cwb", "mny", "nte", "llb", "vmr", "tke", "vmk", "mgh", "xmc", "mhm", "xsq", "brl", "nso", "two", "sot", "kmy", "mjh", "nya", "bwg", "swk", "seh", "phm", "tog", "bvb", "xmb", "bbu", "mma", "dbo", "bau", "dbm", "jjr", "gwb", "baf", "btc", "mlb", "yav", "mmu", "ekm", "yas", "leo", "bag", "ttf", "yat", "lem", "tvu", "ags", "bzz", "uiv", "uta", "ckx", "emn", "amb", "brt", "ael", "bby", "nml", "mtk", "yam", "kdz", "fmp", "bbj", "bko", "nnz", "nla", "nwe", "bfj", "bmo", "bax", "bgj", "mhk", "bce", "azo", "bfp", "pny", "bfd", "baw", "mfd", "nge", "koc", "mnf", "njj", "ngj", "nsh", "mgo", "nbv", "lns", "kfl", "bkm", "emz", "bmv", "kfn", "lmx", "isu", "zhw", "weh", "bvm", "ndb", "bqo", "bxs", "ost", "mea", "vit", "fak", "kid", "muc", "mij", "boe", "fam", "xab", "mgi", "cen", "gne", "sha", "dbi", "ikv", "khj", "mae", "pym", "tdl", "tyy", "jbm", "dkg", "ikl", "aqk", "ayu", "nbr", "kdp", "ruk", "mda", "kdm", "kci", "xsh", "ahs", "vkn", "klo", "aku", "bnz", "ldq", "aqg", "ahn", "aye", "igl", "its", "mkl", "cbj", "ijj", "luq", "yor", "nqk", "idd", "ica", "ife", "abn", "odu", "kes", "ogg", "obu", "xoc", "ebg", "ibn", "iki", "ilv", "okb", "orx", "usk", "efa", "anw", "ukq", "eke", "etb", "ibr", "itw", "itm", "nkz", "enw", "uda", "eki", "ide", "gkn", "tkq", "elm", "akd", "bbs", "uya", "iko", "yaz", "kcc", "mfn", "agb", "ldg", "ayi", "org", "kez", "eze", "byc", "yay", "bcs", "umm", "krp", "igb", "gbr", "gby", "aum", "nup", "kka", "kug", "kmi", "gpa", "vkz", "ige", "utr", "akf", "ekp", "ikk", "ikw", "ogc", "eza", "iqw", "kub", "nza", "juw", "jib", "juh", "jub", "cfg", "jrr", "bcv", "ich", "kpk", "bzw", "buj", "bsr", "amo", "byj", "klk", "gnh", "gye", "kov", "nar", "jer", "pwb", "cbo", "xsn", "scv", "dam", "awc", "tvd", "kdl", "rod", "acp", "sqa", "bsf", "ula", "gvm", "fah", "tdq", "ada", "ajg", "gbx", "tfi", "cib", "gbh", "mxl", "wem", "wud", "ayb", "gbs", "kqk", "sxw", "xwl", "xwe", "adq", "kef", "wci", "nyb", "tcd", "keu", "anf", "ahl", "kpo", "bov", "blo", "lip", "snw", "ati", "aba", "abi", "adj", "ald", "avi", "gwa", "kxb", "abr", "aka", "wss", "twi", "cko", "bci", "mtb", "aha", "nzi", "doy", "gjn", "nkq", "nko", "naw", "fod", "acd", "kph", "kye", "ncu", "bqa", "nlu", "afu", "lar", "cpn", "gwx", "abu", "eot", "dai", "tug", "bub", "glc", "zna", "glj", "kou", "bes", "goy", "kia", "lla", "yun", "vor", "gmd", "pbl", "bka", "ldk", "gwg", "jen", "mdd", "kbn", "pnz", "gke", "mcs", "tui", "mru", "toz", "pgs", "rax", "bcn", "pbn", "yot", "tdo", "wav", "ynq", "dow", "kmp", "gmn", "ver", "wok", "dur", "ndu", "dae", "klc", "ndi", "wom", "zmz", "nuu", "bbp", "yaj", "bqk", "bpd", "liy", "bfl", "tor", "gox", "kuw", "bjo", "mnh", "nue", "lna", "lnl", "msj", "doo", "mfc", "ndt", "gyg", "deq", "mgn", "ngb", "nbw", "yky", "snj", "muh", "bbe", "mdm", "gdi", "bme", "bkc", "gnz", "gix", "nbm", "moj", "kpl", "yng", "fer", "myj", "idr", "tgy", "ndz", "swf", "tbm", "brm", "pmb", "geq", "nzk", "obl", "gbv", "mzv", "aiy", "ngg", "gmm", "gya", "gbq", "gbp", "sqm", "gso", "vig", "kfz", "bwj", "bwu", "gux", "bim", "mfq", "aks", "pil", "xkt", "mos", "saf", "dgd", "wlx", "dgi", "bfo", "hag", "jmr", "beh", "ntm", "tbz", "mql", "bba", "dos", "kqm", "las", "dop", "bqg", "cll", "pug", "kst", "vag", "cli", "tpm", "sil", "ssl", "pnq", "xsm", "nuv", "nnw", "dya", "cfa", "awo", "tul", "kzc", "nku", "loi", "lor", "tsp", "wib", "xrb", "kza", "myk", "sen", "sep", "spp", "shz", "seb", "sev", "plr", "dyi", "tgw", "soy", "ahp", "fll", "fal", "jah", "cwg", "kns", "knq", "jhi", "mnq", "btq", "tea", "mhe", "szc", "sza", "tmo", "cua", "kta", "tkz", "moo", "tdr", "hre", "sed", "kxy", "hal", "jeh", "hld", "rmx", "alk", "brb", "oyb", "krv", "krr", "lbo", "sqq", "cma", "crw", "mng", "cmo", "rka", "mnn", "stt", "sti", "hkn", "tpu", "tdf", "stg", "pac", "ktv", "kuf", "tto", "tth", "bru", "ncq", "sct", "sss", "brv", "nyl", "aml", "huo", "mml", "mqt", "bgk", "stu", "lwl", "lcp", "rbb", "pce", "pll", "kxm", "okz", "mra", "khf", "tyh", "pnx", "zng", "ply", "bbh", "cbn", "omx", "gaq", "gbj", "bfw", "biy", "cdz", "mmj", "trd", "asr", "bix", "ksz", "ekl", "mjx", "juy", "caq", "ncb", "aem", "scb", "hnu", "tou", "nuo", "pyu", "tay", "szy", "byq", "kae", "fos", "atk", "eno", "nsy", "bdb", "duq", "dun", "apg", "tjg", "lbx", "twy", "kkx", "otd", "sya", "abx", "yka", "slm", "bdl", "sjm", "bdr", "sse", "sml", "ssb", "duw", "mhy", "pku", "plt", "bzc", "xmv", "bmm", "xmw", "tkg", "bhr", "txy", "msh", "bkr", "nij", "ivb", "bgi", "tiy", "tbl", "bpr", "bps", "bgz", "bgb", "zbt", "mqn", "bsu", "bkz", "xkq", "vkl", "xmz", "tlk", "wow", "mzq", "pdo", "tdi", "vko", "raz", "lbw", "wru", "xks", "llm", "bup", "zka", "ues", "lix", "pnp", "bna", "khc", "bhq", "dok", "law", "txm", "bls", "dms", "ums", "pee", "tdj", "toy", "tvw", "brs", "kzf", "lew", "unz", "myl", "klw", "pmf", "ttp", "sdu", "wtw", "kgx", "wlo", "pam", "abc", "sbl", "blx", "tre", "txn", "bay", "mqi", "lcd", "lrn", "woo", "kvo", "kpd", "baj", "kyd", "udj", "kvv", "kvp", "ksx", "ski", "slp", "lwt", "lmr", "ila", "lmj", "lmq", "lwe", "kuk", "kvh", "mqy", "riu", "reb", "rjg", "end", "ljl", "nxe", "nxg", "ror", "nea", "xbr", "mvd", "akg", "wnk", "lmy", "lur", "bnd", "wah", "bvt", "ges", "bty", "bgy", "ste", "sgu", "hud", "nni", "nxl", "spb", "plh", "kzb", "lhh", "hik", "htu", "tlu", "kzx", "hrk", "amq", "nul", "ltu", "spr", "asl", "bzn", "alo", "weo", "huk", "lcs", "lox", "alp", "nae", "kuv", "tev", "mhs", "mqc", "kzd", "tlv", "kei", "jmd", "oni", "skz", "urn", "heg", "idt", "lka", "hbu", "tdt", "krd", "nxa", "wmh", "aaz", "bkx", "lva", "dij", "ddw", "bcd", "mxz", "vme", "sve", "vbb", "mss", "emw", "imr", "tvm", "kje", "rmm", "lti", "slu", "sws", "tve", "nil", "srw", "ilu", "tzn", "apx", "wet", "mgm", "wlh", "kem", "tkd", "pkg", "anx", "lek", "ncc", "lle", "nss", "twp", "sbc", "elu", "los", "mft", "biq", "llf", "lid", "sbh", "npn", "rak", "lib", "ler", "ncn", "pek", "loj", "pmn", "ssg", "wuv", "ktk", "goo", "llx", "lmv", "aud", "fud", "mnv", "tkp", "num", "nkp", "tvl", "pkp", "tkl", "sky", "nuq", "nur", "nho", "rap", "mrq", "mqm", "mri", "rkh", "aut", "fut", "ton", "bwb", "wyy", "pif", "mpy", "woe", "mrl", "puw", "stw", "nmt", "pfa", "tpv", "sov", "kos", "nau", "pma", "mmg", "lpa", "etn", "erk", "bki", "bnk", "brj", "mmm", "lmu", "lww", "upv", "aul", "vrt", "klv", "ahb", "psw", "pgk", "onu", "mll", "mvt", "vao", "lrv", "mrs", "dix", "nvh", "nms", "rpn", "app", "sax", "ske", "sww", "lml", "omb", "nnd", "mkv", "tmi", "plb", "tls", "gnj", "aor", "akr", "sku", "tlm", "nkk", "ptr", "tmt", "vlp", "vnp", "alm", "mrp", "nrg", "lmb", "nsw", "mnl", "tsr", "btr", "mwo", "urr", "mrm", "mtt", "tgs", "msn", "hiw", "lht", "lkn", "krf", "lrz", "vra", "bgt", "nlg", "gri", "lgr", "mln", "brr", "tlr", "lgu", "apb", "kwd", "lgl", "bvc", "far", "mlu", "alu", "dor", "ora", "aia", "faf", "dhv", "nen", "nee", "jaz", "pme", "piz", "fwa", "nem", "cam", "pri", "mrk", "mkt", "wmn", "hvk", "bwa", "duf", "nek", "ane", "aji", "aqr", "aok", "cir", "aty", "iff", "erg", "uur", "tnn", "tnp", "nwi", "emi", "tns", "nlz", "ntu", "mla", "neu", "tkw", "utp", "aua", "tqp", "bjk", "lbv", "mmx", "koa", "sgz", "kqw", "rai", "bxf", "lbb", "rri", "baa", "tva", "vrs", "ttu", "urv", "sol", "nsn", "ppn", "pex", "hao", "hla", "hah", "tio", "kzk", "uge", "mvo", "mpr", "rug", "hoa", "ksg", "nke", "sbb", "lga", "tgi", "blp", "jaj", "mrn", "gga", "lgb", "kji", "grz", "ksd", "bjp", "hrw", "hrc", "tbf", "ncf", "leu", "nal", "tbj", "tgc", "lcm", "bnp", "bjl", "sij", "lbu", "ylu", "msu", "srf", "adz", "hob", "zsa", "zsu", "waz", "mpl", "una", "mcy", "buk", "kcl", "kbm", "tbx", "pix", "val", "goc", "dac", "ksl", "ptp", "zeg", "ymp", "bch", "kvc", "ggt", "mgl", "mna", "xsi", "tmy", "met", "roe", "bcu", "mpn", "wab", "gdd", "dad", "mjk", "tbc", "apr", "bbv", "uvl", "kdf", "mee", "aie", "akt", "avb", "mwg", "gip", "aaw", "bek", "mbh", "aix", "xkx", "pss", "mpo", "ssz", "lmg", "mwh", "kzu", "orz", "bpg", "kbi", "ism", "tpf", "lio", "sob", "kxa", "kbw", "trb", "mjm", "bmc", "mva", "spe", "kis", "woc", "svb", "ykm", "tmq", "sry", "aps", "mbk", "sso", "aui", "gvs", "mbq", "aai", "ubr", "mwc", "dgg", "pwg", "bmk", "mvn", "tbo", "grw", "hgw", "mum", "tpa", "wag", "ylb", "wed", "ykk", "klx", "bwd", "viv", "yml", "mzz", "dob", "dva", "sew", "bwf", "gar", "bdd", "mwa", "dww", "kqf", "kud", "bxh", "tte", "oyy", "unu", "wgb", "sbe", "swp", "oum", "bmn", "zgr", "yob", "snc", "hul", "khz", "kbt", "meu", "kse", "nrz", "mek", "don", "rro", "btp", "kij", "myw", "nmw", "tgo", "nuw", "mhz", "tni", "wrp", "agf", "bed", "erw", "dsn", "mvx", "rnn", "gop", "jau", "amk", "and", "mvr", "wbw", "wad", "mth", "ppm", "pmo", "bsm", "seu", "kjr", "wbb", "yki", "asz", "bhc", "wgo", "xmt", "kgb", "lcc", "wuy", "xmx", "bzq", "mqa", "ptn", "mky", "gzn", "due", "bik", "mmn", "dul", "agk", "agz", "atl", "bno", "prh", "msb", "bvy", "cbw", "war", "kyn", "mtw", "btw", "sgd", "tgn", "atm", "loc", "srg", "cyo", "clu", "daw", "kyk", "kll", "kqe", "ksn", "mrw", "bne", "kzp", "llq", "swu", "mog", "pns", "atd", "mbt", "msm", "mbd", "mqk", "obo", "mbi", "mbb", "bgs", "mta", "mbs", "cgc", "mba", "tbw", "bya", "tgt", "pwm", "plc", "plw", "plv", "bnj", "twb", "syb", "sfe", "stb", "skn", "suc", "kaw", "jvn", "jas", "osi", "tes", "agn", "abl", "ljp", "byd", "lra", "bth", "trx", "sdo", "rir", "scg", "sdq", "sas", "hro", "cjm", "cja", "roc", "cje", "rgs", "rog", "huq", "ibh", "rad", "dup", "hji", "xdy", "omy", "knl", "sbx", "ebc", "gef", "coa", "pea", "kvb", "mui", "mqg", "bjn", "bvu", "bve", "msi", "btj", "kxd", "jax", "mfb", "lcf", "zmi", "pel", "mhp", "jak", "pse", "orn", "ors", "vkt", "meo", "mfa", "zsm", "mbf", "mfp", "ccm", "mkn", "lrt", "pmy", "abs", "bpq", "goq", "xmm", "max", "bac", "tnw", "tnt", "tdn", "txs", "mwt", "mkm", "skh", "btz", "btd", "bbc", "akb", "btm", "alj", "iry", "tdy", "atz", "ilo", "isd", "tiu", "ibg", "azt", "att", "atp", "agt", "itv", "yog", "gdg", "gad", "aqn", "agy", "itb", "iti", "knb", "kyb", "kml", "tis", "ity", "kmk", "bjx", "kkg", "blw", "inn", "bnc", "obk", "kne", "itt", "xnn", "ifa", "ifk", "ifb", "ifu", "ilk", "iwk", "kak", "kyj", "duo", "prf", "duy", "mxr", "bhv", "kys", "xkn", "xkd", "bfg", "xay", "ree", "mxd", "sge", "zbw", "zbc", "zbe", "kyi", "ttg", "llk", "kzi", "lgi", "lnd", "snv", "tgq", "ulu", "xky", "pez", "sib", "pne", "blj", "bdg", "dbj", "dtr", "bsy", "bsb", "kqr", "kqt", "grm", "dkr", "tgb", "dtp", "mqq", "kzs", "drg", "dmv", "dtb", "abf", "srk", "txa", "ruu", "low", "dmg", "dpp", "slg", "sbr", "gnq", "plz", "tih", "mvv", "bqr", "ntd", "itd", "skp", "kag", "lhn", "mel", "dro", "kxn", "sdx", "pni", "xke", "pud", "puf", "pnm", "snr", "bvk", "bkn", "umi", "puj", "pna", "tld", "sxn", "snl", "bnq", "rth", "cml", "emb", "tmn", "kjc", "bnu", "mak", "mqx", "mdr", "wmm", "mli", "dkk", "pnc", "ulm", "kli", "mqj", "rob", "tln", "sda", "lje", "bhz", "bep", "npy", "sko", "skx", "bzl", "txe", "uon", "pzh", "bzg", "ppu", "ayr", "ayc", "bbf", "ckr", "smg", "uro", "zmh", "gum", "ttk", "kwi", "awh", "byl", "adu", "ahr", "bpo", "acb", "rkw", "xss", "bqf", "bsv", "bcb", "bhx", "bbx", "bvp", "bkg", "bso", "ctc", "cqd", "cno", "dso", "fom", "fum", "geg", "gok", "goj", "ids", "ihi", "nkf", "irr", "jya", "jbe", "kyp", "kyv", "kfj", "xao", "xhv", "kqh", "kso", "okg", "kkn", "kze", "kym", "xnh", "kex", "xmq", "wkb", "lau", "kvt", "lmh", "yne", "lbg", "lso", "len", "lrk", "lov", "luu", "zlm", "mzx", "zrg", "unx", "ned", "njd", "nmj", "nom", "nrr", "faz", "tmk", "kav", "npb", "oda", "otk", "olk", "ont", "prp", "prd", "phw", "pok", "npu", "puc", "put", "pxm", "rui", "slj", "szd", "sdt", "sls", "nsv", "ysp", "npl", "tgr", "twm", "teb", "tyl", "tgv", "urf", "whu", "xin", "ymg", "yrs", "yax", "nqy", "dwk", "cey", "clj", "nlq", "npg", "rtc", "csj", "nby", "aic", "kih", "pgi", "auw", "amn", "smf", "dnd", "imn", "snu", "wrs", "sow", "upi", "umo", "otu", "khs", "onn", "siq", "beo", "etr", "gni", "kii", "paw", "apy", "car", "ako", "tri", "way", "kui", "mzo", "kbb", "hix", "waw", "bkq", "tmz", "ciy", "mcg", "pev", "yar", "mbc", "pbc", "ake", "atr", "jru", "dno", "lmi", "asv", "mdi", "mdk", "bct", "efe", "mxh", "bvq", "luc", "avu", "log", "lgg", "kbo", "omi", "lul", "snm", "bot", "bdh", "blm", "mwu", "gbn", "mgc", "bex", "nwm", "kcm", "kah", "vae", "kyq", "jyy", "glu", "bdo", "bxv", "mne", "hor", "sba", "lap", "gqr", "mge", "dgk", "sbz", "kwv", "kwg", "kxj", "trz", "ite", "orw", "pay", "sab", "gym", "kvn", "cuk", "brn", "cjp", "kog", "mbp", "tnd", "tbn", "tuf", "tnb", "gut", "wac", "noa", "cto", "bdc", "emp", "sja", "tdc", "cmi", "ans", "crf", "alr", "krk", "boi", "inz", "puy", "coj", "coc", "yuf", "mov", "xcm", "xgr", "onj", "trh", "mti", "dgz", "mnm", "gnm", "liu", "djc", "dau", "njl", "byg", "daj", "mdx", "noz", "she", "dds", "dto", "dts", "dbw", "dbt", "dbg", "dtu", "dti", "dym", "djm", "dtt", "dtm", "tde", "aqd", "dgb", "dmb", "dol", "tqm", "kfb", "nit", "gau", "gdb", "kmj", "mjt", "xua", "hoy", "xuj", "sle", "kan", "kfe", "tcx", "pkr", "udg", "kfa", "all", "aaf", "kej", "kfh", "mjo", "mjr", "mal", "mjq", "kpb", "thn", "vis", "ctt", "wkl", "wku", "pty", "yea", "ima", "mjp", "oty", "ymr", "mjv", "pcf", "kep", "ptq", "yeu", "kfd", "vmd", "brw", "kfg", "gno", "emu", "mut", "wsg", "esg", "fmu", "mrr", "daq", "kfc", "uki", "mha", "peg", "mmk", "wbq", "mju", "kwx", "xmu", "xel", "zmo", "kxw", "kkc", "jko", "smq", "fiw", "foi", "bon", "tof", "mud", "ike", "kal", "esi", "ikt", "ems", "wrk", "wny", "bvz", "dei", "tfo", "wor", "brp", "kpi", "srt", "bti", "trt", "zme", "err", "urc", "jnj", "myo", "bwo", "moy", "cra", "kqy", "zay", "bst", "mdy", "doz", "mfx", "oyd", "wal", "dwr", "gmv", "gof", "gac", "cui", "gob", "kbc", "axb", "moc", "plg", "tob", "nid", "wlg", "hdn", "hax", "amr", "hug", "had", "fuj", "wrn", "tic", "hib", "pnu", "hmq", "hea", "hms", "muq", "mmr", "bwx", "hmj", "hml", "mww", "hrm", "hnj", "hmf", "hmv", "huj", "hmy", "hmg", "hmc", "hme", "hmi", "hmh", "hmm", "hmp", "hma", "hmw", "pha", "bwn", "buh", "bje", "bmt", "mji", "huu", "xhu", "xur", "ijs", "nkx", "iby", "okr", "orr", "ije", "dbn", "plq", "xcr", "xlu", "hlu", "xps", "xld", "xsd", "xve", "aln", "aae", "aat", "xcl", "axm", "hyw", "lvs", "olt", "orv", "chu", "svm", "slv", "xce", "xga", "xcg", "xlp", "xtg", "wlm", "owl", "xbm", "obt", "oco", "gla", "ghc", "nrc", "got", "ovd", "jut", "non", "nob", "nno", "yid", "sli", "sxu", "ydd", "yih", "ksh", "lim", "hrx", "pdc", "goh", "gct", "swg", "wae", "bar", "geh", "uln", "jvd", "pey", "afr", "oor", "brc", "dcr", "skw", "zea", "odt", "osx", "nds", "gml", "pdt", "gos", "act", "drt", "sdz", "stl", "twd", "vel", "ang", "yol", "pih", "eng", "vic", "bjs", "gyn", "trf", "aig", "afs", "gul", "bah", "tch", "svc", "gcl", "tgh", "jam", "bzj", "bzk", "srn", "kww", "kri", "gpe", "wes", "pcm", "hwc", "rop", "bis", "pis", "tpi", "tcs", "frr", "ofs", "fry", "xpg", "gmy", "rge", "cpg", "pnt", "yms", "khw", "san", "gwt", "sts", "nli", "bhu", "keq", "nhh", "ksy", "lbm", "tnv", "kfv", "nag", "rjs", "key", "lah", "pnb", "hno", "hnd", "phj", "xhe", "luv", "sbn", "lss", "kfu", "gom", "omr", "smv", "vah", "anr", "raj", "dub", "gjk", "vgr", "kxp", "wry", "jnd", "hoj", "gda", "gdx", "rwr", "bhe", "gig", "lmn", "mve", "kvx", "bge", "duh", "gbl", "mke", "vaa", "wbr", "gas", "gra", "bhi", "rtw", "noi", "dty", "jns", "mjl", "bht", "kfs", "cdh", "pgg", "cdj", "bhd", "lhl", "kfx", "bfz", "dhn", "khn", "pli", "anp", "hns", "xis", "kyw", "tdb", "sdr", "sck", "thr", "the", "tkt", "thq", "thl", "soi", "tkb", "mjz", "smm", "kra", "dry", "dwz", "pwr", "sgj", "dmk", "rmn", "rml", "rmq", "rmf", "bra", "bjj", "bha", "bns", "hca", "hif", "hin", "urd", "ghr", "ggg", "odk", "hkh", "wsv", "mvy", "clh", "gwf", "nlm", "tra", "bkk", "scl", "plk", "ush", "sdg", "div", "ved", "ave", "bgp", "ktl", "bcc", "bgn", "rdb", "srz", "gzi", "ntz", "soj", "nyq", "lsa", "sgr", "sqo", "kur", "ckb", "kmr", "sdh", "zza", "hac", "bjm", "sdf", "xkc", "vmh", "xkj", "xkp", "tov", "hrz", "avd", "esh", "rat", "tks", "atn", "vaf", "oos", "yai", "yah", "oru", "prc", "wne", "pst", "pbu", "pbt", "kho", "xtq", "peo", "pal", "zum", "jdt", "ttt", "jpr", "aiq", "prs", "haz", "bhh", "lrl", "def", "lrc", "bqi", "luz", "ask", "xvi", "trm", "xfa", "lat", "ruo", "ruq", "itk", "sdc", "rgn", "pms", "fro", "frc", "rcf", "cks", "hat", "gcr", "acf", "gcf", "scf", "mfe", "crs", "frp", "osp", "lad", "pln", "cbk", "tmg", "fax", "aoa", "pre", "cri", "mzs", "tvy", "kea", "pap", "pov", "mxi", "sdn", "sro", "src", "osc", "xum", "xhr", "umc", "pgn", "xvs", "sbv", "spx", "xae", "ims", "xvo", "xto", "txb", "xdc", "xls", "cms", "txh", "irn", "lre", "sqn", "ntw", "wdt", "amg", "ilg", "ibd", "ojp", "kzg", "okn", "tkn", "ryn", "ams", "ryu", "mvi", "anq", "oon", "acu", "hub", "kec", "tey", "kgo", "tbr", "kcp", "xtc", "mbr", "vkm", "awi", "oge", "jge", "xat", "kiq", "alc", "kbx", "kee", "kjq", "kqz", "xii", "shg", "tyu", "xuu", "nhr", "pie", "lax", "tix", "bcf", "kiw", "kjd", "kmx", "kxz", "mdb", "mcq", "aom", "nvm", "bbb", "bdf", "kpx", "kbk", "kqi", "nqm", "kig", "udu", "jje", "aja", "bjw", "hwa", "btg", "kyf", "bev", "god", "bet", "ney", "gud", "dic", "kwp", "blh", "ahm", "ahi", "grj", "gbo", "gry", "grv", "gec", "pye", "ktj", "ted", "dee", "ggb", "tja", "nwb", "das", "glr", "oub", "krn", "krw", "gxx", "wec", "big", "kup", "wer", "mfw", "huf", "ksj", "srl", "bqb", "xau", "tip", "air", "kwo", "huc", "awr", "rac", "spi", "duv", "dbf", "tty", "tds", "tcq", "kkb", "pas", "tad", "fau", "owi", "amm", "nax", "niw", "bpw", "xkw", "lpe", "rmh", "wux", "can", "yee", "xop", "mtf", "byz", "ado", "grq", "aki", "anj", "brq", "rmk", "igg", "xoi", "aod", "tbs", "tgu", "gai", "aya", "bqs", "wax", "mdg", "sbj", "kth", "mde", "kie", "rou", "kgw", "mjd", "nmu", "vmv", "luf", "mze", "bwk", "mnu", "zrs", "etz", "bqc", "bus", "bqp", "sho", "stj", "sym", "sbd", "lda", "neb", "goa", "yre", "xgb", "moa", "bxl", "lig", "tjn", "bof", "rkm", "emk", "mku", "mzj", "msc", "mxx", "jod", "jud", "kfo", "kga", "mnk", "xkg", "mwk", "jad", "mlq", "kao", "kke", "knk", "llc", "kno", "yal", "gkp", "knu", "xpe", "lom", "tod", "bza", "men", "bbo", "bwq", "sos", "bxw", "dux", "dnn", "cpo", "bze", "boo", "boz", "skq", "mpc", "alh", "mec", "wnd", "djj", "bvr", "kqc", "mds", "hoz", "sze", "mhg", "mca", "crt", "crq", "mtp", "wlv", "mzh", "kek", "usp", "quv", "qum", "tzj", "ckz", "quc", "poc", "poh", "agu", "ixl", "ttc", "emy", "ctu", "chf", "caa", "toj", "mhc", "jac", "kjb", "itz", "mop", "nug", "nji", "wmb", "miq", "ccr", "mtn", "yan", "ulw", "krb", "pmw", "csm", "nsq", "skd", "csi", "lmw", "plo", "pos", "mto", "mxp", "mco", "mir", "mzl", "mxq", "neq", "zoh", "zoc", "zos", "zor", "poi", "zoq", "poq", "yec", "gjr", "mue", "kdw", "mso", "zkt", "mhj", "bua", "mon", "bxu", "bxm", "bxr", "khk", "mvf", "xal", "yuy", "sce", "kxs", "mxk", "kxq", "krz", "jei", "nkm", "ncm", "nex", "nqn", "nmx", "mxw", "stk", "bow", "tci", "mus", "mik", "xap", "mbj", "kwa", "yab", "kpt", "xag", "sae", "nab", "wmd", "lkd", "ltn", "xtw", "naa", "tlg", "acz", "tqr", "bzf", "nud", "abt", "wos", "mle", "kxt", "spk", "bry", "gbf", "sdk", "keo", "mqu", "ukv", "imt", "lgo", "lqr", "oie", "nsg", "mas", "kdj", "nnj", "kln", "sgc", "niq", "enb", "pko", "oki", "bdi", "jum", "mfz", "dip", "diw", "dik", "dib", "dks", "anu", "bxb", "lwo", "thu", "ach", "adh", "luo", "kdi", "laj", "kja", "grs", "kmt", "tby", "gbi", "mqo", "kax", "pgu", "tlb", "tuj", "ibu", "saj", "wli", "tvo", "roo", "onw", "mei", "brk", "drb", "kdu", "elh", "kko", "wll", "xeu", "opo", "oro", "bey", "lkl", "uri", "wmo", "avt", "elk", "ong", "urt", "aon", "aah", "ape", "ymb", "eit", "xbi", "aur", "bvn", "but", "kms", "urx", "niz", "yll", "aof", "aag", "ygl", "ymo", "yde", "gnu", "stf", "sbi", "okk", "osu", "oin", "onk", "aun", "onr", "aif", "yyu", "yis", "ghs", "ykr", "sue", "zia", "bhg", "nou", "dgx", "gcn", "kpr", "aez", "hkk", "okv", "kgq", "xse", "cns", "asy", "txt", "diy", "tml", "asi", "psa", "awy", "yir", "aws", "ahh", "awu", "ktt", "wms", "aax", "bwp", "tyn", "wng", "saw", "kzv", "opk", "aip", "kwr", "kti", "kts", "bhl", "fai", "stm", "tlf", "tif", "urm", "mpt", "sug", "nkj", "tkx", "imo", "ubu", "mux", "med", "mbw", "gam", "nac", "cjv", "nof", "gvf", "sst", "whg", "wgi", "nbq", "wno", "dnt", "hap", "dni", "dna", "wlw", "ndx", "yli", "nlk", "yac", "enq", "ipi", "kyc", "leq", "mme", "asj", "bir", "net", "hui", "ssx", "akh", "aoe", "kew", "kjs", "kjy", "mpv", "nop", "nif", "noc", "fag", "mhf", "nis", "skc", "nkg", "nej", "ufi", "nnf", "klt", "smc", "klh", "yuw", "iou", "awx", "frq", "dge", "mtv", "bmp", "gka", "ygm", "nnk", "mjn", "bop", "yut", "ytw", "ons", "slw", "kqb", "sej", "kmg", "mlh", "mpp", "msz", "noh", "kco", "kuo", "tim", "spl", "mci", "naf", "ded", "tbv", "gaf", "for", "gim", "aso", "zuh", "bef", "snp", "yby", "ino", "kbq", "kmu", "kyg", "ygr", "abg", "isa", "usa", "awb", "agd", "gaj", "tbg", "omw", "waj", "kyy", "gat", "ali", "koz", "wsk", "tnh", "ped", "pla", "bie", "mvq", "xow", "mjj", "ybm", "ukg", "yrw", "kmf", "gmu", "bbd", "igo", "pnr", "bmx", "gap", "gyb", "rmp", "ydk", "bpi", "mcz", "sra", "xsp", "utu", "mqe", "nbk", "rpt", "mqv", "mqw", "swm", "wmc", "mtc", "kpw", "kmh", "taw", "wdg", "pda", "msx", "xes", "ssj", "awm", "lei", "pup", "ssd", "bpu", "mdc", "jil", "rea", "ynl", "dnr", "urg", "bpm", "gsp", "ggl", "spd", "ybo", "eip", "mtg", "kpq", "kkl", "nps", "mnz", "wod", "auu", "daz", "opy", "kqq", "acs", "xkr", "xav", "xer", "xok", "zkp", "txu", "xra", "pth", "xxr", "aft", "nyi", "wwr", "xnm", "dyd", "ywr", "nmp", "bcj", "djw", "dyb", "nyv", "azm", "azg", "cux", "cut", "mbz", "mix", "mxb", "mxa", "mks", "mih", "vmj", "mxt", "mjc", "mtu", "mio", "mza", "xtd", "vmm", "mil", "mqh", "mxs", "xtp", "xts", "vmx", "mab", "mim", "xta", "mxv", "xty", "mip", "mxy", "vmq", "miz", "xtu", "mtx", "miu", "xtb", "mii", "mit", "miy", "vmc", "jmx", "mib", "mce", "xtm", "xtn", "mie", "xtj", "mig", "mdv", "xti", "meh", "xtl", "mpm", "mvg", "trs", "trc", "trq", "coz", "pbe", "poe", "pps", "pbf", "pow", "pca", "vmp", "maa", "maq", "maj", "vmy", "mzi", "mau", "vmz", "zap", "czn", "cta", "cly", "cya", "ctp", "ctz", "zoo", "zaf", "zpy", "zaw", "zpf", "ztn", "zas", "ztt", "ztl", "zpi", "zpr", "zax", "ztg", "zpm", "zpg", "zpe", "zpa", "zpj", "zpv", "ztu", "zab", "zai", "zac", "ztx", "zpn", "zts", "zpb", "ztp", "zao", "ztm", "zpc", "zad", "zat", "zpu", "zav", "zpq", "zar", "zty", "zcd", "zsr", "zaq", "zaa", "zpd", "zae", "zca", "zpo", "zpk", "zpt", "zps", "zpx", "zte", "zpz", "zpw", "zph", "zpp", "zpl", "chj", "cso", "cuc", "csa", "ctl", "cpa", "cnt", "chz", "cvn", "cnl", "cle", "cte", "cco", "chq", "pei", "ocu", "mat", "maz", "mmc", "otm", "otn", "otx", "ote", "otq", "otz", "otl", "ots", "ott", "pbs", "pmq", "pmz", "cip", "sut", "tpc", "tcf", "tpx", "tpl", "idi", "atw", "dbl", "mwp", "gbb", "axl", "aly", "adg", "amx", "aer", "are", "axe", "wgu", "bjb", "gvy", "nnr", "nwo", "jui", "nnv", "wrm", "mem", "nna", "wbp", "wrl", "wmt", "gue", "dmw", "ddj", "rxd", "mpj", "kux", "piu", "ntj", "pjt", "kdd", "ant", "ktd", "jan", "yxg", "xbe", "yub", "ktg", "ylr", "yda", "bzr", "gnl", "gdc", "gyf", "gwu", "kgl", "zmk", "wdu", "xyb", "gyy", "zmc", "xpt", "xwk", "bxi", "dif", "nmv", "yry", "ynd", "yww", "hrp", "ard", "pit", "xpa", "dyn", "nyx", "jao", "xtv", "wga", "yil", "nyt", "ljx", "ggd", "ikr", "tgz", "typ", "pkn", "wua", "kbe", "kuy", "umd", "fln", "wie", "wih", "wij", "wim", "uwa", "ugb", "xmp", "wik", "lby", "xmy", "nxn", "xyt", "xyj", "xyk", "wnn", "mvl", "nlw", "xut", "aea", "yxm", "awg", "gwm", "dgt", "xgd", "amz", "avm", "aid", "xpj", "kkp", "uky", "bjy", "xgm", "gmr", "yia", "nha", "bia", "vml", "wbv", "lkm", "nju", "kba", "xbp", "xgg", "pnj", "xwj", "wxw", "bxj", "pnv", "bxn", "dhl", "dze", "iin", "dhr", "wri", "nhf", "tju", "vka", "nrl", "ywg", "vku", "yij", "nrk", "nly", "bdy", "zmu", "nbn", "awk", "kda", "xbj", "xrd", "xul", "dhu", "xjt", "xni", "kgs", "xya", "gnr", "dhx", "wkw", "wlu", "ddr", "pmd", "yxy", "wth", "llj", "dmd", "rnr", "xwd", "xwt", "weg", "dgw", "wyi", "xbg", "dda", "xth", "yga", "wdk", "yxl", "kky", "djf", "gvn", "vmu", "dax", "dhg", "djr", "guf", "dwu", "gnn", "dwy", "djb", "dji", "lja", "jay", "cbr", "ktx", "tux", "cao", "kuq", "pcp", "pno", "sni", "kaq", "shp", "amc", "cbs", "swo", "mcd", "yaa", "ywn", "mts", "atc", "mzr", "knt", "isc", "nuc", "pyn", "mpq", "xor", "xpk", "cav", "tna", "aro", "tno", "enr", "yuj", "wfg", "dmu", "ttn", "pnn", "nef", "mod", "dep", "cpi", "tas", "bxo", "gib", "bpl", "hmo", "njt", "fng", "pom", "poo", "pej", "peq", "prr", "qvp", "qvl", "qxa", "qub", "qvm", "qxh", "qvh", "qwh", "qxn", "qxo", "qwa", "qws", "qvw", "qxw", "qva", "qvn", "qxt", "qvc", "quf", "qwc", "quk", "qvs", "qxu", "quy", "qul", "qus", "quh", "qud", "qxl", "qvj", "qxr", "qvi", "qvo", "quw", "qvz", "qup", "quz", "qve", "qxp", "qxc", "qux", "ras", "tqn", "uma", "byt", "kgf", "kbl", "txj", "krt", "knc", "bms", "kby", "dzg", "tuq", "blc", "hur", "sec", "str", "slh", "ska", "sno", "clm", "cow", "col", "fla", "spo", "slc", "wpc", "kbv", "nxx", "set", "aau", "aad", "iwm", "cjn", "wog", "kmo", "kwj", "sim", "kmn", "xrw", "bye", "ayq", "psq", "nux", "bjh", "bnw", "mbx", "siv", "dju", "amp", "knr", "sny", "ham", "gbe", "pin", "akq", "nnm", "sht", "aen", "asw", "mzg", "psd", "afg", "sqk", "aed", "csx", "gsm", "hsl", "mdl", "lsy", "mzy", "ncs", "psg", "sqs", "tza", "lsn", "tsm", "zsl", "zib", "esl", "lbs", "sdl", "nsr", "bfi", "nzs", "asf", "pgz", "nbs", "sfs", "csg", "pys", "ugy", "hab", "hos", "csl", "gsg", "isr", "pso", "sgg", "nsp", "ins", "pks", "jsl", "kvk", "tss", "asp", "asq", "bzs", "eso", "fsl", "gss", "isg", "lsl", "mfs", "psp", "ssr", "doq", "eth", "gse", "gus", "xms", "psl", "fcs", "esn", "sgx", "tsq", "lst", "ase", "jls", "csr", "hds", "lsp", "xml", "kgi", "cds", "nsi", "rsn", "ugn", "bvl", "csn", "ecs", "prl", "csc", "vsv", "bqn", "cse", "hsh", "rms", "svk", "dse", "sfb", "vgt", "ise", "slf", "tse", "dsl", "icl", "mzc", "nsl", "ysl", "haf", "csd", "lls", "vsi", "msr", "ukl", "rsl", "ssp", "vsl", "psr", "swl", "fss", "fse", "csf", "ils", "ads", "lsc", "syy", "bfk", "rib", "rnb", "gds", "iks", "jcs", "jhs", "jus", "dsz", "mre", "rsm", "ehs", "okl", "lsw", "lsv", "szs", "tsy", "uks", "msd", "prz", "ole", "dka", "dzl", "tgf", "kjz", "xkf", "xkz", "xct", "zau", "prx", "bod", "hut", "lhm", "ola", "dre", "tcn", "ttz", "kgy", "muk", "jul", "nao", "khg", "tsk", "nes", "sbu", "jda", "spt", "sgt", "cgk", "gro", "dzo", "lya", "luk", "kbg", "adx", "kzq", "ghh", "ghe", "tge", "skj", "gvr", "npa", "chx", "taj", "tdg", "rnp", "rgk", "cdn", "bee", "xns", "tpq", "jna", "scu", "lae", "kkf", "tsj", "trp", "ria", "tpe", "usi", "xac", "aot", "kdq", "ruh", "ckh", "zkd", "tcl", "nbc", "nbe", "nph", "nnp", "kix", "lzn", "umn", "njb", "tvt", "ugo", "hpo", "mhx", "bxd", "tco", "dnv", "int", "obr", "tvn", "rmz", "yip", "phq", "bzi", "lwm", "pyy", "cnc", "how", "byo", "enu", "ktp", "aeu", "ahk", "ycp", "ymd", "slt", "jiy", "jiu", "lkc", "lhi", "kaf", "ysd", "lwu", "yiq", "ylm", "ymh", "ysg", "yku", "ykn", "yik", "ywl", "ywt", "yit", "llh", "ylo", "lgh", "ytp", "ymq", "ybk", "ypm", "ymx", "ymc", "ypn", "ypb", "yhl", "ykl", "yzk", "nsd", "nos", "yiv", "iii", "ygp", "smh", "ysy", "ywq", "yyz", "ych", "ywu", "yig", "yna", "yif", "aub", "ypp", "ypz", "ypa", "ypo", "aza", "yix", "yiz", "yso", "nuf", "zal", "ers", "nru", "qvy", "pmi", "pmj", "qxs", "tji", "tjs", "txo", "lep", "lhp", "drq", "kgj", "kip", "kif", "kjl", "mgp", "mrd", "raq", "rav", "cuw", "kle", "ncd", "rab", "raa", "wly", "cur", "aph", "byw", "lbr", "lrr", "ybi", "emg", "raf", "jee", "bhj", "vay", "dus", "brd", "jkm", "kvq", "kxf", "kvy", "eky", "kyu", "ghk", "kvu", "blk", "kjp", "pwo", "kjt", "pww", "jkp", "wea", "bgg", "mni", "nkh", "njm", "nri", "nbi", "pmx", "nnl", "npo", "nre", "nsm", "njo", "njh", "nsa", "pzn", "yim", "lpn", "jmn", "ajz", "bgr", "cbl", "cfm", "biu", "dln", "hmr", "sez", "czt", "mrh", "shl", "aim", "anm", "kmm", "nmh", "rnl", "cek", "cnk", "cnw", "zom", "gnb", "vap", "kfw", "pck", "pub", "ral", "ctd", "tcz", "csh", "csv", "cnb", "dao", "ckn", "mwq", "nng", "nma", "nbu", "nki", "njn", "nme", "nzm", "adl", "nbt", "tgj", "bca", "bfs", "mro", "duu", "rji", "rau", "jnl", "och", "wxa", "lzh", "gan", "hak", "hsn", "cjy", "cmn", "wuh", "wuu", "yue", "cdo", "cpx", "mnp", "czo", "oma", "iow", "ofo", "uni", "suo", "pux", "rwa", "wmx", "vam", "mmb", "mqf", "hmb", "ses", "tst", "ddn", "khq", "dsq", "uka", "xod", "bzp", "jbj", "dim", "aiw", "gyl", "amf", "kxh", "uis", "smz", "nas", "lni", "kqj", "lbi", "rmi", "ngm", "rmd", "rmu", "rmg", "sth", "caw", "cmt", "sui", "ggw", "aac", "wrv", "xwg", "mym", "muz", "mur", "tex", "did", "loh", "cuq", "lic", "yzg", "enc", "yln", "yha", "lha", "aou", "gir", "gqu", "lbt", "lwh", "onb", "zgm", "nut", "tys", "khb", "tyt", "tpo", "nyw", "tyj", "thi", "ksu", "try", "tdd", "tiz", "pdi", "tmm", "tts", "yoy", "zzj", "zch", "zeh", "zgn", "zgb", "zln", "zlj", "zlq", "zqe", "tnu", "tsl", "zyj", "zyn", "zyb", "mlm", "kmc", "cov", "doc", "tct", "aih", "mkg", "cdy", "mmd", "lbc", "mgb", "sjg", "tma", "gcd", "gyd", "tsz", "pua", "tuh", "mps", "ppo", "chd", "clo", "bfn", "swt", "kvd", "woi", "adn", "hmu", "klz", "jka", "twg", "nec", "ddg", "oia", "ury", "bkl", "itx", "kwt", "mqr", "mrx", "bnv", "dbe", "jbr", "kdy", "vto", "tee", "tpp", "tpt", "tlc", "top", "toc", "tos", "too", "tcw", "tku", "bao", "yui", "arj", "ynu", "ten", "mcl", "ude", "oaa", "juc", "nco", "orh", "kpn", "ait", "ktn", "mav", "awe", "kay", "xet", "nhd", "gug", "gnw", "tpj", "jor", "yuq", "yrl", "tpn", "cod", "omg", "pog", "tpk", "asn", "ama", "aan", "awt", "taf", "pak", "mdz", "asu", "twt", "gub", "jua", "paf", "wir", "pah", "api", "kgm", "kyz", "adw", "urz", "urb", "oym", "sru", "cin", "gvo", "kyr", "myu", "pur", "arr", "uru", "mpu", "aqz", "tpr", "jur", "xiy", "msp", "jbk", "jmw", "xbo", "tyv", "aib", "ybe", "uig", "uzn", "kir", "kaa", "xpc", "krc", "qxq", "slq", "azj", "azb", "giy", "wma", "vms", "pax", "rer", "std", "tme", "tka", "waf", "wsu", "woy", "avo", "aga", "hir", "dek", "dbv", "esm", "kce", "ruy", "nsc", "ksa", "kku", "kch", "ays", "dyg", "agi", "nbg", "pch", "bdz", "znk", "ygu", "apv", "xyl", "wif", "pig", "wai", "xmo", "tkf", "nrx", "bfr", "xcc", "xly", "ecr", "ecy", "gic", "hvc", "xil", "xai", "xpn", "kzw", "ktq", "zkg", "xle", "omn", "nrp", "nxm", "pkc", "xpi", "pij", "pld", "quq", "xrr", "txr", "trl", "uam", "urp", "wwb", "liv", "olo", "lud", "fkv", "mvh", "mhr", "mrj", "kpv", "koi", "yrk", "enf", "enh", "sel", "par", "ute", "mnr", "pao", "tbu", "mfy", "azz", "nhq", "nhy", "nht", "ppl", "nch", "nhe", "nhw", "nhk", "nhp", "nhx", "nhc", "nlv", "ncx", "nhz", "nsu", "nhi", "nhn", "nci", "nhm", "ncj", "nhg", "xpo", "nhv", "naz", "nuz", "ncl", "azd", "azn", "crn", "cok", "tar", "tac", "thh", "twr", "tcu", "ood", "ntp", "stp", "tla", "tep", "hei", "tww", "ybx", "wla", "ppq", "mxn", "sbg", "kzz", "msg", "zmm", "zmt", "zmg", "zmj", "zmd", "zmy", "xru", "zmr", "amy", "zma", "wil", "wub", "gma", "gww", "vmi", "xgu", "wro", "xud", "xun", "jbw", "dgn", "wrr", "jng", "bjc", "yrb", "yva", "xrn", "xpm", "cga", "mvk", "bwm", "buv", "ykg", "xcv", "wao", "ayo", "anb", "cah", "iqu", "avs", "zro", "aab", "aaq", "aas", "abd", "abe", "abk", "abp", "ace", "acm", "adb", "add", "adi", "aee", "afe", "afk", "agv", "ain", "ajn", "ajs", "als", "alw", "alx", "anl", "aol", "apf", "apo", "arc", "arx", "asg", "ash", "ate", "ato", "ava", "awv", "aww", "axx", "ayd", "ayt", "ayz", "bab", "bal", "bcg", "bck", "bcl", "bcr", "bcz", "bdj", "beg", "bei", "bfc", "bfu", "bgf", "bgl", "bgx", "bhn", "biz", "bjg", "bjv", "bkd", "bks", "bkw", "bmj", "bmu", "bnr", "bog", "bok", "bor", "bpa", "bpp", "bpy", "bql", "bqm", "bqy", "brx", "brz", "bsh", "buq", "bva", "bvv", "bwi", "bxa", "bxe", "bxz", "byk", "bym", "bzv", "bzx", "cas", "cbi", "cbq", "cbv", "ccd", "cdr", "cet", "chh", "chm", "chn", "ckm", "ckt", "cky", "clc", "clk", "clt", "cmg", "cmm", "cmr", "cnp", "cnu", "cnx", "cof", "cry", "csk", "csp", "csq", "css", "cst", "csy", "csz", "cth", "ctn", "cts", "cty", "cvg", "czh", "czk", "dbu", "dcc", "ddi", "ddo", "del", "den", "dga", "dgc", "dgl", "dgo", "dho", "dhw", "dih", "diq", "diu", "dja", "djd", "djk", "dmf", "dmm", "dmo", "dny", "doi", "dri", "dsi", "dta", "dth", "dtk", "dtn", "duk", "dum", "duz", "dyy", "eaa", "ebo", "egl", "ekk", "ell", "eme", "emq", "enm", "esk", "esu", "etc", "eto", "fab", "faj", "fap", "fat", "fay", "fbl", "fit", "flh", "fly", "fnb", "fpe", "frm", "frs", "frt", "ful", "fuv", "gae", "gal", "gba", "gbd", "gbg", "gbu", "gbw", "gdh", "gdo", "gdt", "gek", "gel", "gev", "gge", "ggu", "gha", "ghl", "ght", "gia", "gie", "gih", "gin", "giq", "giu", "giw", "gjm", "gkd", "gku", "glb", "glh", "gll", "gmg", "gmh", "gmz", "gnk", "goz", "gqn", "grc", "grr", "gsn", "gsw", "gtu", "gup", "gva", "gvc", "gvp", "gwd", "gwj", "hba", "hbs", "hed", "hem", "hgm", "hhr", "hhy", "hio", "hks", "hlt", "hmd", "hmk", "hmz", "hnh", "hov", "hps", "hrt", "htx", "hue", "hum", "huv", "hve", "hvn", "hvv", "icr", "idb", "ify", "ihb", "ihw", "iku", "ilm", "ilp", "inb", "inj", "inl", "ipk", "ire", "izz", "jaa", "jat", "jbi", "jbt", "jek", "jgk", "jid", "jih", "jiq", "jkr", "jks", "jog", "jos", "jrb", "jup", "kac", "kbp", "kcd", "kcx", "kfi", "kfr", "kgn", "khd", "khv", "khy", "kim", "kit", "kiu", "kjj", "kjo", "kjv", "kkq", "kld", "klg", "klm", "kmd", "kmq", "kmv", "kmz", "knd", "kng", "knj", "knm", "knn", "knw", "kod", "koe", "kok", "kow", "kqd", "kqo", "krj", "krs", "ksc", "ksi", "ktz", "kue", "kvz", "kwb", "kwk", "kwl", "kxk", "kxo", "kxr", "kyl", "kyo", "laa", "lab", "lay", "lbl", "lbn", "ldb", "lev", "lez", "lgk", "lgn", "lhs", "lie", "lik", "lin", "lir", "ljw", "lku", "lme", "lmf", "lng", "lnj", "lnm", "lnn", "lnw", "lou", "loy", "lro", "lsb", "lsh", "ltc", "lth", "ltz", "lui", "lus", "lut", "lvi", "lvu", "lxm", "lyg", "man", "mbm", "mch", "mcm", "mcu", "mcv", "mdh", "mep", "mev", "mfg", "mga", "mgs", "mgt", "mhn", "mhu", "mis", "mjb", "mjg", "mjy", "mkr", "mkx", "mkz", "mlg", "mlv", "mlx", "mlz", "mmf", "mmi", "mmq", "mnx", "moe", "mpb", "mpw", "mpx", "mqz", "mrb", "msa", "mte", "mtm", "mul", "mwf", "mwi", "mwr", "mxj", "mzk", "mzu", "nam", "nat", "nay", "nbd", "nbj", "nbl", "nck", "nct", "nde", "ndf", "neh", "nei", "nep", "new", "nfl", "nfr", "nfu", "nga", "ngk", "ngq", "ngr", "ngt", "ngu", "nib", "niv", "njs", "njz", "nkb", "nlo", "nlx", "nmf", "nmm", "nmn", "nmo", "nny", "npi", "npx", "nqg", "nqq", "nrf", "nrt", "nsb", "nsf", "nst", "ntg", "ntk", "ntx", "nua", "nun", "nwc", "nwg", "nwx", "nwy", "nxk", "nyh", "nys", "nzz", "oav", "oci", "ocm", "oht", "ohu", "ojv", "okc", "okh", "okm", "oko", "omk", "omp", "onx", "oog", "opt", "ori", "ort", "osn", "ota", "otb", "oua", "oue", "oui", "pad", "pan", "pav", "pbh", "pbm", "pby", "pcj", "pdu", "pef", "pep", "pes", "pfe", "pfl", "pga", "pgd", "pgl", "phl", "phr", "pir", "piv", "pka", "pkh", "plj", "pls", "pmh", "pmk", "pml", "pmr", "png", "pnw", "pop", "prg", "prk", "prn", "pro", "prt", "psc", "psh", "psi", "psm", "psu", "pti", "puo", "pus", "pyx", "que", "qug", "qur", "qwm", "qwt", "qyp", "ram", "rar", "ray", "rbk", "rbl", "rem", "ret", "rga", "rif", "ril", "rit", "rmc", "rmo", "rom", "rrt", "rsb", "rts", "rup", "rxw", "rzh", "sbf", "sbq", "sci", "scp", "scw", "scx", "sdb", "sde", "sef", "seo", "seq", "sfm", "sga", "sgb", "sgi", "sgp", "shm", "shv", "shy", "sia", "sjb", "sjd", "sje", "sjk", "sjl", "sjt", "sju", "skf", "skg", "skm", "sld", "slz", "sma", "sme", "smj", "smn", "sms", "smu", "sne", "sns", "soe", "soo", "sox", "spg", "spq", "sqr", "sqx", "sre", "srv", "ssq", "ssv", "sta", "stq", "suq", "svx", "swa", "swh", "swn", "sxc", "sxg", "sxk", "sxl", "sxm", "sxo", "tab", "tbh", "tcc", "tcp", "tdx", "teg", "ter", "tew", "tfn", "thd", "thm", "tia", "tiq", "tjj", "tjo", "tjp", "tlo", "tlp", "tlt", "tmb", "tmh", "tmv", "tnr", "tnz", "tpw", "tqb", "tqt", "tro", "trv", "tsw", "ttw", "twe", "twf", "tye", "tzm", "ubl", "uji", "ukk", "ulk", "umg", "und", "unn", "url", "uss", "uth", "vaj", "van", "vbk", "vkp", "vls", "vma", "vmb", "vmf", "vnk", "vnm", "vwa", "waa", "waq", "wbf", "wbk", "wbs", "wbt", "wca", "wdy", "wei", "wep", "weu", "wew", "wgg", "wha", "whk", "wig", "wkr", "wky", "wlr", "wmg", "wnb", "woa", "wob", "wrb", "wrg", "wrw", "wrx", "wrz", "wsi", "wsr", "wwo", "wyb", "xaj", "xam", "xaq", "xas", "xbb", "xbd", "xby", "xcb", "xco", "xcu", "xda", "xdk", "xeb", "xeg", "xep", "xgf", "xgi", "xgl", "xha", "xhc", "xhm", "xiv", "xjb", "xkb", "xki", "xkk", "xlb", "xlg", "xli", "xln", "xme", "xmh", "xmk", "xmn", "xnb", "xng", "xnj", "xnk", "xnq", "xnt", "xnu", "xny", "xom", "xpb", "xpd", "xpf", "xph", "xpl", "xpp", "xpv", "xpw", "xpx", "xpy", "xpz", "xre", "xrg", "xri", "xrm", "xrt", "xsa", "xsb", "xsc", "xsv", "xtr", "xtt", "xvn", "xwo", "xxb", "xxk", "xzm", "xzp", "yaf", "yak", "yau", "ybh", "ybn", "yel", "ygi", "ygs", "yhs", "yii", "yin", "ykt", "yly", "yok", "yon", "yrm", "yrn", "yro", "ysc", "ysm", "ysr", "yta", "ytl", "yty", "yua", "yug", "yuz", "yxa", "yyr", "zam", "zba", "zbu", "zha", "zkb", "zkh", "zkn", "zko", "zkv", "zkz", "zml", "zne", "zra", "zrn", "zsk", "ztq", "zxx", "zyp"], "license": "cc-by-4.0", "size_categories": ["1K<n<10K"], "configs": [{"config_name": "language", "data_files": "train.csv", "sep": ";"}]} | 2024-01-21T21:19:17+00:00 | [] | [
"aal",
"aap",
"aar",
"abj",
"abo",
"abq",
"abw",
"aby",
"abz",
"aci",
"ack",
"acl",
"acn",
"acr",
"acv",
"ade",
"adr",
"adt",
"ady",
"aek",
"aeq",
"aew",
"aey",
"afd",
"afi",
"afn",
"afo",
"afz",
"agc",
"age",
"agg",
"agh",
"agl",
"ago",
"agq",
"agr",
"agw",
"agx",
"ahg",
"aho",
"aik",
"ail",
"aio",
"akj",
"akk",
"akl",
"akm",
"akp",
"akv",
"akx",
"aky",
"akz",
"ala",
"ale",
"alf",
"alq",
"alt",
"alz",
"ame",
"ami",
"amj",
"amu",
"amv",
"ana",
"anh",
"ani",
"ann",
"ano",
"anv",
"any",
"aoc",
"aog",
"aoi",
"aoj",
"aos",
"aox",
"aoz",
"apn",
"apq",
"apt",
"apw",
"apz",
"aqc",
"aqm",
"aqp",
"aqt",
"arg",
"arh",
"ari",
"ark",
"arl",
"arp",
"arw",
"asb",
"asc",
"asm",
"ass",
"ast",
"asx",
"atb",
"atj",
"atq",
"atu",
"atv",
"atx",
"auc",
"aug",
"auh",
"auk",
"aup",
"auq",
"aux",
"auy",
"avn",
"avv",
"awa",
"axg",
"ayg",
"aym",
"aze",
"bak",
"bam",
"ban",
"bap",
"bav",
"bbg",
"bbk",
"bbl",
"bbn",
"bbq",
"bbr",
"bbw",
"bcm",
"bco",
"bcq",
"bdk",
"bdn",
"bdq",
"bdt",
"bdu",
"bdv",
"bdw",
"bdx",
"bec",
"bej",
"bel",
"ben",
"beu",
"bew",
"bfa",
"bfb",
"bfe",
"bff",
"bfh",
"bfm",
"bfq",
"bft",
"bfx",
"bfy",
"bga",
"bgc",
"bgd",
"bgq",
"bgw",
"bhb",
"bho",
"bhp",
"bhs",
"bhw",
"bhy",
"bib",
"bil",
"bio",
"bip",
"bit",
"biv",
"bja",
"bji",
"bjr",
"bjz",
"bkf",
"bkj",
"bku",
"bkv",
"bky",
"bld",
"blf",
"bll",
"bln",
"blq",
"blr",
"blt",
"bly",
"blz",
"bma",
"bmh",
"bmi",
"bmq",
"bmr",
"bnb",
"bnf",
"bng",
"bni",
"bnn",
"bny",
"boa",
"boh",
"boj",
"bol",
"bom",
"bos",
"box",
"bpe",
"bph",
"bpk",
"bpn",
"bpt",
"bpx",
"bpz",
"bqh",
"bqj",
"bqq",
"bqt",
"bqv",
"bqx",
"bre",
"brf",
"brh",
"bro",
"bsa",
"bsc",
"bse",
"bsg",
"bsj",
"bsl",
"bsn",
"bsq",
"bsx",
"bta",
"bte",
"btn",
"bto",
"bts",
"btt",
"btu",
"btv",
"btx",
"buc",
"bud",
"bue",
"bug",
"bul",
"buo",
"buu",
"bvd",
"bvi",
"bvj",
"bvo",
"bwe",
"bwt",
"bww",
"bwy",
"bxp",
"byh",
"bys",
"byv",
"byx",
"bzb",
"bzd",
"bzh",
"cac",
"cad",
"cag",
"cak",
"cal",
"cap",
"cat",
"cax",
"cay",
"cbc",
"cbd",
"cbg",
"cbt",
"cbu",
"cby",
"ccc",
"cce",
"cch",
"ccp",
"cda",
"cde",
"cdf",
"cdi",
"cdm",
"cea",
"ceb",
"ceg",
"ces",
"cfd",
"cha",
"chb",
"chc",
"che",
"chg",
"chk",
"chl",
"cho",
"chp",
"chr",
"cht",
"chv",
"chw",
"chy",
"cia",
"cic",
"cih",
"cik",
"cim",
"cjh",
"cji",
"cjk",
"cjs",
"ckl",
"cku",
"ckv",
"clw",
"cme",
"cna",
"cng",
"cnh",
"cni",
"cnq",
"cnr",
"cob",
"coe",
"cog",
"com",
"con",
"coo",
"cop",
"cor",
"cos",
"cot",
"cou",
"cox",
"cps",
"crc",
"crd",
"cre",
"crh",
"crk",
"crm",
"cro",
"crr",
"crv",
"crx",
"crz",
"csb",
"csw",
"ctg",
"ctm",
"cub",
"cuj",
"cuo",
"cup",
"cuu",
"cwe",
"cym",
"daa",
"dag",
"dah",
"dak",
"dan",
"dar",
"dba",
"dbd",
"dby",
"ddd",
"dec",
"deh",
"dem",
"der",
"des",
"deu",
"dev",
"dgr",
"dgs",
"dhd",
"dhi",
"dhm",
"dia",
"dig",
"dil",
"din",
"dio",
"dis",
"diz",
"dje",
"djn",
"djo",
"dlg",
"dlk",
"dlm",
"dmc",
"dml",
"dmr",
"dmy",
"dng",
"dnj",
"dnk",
"dnu",
"dnw",
"doa",
"dof",
"dox",
"drc",
"drd",
"drl",
"drn",
"dru",
"dsb",
"dtd",
"dui",
"dyo",
"dyu",
"dza",
"ebk",
"ebr",
"ebu",
"eee",
"efi",
"ego",
"eiv",
"ekg",
"eko",
"ekr",
"ele",
"eli",
"emm",
"emx",
"ena",
"enl",
"enn",
"enx",
"era",
"eri",
"ero",
"ert",
"ese",
"esq",
"ess",
"est",
"esy",
"etx",
"eus",
"eve",
"evh",
"evn",
"ewe",
"ext",
"eyo",
"faa",
"fad",
"fao",
"fas",
"ffi",
"fgr",
"fia",
"fif",
"fij",
"fil",
"fin",
"fip",
"fir",
"fkk",
"fni",
"fon",
"fqs",
"fra",
"frd",
"frk",
"fuc",
"fur",
"fuu",
"fvr",
"fwe",
"gaa",
"gag",
"gah",
"gak",
"gao",
"gaw",
"gay",
"gbk",
"gbm",
"gbz",
"gcc",
"gce",
"gdj",
"gdl",
"gdm",
"gdn",
"gdr",
"gea",
"geb",
"gei",
"gej",
"gew",
"gex",
"gey",
"gfk",
"ggk",
"ghn",
"gid",
"gil",
"git",
"gju",
"gko",
"gld",
"gle",
"glg",
"glk",
"glv",
"glw",
"gmb",
"gna",
"gng",
"gnt",
"goe",
"gog",
"goi",
"gon",
"gor",
"gov",
"gqi",
"grb",
"grh",
"grn",
"grt",
"gua",
"guc",
"guh",
"gui",
"guj",
"gun",
"guo",
"guq",
"gur",
"guu",
"guw",
"guz",
"gve",
"gvj",
"gvl",
"gwc",
"gwe",
"gwi",
"gwr",
"gyo",
"gyr",
"gza",
"hai",
"haj",
"han",
"haq",
"har",
"has",
"hau",
"hav",
"haw",
"hay",
"hbb",
"hbn",
"hch",
"heb",
"heh",
"her",
"hhi",
"hid",
"hih",
"hii",
"hil",
"hit",
"hke",
"hlb",
"hle",
"hmn",
"hmt",
"hne",
"hni",
"hnn",
"hoc",
"hoe",
"hoi",
"hol",
"hoo",
"hop",
"hot",
"hra",
"hru",
"hrv",
"hsb",
"hto",
"hts",
"huh",
"hun",
"hup",
"hus",
"huw",
"hux",
"huz",
"hye",
"iai",
"ian",
"iba",
"ibb",
"ibl",
"ibm",
"ibo",
"idc",
"idu",
"igm",
"ihp",
"ijc",
"ijn",
"ikx",
"ikz",
"ilb",
"ili",
"imi",
"iml",
"imy",
"ind",
"inh",
"ior",
"irh",
"iri",
"irk",
"iru",
"irx",
"ish",
"isi",
"isk",
"isl",
"isn",
"ist",
"ita",
"itl",
"ito",
"itr",
"ium",
"ivv",
"iwo",
"iws",
"ixc",
"iyo",
"izh",
"izr",
"jab",
"jae",
"jal",
"jav",
"jbn",
"jbu",
"jct",
"jdg",
"jeb",
"jel",
"jet",
"jgb",
"jgo",
"jic",
"jig",
"jio",
"jit",
"jiv",
"jku",
"jle",
"jma",
"jmb",
"jml",
"jni",
"jow",
"jpn",
"jqr",
"jra",
"juk",
"jun",
"juo",
"jwi",
"kab",
"kad",
"kaj",
"kap",
"kas",
"kat",
"kau",
"kaz",
"kbd",
"kbj",
"kbr",
"kbu",
"kbz",
"kca",
"kcg",
"kck",
"kcn",
"kcq",
"kcr",
"kct",
"kcw",
"kcy",
"kde",
"kdh",
"kdk",
"kdn",
"kdr",
"kdt",
"kdx",
"ked",
"keg",
"keh",
"ken",
"ket",
"kev",
"kff",
"kfk",
"kfm",
"kfp",
"kfq",
"kft",
"kfy",
"kge",
"kgg",
"kgk",
"kgp",
"kgt",
"kgu",
"kgv",
"kha",
"khe",
"khl",
"khm",
"khr",
"kht",
"kib",
"kik",
"kil",
"kio",
"kiv",
"kiy",
"kjg",
"kjh",
"kjk",
"kjm",
"kjn",
"kju",
"kjx",
"kkd",
"kkh",
"kkk",
"kkm",
"kks",
"kkt",
"kkv",
"kkz",
"klb",
"klf",
"klj",
"klq",
"klr",
"kls",
"klu",
"kly",
"kma",
"kni",
"knp",
"knv",
"knx",
"knz",
"kom",
"kon",
"kop",
"kor",
"kot",
"koy",
"kpa",
"kpe",
"kpf",
"kpg",
"kpj",
"kpm",
"kps",
"kpu",
"kpy",
"kpz",
"kqa",
"kqg",
"kql",
"kqn",
"kqp",
"kqu",
"kqv",
"kre",
"krh",
"krl",
"kru",
"kry",
"ksb",
"ksk",
"ksm",
"ksp",
"ksr",
"ksw",
"kte",
"ktm",
"kuc",
"kuj",
"kum",
"kun",
"kus",
"kut",
"kuu",
"kuz",
"kva",
"kve",
"kvf",
"kvl",
"kvr",
"kvw",
"kwe",
"kwf",
"kwh",
"kwn",
"kws",
"kwz",
"kxi",
"kxv",
"kyt",
"kyx",
"kzl",
"kzm",
"kzr",
"lac",
"lai",
"lam",
"lan",
"lao",
"laq",
"lav",
"laz",
"lbe",
"lbf",
"lbj",
"lbk",
"lbq",
"lbz",
"lce",
"lcl",
"lcq",
"ldd",
"ldj",
"ldl",
"ldo",
"ldp",
"leb",
"lec",
"led",
"lee",
"lef",
"leh",
"lej",
"les",
"let",
"lex",
"ley",
"lgq",
"lgt",
"lhu",
"lif",
"lih",
"lij",
"lil",
"lis",
"lit",
"liw",
"lji",
"lkh",
"lki",
"lkj",
"lko",
"lkr",
"lkt",
"lky",
"lld",
"llg",
"lll",
"llp",
"llu",
"lmc",
"lmd",
"lmk",
"lmo",
"lmp",
"lnh",
"lnu",
"loa",
"lob",
"loe",
"lof",
"lok",
"lol",
"lon",
"lop",
"lot",
"loz",
"lpo",
"lpx",
"lri",
"lsi",
"lsr",
"ltg",
"lub",
"lun",
"lup",
"lwa",
"lyn",
"lzl",
"lzz",
"mad",
"mag",
"mah",
"mai",
"mam",
"mar",
"maw",
"mbl",
"mbn",
"mbu",
"mby",
"mcc",
"mcf",
"mcj",
"mck",
"mdf",
"mdj",
"mdq",
"mdt",
"meb",
"mef",
"mej",
"mer",
"mew",
"mez",
"mff",
"mfi",
"mfo",
"mfr",
"mgd",
"mgf",
"mgg",
"mgj",
"mgq",
"mgr",
"mgu",
"mgv",
"mgw",
"mhd",
"mhi",
"mhl",
"mhq",
"mhw",
"mic",
"mid",
"min",
"miw",
"mje",
"mjs",
"mjw",
"mka",
"mkb",
"mkc",
"mkd",
"mki",
"mkj",
"mkk",
"mko",
"mkp",
"mkq",
"mlc",
"mlf",
"mlk",
"mlp",
"mlr",
"mls",
"mlt",
"mlw",
"mmo",
"mmp",
"mmt",
"mmv",
"mmw",
"mnb",
"mnc",
"mnd",
"mnj",
"mns",
"mnw",
"moh",
"moi",
"mok",
"mom",
"mor",
"mot",
"mox",
"mpa",
"mpe",
"mpg",
"mph",
"mpz",
"mqp",
"mqs",
"mrc",
"mrf",
"mrg",
"mrv",
"mry",
"msf",
"msk",
"msq",
"msy",
"mtd",
"mtj",
"mtl",
"mtq",
"mtr",
"mty",
"mua",
"mug",
"muo",
"mup",
"muv",
"mvp",
"mvs",
"mvu",
"mwb",
"mwl",
"mwm",
"mwv",
"mxe",
"mxf",
"mxm",
"mxo",
"mya",
"myb",
"mye",
"myf",
"myg",
"myh",
"myp",
"myv",
"myy",
"mzm",
"mzn",
"mzp",
"mzt",
"mzw",
"nak",
"nap",
"naq",
"nav",
"nbb",
"nbo",
"nbp",
"nca",
"ncg",
"ncz",
"ndd",
"ndg",
"ndh",
"ndp",
"ndy",
"neg",
"neo",
"ner",
"nev",
"nez",
"nfa",
"nfd",
"ngh",
"ngl",
"ngn",
"ngp",
"ngv",
"ngy",
"nhb",
"nia",
"nie",
"nig",
"nii",
"nik",
"nin",
"nio",
"nir",
"niu",
"nix",
"niy",
"nka",
"nkd",
"nkr",
"nks",
"nlc",
"nld",
"nlj",
"nmb",
"nmc",
"nmg",
"nmk",
"nmq",
"nmr",
"nmy",
"nmz",
"nnb",
"nnh",
"nnq",
"nnu",
"nod",
"noe",
"nog",
"noj",
"nok",
"nol",
"nor",
"not",
"now",
"noy",
"nrb",
"nrm",
"nrn",
"nse",
"nsk",
"nsx",
"nsz",
"nti",
"ntr",
"nty",
"nuk",
"nus",
"nuy",
"nvo",
"nwr",
"nxq",
"nxr",
"nyj",
"nyk",
"nyo",
"nyp",
"nyu",
"nzb",
"nzd",
"nzy",
"oac",
"obi",
"oca",
"ogb",
"ogo",
"ogu",
"oka",
"okd",
"okj",
"oku",
"olr",
"omc",
"omo",
"omt",
"ona",
"one",
"ono",
"onp",
"opm",
"ore",
"orm",
"ory",
"osa",
"oso",
"oss",
"oti",
"otr",
"pae",
"pag",
"pai",
"paq",
"pau",
"paz",
"pbb",
"pbg",
"pbi",
"pbp",
"pbr",
"pbv",
"pcb",
"pcc",
"pcd",
"pcg",
"pci",
"pcl",
"pcn",
"pdn",
"peb",
"peh",
"phd",
"phg",
"phh",
"phk",
"pho",
"pht",
"phu",
"phv",
"pia",
"pib",
"pic",
"pid",
"pio",
"pip",
"piw",
"pkb",
"pkt",
"ple",
"plu",
"pmt",
"pnh",
"pnl",
"pol",
"pon",
"por",
"pot",
"pox",
"poy",
"ppi",
"ppk",
"ppt",
"pru",
"prw",
"psn",
"pta",
"pto",
"ptt",
"ptu",
"ptv",
"ptw",
"pue",
"pui",
"pum",
"puu",
"pwi",
"pwn",
"qua",
"qui",
"qun",
"rag",
"rah",
"ran",
"rao",
"raw",
"rbp",
"rei",
"rej",
"ren",
"res",
"rey",
"rgu",
"rhg",
"rhp",
"rin",
"rkb",
"rki",
"rkt",
"rma",
"rmb",
"rme",
"rmt",
"rmw",
"rmy",
"rnd",
"rnw",
"rof",
"roh",
"rol",
"ron",
"row",
"rsk",
"rtm",
"rub",
"ruc",
"rue",
"ruf",
"rus",
"rut",
"ruz",
"rwo",
"rys",
"sad",
"sag",
"sah",
"sak",
"sam",
"saq",
"sat",
"sau",
"say",
"saz",
"sbk",
"sbo",
"sbt",
"sby",
"sch",
"scn",
"sco",
"scq",
"sdj",
"sdp",
"sea",
"see",
"sei",
"sek",
"ser",
"sey",
"sfw",
"sgh",
"sgk",
"sgm",
"sgs",
"sgy",
"shb",
"shc",
"shd",
"shh",
"shj",
"shk",
"shn",
"shr",
"shs",
"shw",
"shx",
"sif",
"sig",
"sih",
"sik",
"sin",
"sip",
"sis",
"siu",
"siw",
"six",
"siy",
"siz",
"sjo",
"sjp",
"sjr",
"sjw",
"skb",
"skr",
"sks",
"skv",
"slk",
"sll",
"slr",
"slx",
"sly",
"smk",
"smo",
"smr",
"smt",
"smw",
"smy",
"sna",
"snd",
"snf",
"snk",
"snn",
"snx",
"snz",
"soa",
"sog",
"soh",
"som",
"soq",
"sor",
"sou",
"spa",
"spc",
"spm",
"spn",
"sps",
"spu",
"spv",
"spy",
"sqh",
"sqi",
"sqt",
"squ",
"srb",
"srd",
"srh",
"sri",
"srm",
"srp",
"srq",
"srr",
"srx",
"ssf",
"ssi",
"ssk",
"ssm",
"stn",
"sto",
"sty",
"sub",
"suk",
"sun",
"sus",
"suv",
"suw",
"sux",
"suy",
"suz",
"sva",
"swe",
"swi",
"swr",
"swv",
"sxe",
"sxr",
"syk",
"syl",
"syo",
"syr",
"sys",
"syw",
"syx",
"szb",
"szl",
"szn",
"szp",
"szw",
"taa",
"tag",
"tah",
"tam",
"tao",
"tap",
"taq",
"tat",
"tau",
"tav",
"taz",
"tba",
"tbe",
"tbi",
"tbk",
"tbp",
"tbt",
"tca",
"tcb",
"tcg",
"tcy",
"tda",
"tdh",
"tdv",
"tec",
"tef",
"teh",
"tei",
"tel",
"teo",
"teq",
"tet",
"teu",
"tez",
"tfr",
"tft",
"tgk",
"tgl",
"tgp",
"tgx",
"tha",
"thf",
"thp",
"ths",
"tht",
"thy",
"tig",
"tii",
"tij",
"til",
"tin",
"tir",
"tit",
"tiv",
"tjl",
"tjw",
"tkm",
"tkr",
"tkv",
"tlh",
"tli",
"tll",
"tlq",
"tlx",
"tly",
"tmd",
"tmf",
"tmj",
"tms",
"tmu",
"tmw",
"tnc",
"tng",
"tnk",
"tnl",
"tnm",
"tnx",
"tny",
"tol",
"tom",
"toq",
"tow",
"tox",
"tpg",
"tpy",
"tpz",
"tql",
"tqo",
"trr",
"tru",
"trw",
"tsa",
"tsb",
"tsc",
"tsd",
"tsg",
"tsn",
"tso",
"tsu",
"tsv",
"tsx",
"tta",
"ttb",
"tti",
"ttj",
"ttl",
"ttv",
"tua",
"tub",
"tuc",
"tue",
"tuk",
"tum",
"tun",
"tuo",
"tur",
"tus",
"tuu",
"tuv",
"tuy",
"tuz",
"tvk",
"tvx",
"twa",
"twh",
"twn",
"twq",
"twu",
"txc",
"txg",
"txi",
"txq",
"txx",
"tya",
"tyr",
"tyz",
"tzh",
"tzo",
"tzx",
"uan",
"uar",
"uby",
"udi",
"udm",
"ugh",
"ukr",
"ukw",
"ulb",
"ulc",
"ule",
"ulf",
"uli",
"ull",
"ump",
"umu",
"une",
"ung",
"unr",
"ura",
"ure",
"urk",
"urw",
"usu",
"uum",
"uuu",
"uve",
"uvh",
"uzb",
"uzs",
"vai",
"var",
"vas",
"vau",
"vav",
"vec",
"ven",
"veo",
"vep",
"vie",
"vif",
"vkk",
"vmg",
"vmw",
"vot",
"vro",
"vum",
"wan",
"was",
"wat",
"wbe",
"wbh",
"wbi",
"wbl",
"wbm",
"wdj",
"wgy",
"wic",
"wii",
"win",
"wiv",
"wja",
"wkd",
"wln",
"wls",
"wme",
"wmi",
"wmw",
"wnc",
"wnm",
"wnp",
"wnu",
"wnw",
"wol",
"won",
"wrh",
"wsa",
"wtf",
"wti",
"wtk",
"wtm",
"wul",
"wur",
"wut",
"wwa",
"wym",
"wyn",
"wyr",
"xad",
"xan",
"xaw",
"xbc",
"xbw",
"xch",
"xdq",
"xed",
"xem",
"xgw",
"xho",
"xka",
"xkl",
"xko",
"xkv",
"xla",
"xlc",
"xmd",
"xmf",
"xmg",
"xno",
"xnr",
"xnz",
"xog",
"xon",
"xpq",
"xpr",
"xqa",
"xso",
"xsr",
"xsu",
"xsy",
"xte",
"xub",
"xug",
"xuo",
"xwa",
"xwc",
"xwr",
"xww",
"xyy",
"xzh",
"yad",
"yao",
"yap",
"yaq",
"yba",
"ybb",
"ybj",
"ybl",
"ycl",
"ycn",
"ydg",
"yej",
"yer",
"yes",
"yev",
"yey",
"yiu",
"yko",
"yla",
"yle",
"ylg",
"yme",
"ymi",
"ymk",
"ymn",
"ymz",
"ynk",
"yno",
"yns",
"yoi",
"yox",
"ypg",
"yph",
"ysn",
"yss",
"yuc",
"yuk",
"yul",
"yum",
"yup",
"yur",
"yux",
"ywa",
"yxu",
"zag",
"zen",
"zga",
"zhb",
"zhd",
"zhi",
"zhn",
"zho",
"zil",
"zim",
"zin",
"ziw",
"ziz",
"zkk",
"zkr",
"zku",
"zmb",
"zmf",
"zmn",
"zmp",
"zmv",
"zrp",
"zul",
"zun",
"zwa",
"zyg",
"kgr",
"anz",
"blb",
"boq",
"bzu",
"bsk",
"kbh",
"caz",
"xcy",
"cyb",
"cid",
"xcw",
"xcn",
"cuy",
"uhn",
"duc",
"elx",
"ett",
"fun",
"fuy",
"gta",
"gly",
"guk",
"grx",
"xht",
"xib",
"tbd",
"khp",
"xar",
"kyh",
"khh",
"xbn",
"prm",
"kla",
"kol",
"vkj",
"kto",
"laf",
"lrg",
"lvk",
"xak",
"mgk",
"xmr",
"xxm",
"mbe",
"msl",
"moq",
"akc",
"myr",
"nll",
"bhf",
"omu",
"ppe",
"pwa",
"ata",
"yae",
"puq",
"iar",
"sln",
"sao",
"svs",
"sii",
"sua",
"gpn",
"xxt",
"tcm",
"tdm",
"ttd",
"tjm",
"tiw",
"tqw",
"tqu",
"tsi",
"tud",
"umr",
"vil",
"wba",
"wiu",
"xoo",
"nce",
"yag",
"ynn",
"yra",
"yet",
"hti",
"auj",
"mzb",
"sds",
"shi",
"zgh",
"gho",
"sjs",
"thv",
"ttq",
"thz",
"gnc",
"mqb",
"mpk",
"hya",
"kvj",
"bcw",
"hig",
"bdm",
"jia",
"xmj",
"kqx",
"msv",
"mpi",
"hia",
"vem",
"mrt",
"mfm",
"bwr",
"ngx",
"mfl",
"dgh",
"ngs",
"cie",
"gdf",
"mfh",
"dme",
"meq",
"gnd",
"mif",
"mfk",
"mxu",
"muy",
"udl",
"gis",
"giz",
"bcy",
"gdu",
"ngw",
"jim",
"fli",
"gde",
"hod",
"nja",
"swq",
"tsh",
"hna",
"gou",
"dkx",
"dbq",
"bvw",
"gqa",
"hwo",
"jaf",
"ttr",
"cuv",
"maf",
"mfj",
"jie",
"moz",
"muj",
"btf",
"mou",
"trj",
"bid",
"mmy",
"jeu",
"ckq",
"mes",
"mub",
"mcw",
"ubi",
"bvf",
"mlj",
"saa",
"sok",
"tax",
"ker",
"kvi",
"lln",
"nnc",
"gab",
"ndm",
"tmc",
"gdk",
"swy",
"mse",
"mcn",
"zuy",
"nnn",
"fie",
"tdk",
"kul",
"cla",
"gwn",
"kai",
"glo",
"nbh",
"bxq",
"dbb",
"kof",
"bvh",
"ktc",
"nmi",
"kna",
"kuh",
"piy",
"tan",
"ksq",
"sur",
"anc",
"ank",
"tal",
"kcs",
"pcw",
"jrt",
"nqt",
"dbp",
"ngi",
"bde",
"auo",
"twc",
"ajw",
"tgd",
"dwa",
"bbt",
"pqa",
"sir",
"mkf",
"wji",
"bux",
"kkr",
"zns",
"grd",
"jmi",
"juu",
"tak",
"zah",
"gyz",
"dot",
"zua",
"zaz",
"awn",
"byn",
"dal",
"hdy",
"liq",
"ktb",
"drs",
"sid",
"ssy",
"kxc",
"gaz",
"gax",
"orc",
"hae",
"ssn",
"gii",
"ymm",
"rel",
"bsw",
"jii",
"dbr",
"tqq",
"bob",
"arv",
"dsh",
"elo",
"muu",
"bnl",
"wka",
"bds",
"wbj",
"gow",
"egy",
"xna",
"ara",
"arb",
"ayh",
"acw",
"jye",
"ayn",
"ssh",
"acq",
"abv",
"adf",
"afb",
"ars",
"acx",
"abh",
"auz",
"yhd",
"ayp",
"avl",
"arz",
"aec",
"shu",
"apd",
"acy",
"apc",
"ajp",
"arq",
"aao",
"mey",
"yud",
"aju",
"ayl",
"aeb",
"xaa",
"ary",
"syc",
"aii",
"cld",
"tmr",
"syn",
"bjf",
"lsd",
"huy",
"trg",
"aij",
"myz",
"amw",
"jpa",
"oar",
"hbo",
"smp",
"xdm",
"obm",
"uga",
"phn",
"xpu",
"xhd",
"inm",
"xqt",
"gez",
"amh",
"agj",
"stv",
"wle",
"gft",
"gru",
"mvz",
"sgw",
"mys",
"hoh",
"bhm",
"hss",
"gdq",
"wiy",
"bla",
"nwa",
"ats",
"crl",
"crj",
"cwd",
"crg",
"pqm",
"pim",
"unm",
"nnt",
"psy",
"xlo",
"wam",
"mia",
"kic",
"sac",
"oji",
"otw",
"ojc",
"ciw",
"ojg",
"ojb",
"ojw",
"ojs",
"aes",
"amt",
"agm",
"ygw",
"byr",
"smb",
"mcr",
"kcb",
"klp",
"ssu",
"aak",
"ipo",
"kvg",
"zik",
"bpv",
"mrz",
"bgv",
"jaq",
"aob",
"bmz",
"afp",
"arn",
"yvt",
"bae",
"tnq",
"cab",
"crb",
"unk",
"pab",
"sar",
"yaw",
"mmh",
"wau",
"cbb",
"tae",
"kpc",
"aca",
"mht",
"rgr",
"xir",
"wap",
"brg",
"pnk",
"ign",
"trn",
"caj",
"cpc",
"prq",
"cpu",
"cpb",
"cjo",
"cpy",
"mcb",
"apu",
"inp",
"mpd",
"aru",
"swx",
"grg",
"cul",
"afh",
"zbl",
"bzt",
"dws",
"ina",
"igs",
"ile",
"avk",
"ldn",
"lfn",
"jbo",
"lws",
"nqo",
"nov",
"qya",
"rmv",
"sjn",
"tzl",
"tok",
"vol",
"epo",
"ido",
"eya",
"srs",
"apk",
"apj",
"apl",
"apm",
"caf",
"haa",
"ing",
"ttm",
"tce",
"bea",
"scs",
"xsl",
"ktw",
"mvb",
"wlk",
"xup",
"coq",
"aht",
"gol",
"msw",
"lma",
"lia",
"bun",
"bmf",
"buy",
"kqs",
"kss",
"bmd",
"bsp",
"bgo",
"ldm",
"tem",
"ndv",
"sav",
"cae",
"ble",
"bjt",
"bda",
"eja",
"cwt",
"krx",
"mlo",
"gsl",
"knf",
"mfv",
"pbo",
"bif",
"mbv",
"naj",
"fue",
"ffm",
"fuf",
"fuh",
"fuq",
"fub",
"fui",
"ccj",
"kcj",
"wof",
"ega",
"ged",
"oks",
"kcf",
"ibe",
"epi",
"deg",
"aaa",
"ets",
"bin",
"ema",
"env",
"ikp",
"atg",
"igw",
"sxs",
"iya",
"uha",
"ehu",
"uku",
"opa",
"olm",
"ayk",
"okx",
"erh",
"iso",
"oke",
"urh",
"tik",
"ccg",
"dir",
"ldh",
"doh",
"ndr",
"bqd",
"luw",
"njr",
"yei",
"bgu",
"nuh",
"vut",
"www",
"bwh",
"bju",
"byb",
"buz",
"jms",
"nhu",
"bpc",
"ncr",
"byp",
"bzy",
"byf",
"uba",
"ukp",
"bqw",
"etu",
"ofu",
"abm",
"eka",
"kvm",
"syi",
"kbs",
"sbw",
"buw",
"dii",
"ksf",
"lfa",
"abb",
"bbi",
"bkh",
"bas",
"hij",
"bum",
"fan",
"mct",
"beb",
"ewo",
"koq",
"mhb",
"nda",
"wum",
"keb",
"nra",
"nxo",
"bvg",
"nkc",
"bri",
"bsi",
"mbo",
"bss",
"bqz",
"kkj",
"kwu",
"bmw",
"mcx",
"ukh",
"ozm",
"njy",
"mcp",
"biw",
"gyi",
"pmm",
"bnm",
"bxc",
"nui",
"dua",
"mzd",
"kme",
"szv",
"mho",
"nye",
"sie",
"sng",
"kny",
"bnx",
"lua",
"bpj",
"luj",
"sop",
"zla",
"mxg",
"pem",
"mdp",
"blv",
"kmb",
"pnd",
"lue",
"lch",
"nkn",
"nba",
"lum",
"mfu",
"kcv",
"umb",
"olu",
"xdo",
"nql",
"kua",
"kwm",
"ndo",
"lnb",
"nne",
"khu",
"ndq",
"zms",
"loo",
"pof",
"mwz",
"soc",
"zmw",
"ndk",
"szg",
"bli",
"nto",
"lal",
"nxd",
"oml",
"buf",
"lel",
"dez",
"nkw",
"ksv",
"kel",
"akw",
"mdu",
"koh",
"mdw",
"bvx",
"mdn",
"ndn",
"axk",
"zmx",
"bui",
"ngd",
"lse",
"bmg",
"dzn",
"ndl",
"bws",
"bml",
"bzo",
"bcp",
"rwm",
"kzy",
"kmw",
"kty",
"nyc",
"hom",
"myc",
"boy",
"bqu",
"lgz",
"ngc",
"bwl",
"bzm",
"bbm",
"bkp",
"loq",
"bkt",
"mow",
"bxg",
"kxx",
"kwc",
"mmz",
"ndw",
"liz",
"smx",
"beq",
"xku",
"njx",
"dde",
"ldi",
"hng",
"mkw",
"ktu",
"kwy",
"yom",
"bwz",
"snq",
"swj",
"lnz",
"ppp",
"noq",
"tek",
"skt",
"ifm",
"tyx",
"kkw",
"tyi",
"tck",
"kzo",
"nmd",
"lli",
"iyx",
"dma",
"wdd",
"ngz",
"nzu",
"dov",
"shq",
"toi",
"sbs",
"wun",
"mwn",
"nkt",
"nkv",
"nyr",
"nih",
"nyy",
"lag",
"mgz",
"dhs",
"kam",
"cuh",
"thk",
"soz",
"mws",
"sxb",
"ssc",
"cwa",
"zak",
"reg",
"kya",
"luy",
"ida",
"bxk",
"lkb",
"myx",
"nle",
"lks",
"lrm",
"nyd",
"lts",
"lto",
"lwg",
"lsm",
"nuj",
"lug",
"lke",
"tlj",
"cgg",
"nyn",
"xsj",
"nyg",
"flr",
"job",
"kin",
"run",
"vin",
"suj",
"koo",
"hka",
"old",
"vun",
"jmc",
"rwk",
"tga",
"dav",
"wlc",
"zdj",
"swb",
"wni",
"coh",
"dug",
"nyf",
"seg",
"swc",
"ccl",
"tvs",
"asa",
"kki",
"doe",
"kcu",
"kdc",
"zaj",
"bou",
"xma",
"sbm",
"vid",
"bez",
"egm",
"gmx",
"kiz",
"sbp",
"nym",
"kcz",
"rwl",
"bdp",
"bmb",
"sod",
"byi",
"lgm",
"khx",
"lea",
"zmq",
"ktf",
"nim",
"rim",
"ndj",
"mgy",
"nww",
"dne",
"nxi",
"mvw",
"mwe",
"bwc",
"bem",
"kdg",
"ndc",
"mxc",
"twx",
"twl",
"dmx",
"toh",
"ssw",
"rng",
"kzn",
"cwb",
"mny",
"nte",
"llb",
"vmr",
"tke",
"vmk",
"mgh",
"xmc",
"mhm",
"xsq",
"brl",
"nso",
"two",
"sot",
"kmy",
"mjh",
"nya",
"bwg",
"swk",
"seh",
"phm",
"tog",
"bvb",
"xmb",
"bbu",
"mma",
"dbo",
"bau",
"dbm",
"jjr",
"gwb",
"baf",
"btc",
"mlb",
"yav",
"mmu",
"ekm",
"yas",
"leo",
"bag",
"ttf",
"yat",
"lem",
"tvu",
"ags",
"bzz",
"uiv",
"uta",
"ckx",
"emn",
"amb",
"brt",
"ael",
"bby",
"nml",
"mtk",
"yam",
"kdz",
"fmp",
"bbj",
"bko",
"nnz",
"nla",
"nwe",
"bfj",
"bmo",
"bax",
"bgj",
"mhk",
"bce",
"azo",
"bfp",
"pny",
"bfd",
"baw",
"mfd",
"nge",
"koc",
"mnf",
"njj",
"ngj",
"nsh",
"mgo",
"nbv",
"lns",
"kfl",
"bkm",
"emz",
"bmv",
"kfn",
"lmx",
"isu",
"zhw",
"weh",
"bvm",
"ndb",
"bqo",
"bxs",
"ost",
"mea",
"vit",
"fak",
"kid",
"muc",
"mij",
"boe",
"fam",
"xab",
"mgi",
"cen",
"gne",
"sha",
"dbi",
"ikv",
"khj",
"mae",
"pym",
"tdl",
"tyy",
"jbm",
"dkg",
"ikl",
"aqk",
"ayu",
"nbr",
"kdp",
"ruk",
"mda",
"kdm",
"kci",
"xsh",
"ahs",
"vkn",
"klo",
"aku",
"bnz",
"ldq",
"aqg",
"ahn",
"aye",
"igl",
"its",
"mkl",
"cbj",
"ijj",
"luq",
"yor",
"nqk",
"idd",
"ica",
"ife",
"abn",
"odu",
"kes",
"ogg",
"obu",
"xoc",
"ebg",
"ibn",
"iki",
"ilv",
"okb",
"orx",
"usk",
"efa",
"anw",
"ukq",
"eke",
"etb",
"ibr",
"itw",
"itm",
"nkz",
"enw",
"uda",
"eki",
"ide",
"gkn",
"tkq",
"elm",
"akd",
"bbs",
"uya",
"iko",
"yaz",
"kcc",
"mfn",
"agb",
"ldg",
"ayi",
"org",
"kez",
"eze",
"byc",
"yay",
"bcs",
"umm",
"krp",
"igb",
"gbr",
"gby",
"aum",
"nup",
"kka",
"kug",
"kmi",
"gpa",
"vkz",
"ige",
"utr",
"akf",
"ekp",
"ikk",
"ikw",
"ogc",
"eza",
"iqw",
"kub",
"nza",
"juw",
"jib",
"juh",
"jub",
"cfg",
"jrr",
"bcv",
"ich",
"kpk",
"bzw",
"buj",
"bsr",
"amo",
"byj",
"klk",
"gnh",
"gye",
"kov",
"nar",
"jer",
"pwb",
"cbo",
"xsn",
"scv",
"dam",
"awc",
"tvd",
"kdl",
"rod",
"acp",
"sqa",
"bsf",
"ula",
"gvm",
"fah",
"tdq",
"ada",
"ajg",
"gbx",
"tfi",
"cib",
"gbh",
"mxl",
"wem",
"wud",
"ayb",
"gbs",
"kqk",
"sxw",
"xwl",
"xwe",
"adq",
"kef",
"wci",
"nyb",
"tcd",
"keu",
"anf",
"ahl",
"kpo",
"bov",
"blo",
"lip",
"snw",
"ati",
"aba",
"abi",
"adj",
"ald",
"avi",
"gwa",
"kxb",
"abr",
"aka",
"wss",
"twi",
"cko",
"bci",
"mtb",
"aha",
"nzi",
"doy",
"gjn",
"nkq",
"nko",
"naw",
"fod",
"acd",
"kph",
"kye",
"ncu",
"bqa",
"nlu",
"afu",
"lar",
"cpn",
"gwx",
"abu",
"eot",
"dai",
"tug",
"bub",
"glc",
"zna",
"glj",
"kou",
"bes",
"goy",
"kia",
"lla",
"yun",
"vor",
"gmd",
"pbl",
"bka",
"ldk",
"gwg",
"jen",
"mdd",
"kbn",
"pnz",
"gke",
"mcs",
"tui",
"mru",
"toz",
"pgs",
"rax",
"bcn",
"pbn",
"yot",
"tdo",
"wav",
"ynq",
"dow",
"kmp",
"gmn",
"ver",
"wok",
"dur",
"ndu",
"dae",
"klc",
"ndi",
"wom",
"zmz",
"nuu",
"bbp",
"yaj",
"bqk",
"bpd",
"liy",
"bfl",
"tor",
"gox",
"kuw",
"bjo",
"mnh",
"nue",
"lna",
"lnl",
"msj",
"doo",
"mfc",
"ndt",
"gyg",
"deq",
"mgn",
"ngb",
"nbw",
"yky",
"snj",
"muh",
"bbe",
"mdm",
"gdi",
"bme",
"bkc",
"gnz",
"gix",
"nbm",
"moj",
"kpl",
"yng",
"fer",
"myj",
"idr",
"tgy",
"ndz",
"swf",
"tbm",
"brm",
"pmb",
"geq",
"nzk",
"obl",
"gbv",
"mzv",
"aiy",
"ngg",
"gmm",
"gya",
"gbq",
"gbp",
"sqm",
"gso",
"vig",
"kfz",
"bwj",
"bwu",
"gux",
"bim",
"mfq",
"aks",
"pil",
"xkt",
"mos",
"saf",
"dgd",
"wlx",
"dgi",
"bfo",
"hag",
"jmr",
"beh",
"ntm",
"tbz",
"mql",
"bba",
"dos",
"kqm",
"las",
"dop",
"bqg",
"cll",
"pug",
"kst",
"vag",
"cli",
"tpm",
"sil",
"ssl",
"pnq",
"xsm",
"nuv",
"nnw",
"dya",
"cfa",
"awo",
"tul",
"kzc",
"nku",
"loi",
"lor",
"tsp",
"wib",
"xrb",
"kza",
"myk",
"sen",
"sep",
"spp",
"shz",
"seb",
"sev",
"plr",
"dyi",
"tgw",
"soy",
"ahp",
"fll",
"fal",
"jah",
"cwg",
"kns",
"knq",
"jhi",
"mnq",
"btq",
"tea",
"mhe",
"szc",
"sza",
"tmo",
"cua",
"kta",
"tkz",
"moo",
"tdr",
"hre",
"sed",
"kxy",
"hal",
"jeh",
"hld",
"rmx",
"alk",
"brb",
"oyb",
"krv",
"krr",
"lbo",
"sqq",
"cma",
"crw",
"mng",
"cmo",
"rka",
"mnn",
"stt",
"sti",
"hkn",
"tpu",
"tdf",
"stg",
"pac",
"ktv",
"kuf",
"tto",
"tth",
"bru",
"ncq",
"sct",
"sss",
"brv",
"nyl",
"aml",
"huo",
"mml",
"mqt",
"bgk",
"stu",
"lwl",
"lcp",
"rbb",
"pce",
"pll",
"kxm",
"okz",
"mra",
"khf",
"tyh",
"pnx",
"zng",
"ply",
"bbh",
"cbn",
"omx",
"gaq",
"gbj",
"bfw",
"biy",
"cdz",
"mmj",
"trd",
"asr",
"bix",
"ksz",
"ekl",
"mjx",
"juy",
"caq",
"ncb",
"aem",
"scb",
"hnu",
"tou",
"nuo",
"pyu",
"tay",
"szy",
"byq",
"kae",
"fos",
"atk",
"eno",
"nsy",
"bdb",
"duq",
"dun",
"apg",
"tjg",
"lbx",
"twy",
"kkx",
"otd",
"sya",
"abx",
"yka",
"slm",
"bdl",
"sjm",
"bdr",
"sse",
"sml",
"ssb",
"duw",
"mhy",
"pku",
"plt",
"bzc",
"xmv",
"bmm",
"xmw",
"tkg",
"bhr",
"txy",
"msh",
"bkr",
"nij",
"ivb",
"bgi",
"tiy",
"tbl",
"bpr",
"bps",
"bgz",
"bgb",
"zbt",
"mqn",
"bsu",
"bkz",
"xkq",
"vkl",
"xmz",
"tlk",
"wow",
"mzq",
"pdo",
"tdi",
"vko",
"raz",
"lbw",
"wru",
"xks",
"llm",
"bup",
"zka",
"ues",
"lix",
"pnp",
"bna",
"khc",
"bhq",
"dok",
"law",
"txm",
"bls",
"dms",
"ums",
"pee",
"tdj",
"toy",
"tvw",
"brs",
"kzf",
"lew",
"unz",
"myl",
"klw",
"pmf",
"ttp",
"sdu",
"wtw",
"kgx",
"wlo",
"pam",
"abc",
"sbl",
"blx",
"tre",
"txn",
"bay",
"mqi",
"lcd",
"lrn",
"woo",
"kvo",
"kpd",
"baj",
"kyd",
"udj",
"kvv",
"kvp",
"ksx",
"ski",
"slp",
"lwt",
"lmr",
"ila",
"lmj",
"lmq",
"lwe",
"kuk",
"kvh",
"mqy",
"riu",
"reb",
"rjg",
"end",
"ljl",
"nxe",
"nxg",
"ror",
"nea",
"xbr",
"mvd",
"akg",
"wnk",
"lmy",
"lur",
"bnd",
"wah",
"bvt",
"ges",
"bty",
"bgy",
"ste",
"sgu",
"hud",
"nni",
"nxl",
"spb",
"plh",
"kzb",
"lhh",
"hik",
"htu",
"tlu",
"kzx",
"hrk",
"amq",
"nul",
"ltu",
"spr",
"asl",
"bzn",
"alo",
"weo",
"huk",
"lcs",
"lox",
"alp",
"nae",
"kuv",
"tev",
"mhs",
"mqc",
"kzd",
"tlv",
"kei",
"jmd",
"oni",
"skz",
"urn",
"heg",
"idt",
"lka",
"hbu",
"tdt",
"krd",
"nxa",
"wmh",
"aaz",
"bkx",
"lva",
"dij",
"ddw",
"bcd",
"mxz",
"vme",
"sve",
"vbb",
"mss",
"emw",
"imr",
"tvm",
"kje",
"rmm",
"lti",
"slu",
"sws",
"tve",
"nil",
"srw",
"ilu",
"tzn",
"apx",
"wet",
"mgm",
"wlh",
"kem",
"tkd",
"pkg",
"anx",
"lek",
"ncc",
"lle",
"nss",
"twp",
"sbc",
"elu",
"los",
"mft",
"biq",
"llf",
"lid",
"sbh",
"npn",
"rak",
"lib",
"ler",
"ncn",
"pek",
"loj",
"pmn",
"ssg",
"wuv",
"ktk",
"goo",
"llx",
"lmv",
"aud",
"fud",
"mnv",
"tkp",
"num",
"nkp",
"tvl",
"pkp",
"tkl",
"sky",
"nuq",
"nur",
"nho",
"rap",
"mrq",
"mqm",
"mri",
"rkh",
"aut",
"fut",
"ton",
"bwb",
"wyy",
"pif",
"mpy",
"woe",
"mrl",
"puw",
"stw",
"nmt",
"pfa",
"tpv",
"sov",
"kos",
"nau",
"pma",
"mmg",
"lpa",
"etn",
"erk",
"bki",
"bnk",
"brj",
"mmm",
"lmu",
"lww",
"upv",
"aul",
"vrt",
"klv",
"ahb",
"psw",
"pgk",
"onu",
"mll",
"mvt",
"vao",
"lrv",
"mrs",
"dix",
"nvh",
"nms",
"rpn",
"app",
"sax",
"ske",
"sww",
"lml",
"omb",
"nnd",
"mkv",
"tmi",
"plb",
"tls",
"gnj",
"aor",
"akr",
"sku",
"tlm",
"nkk",
"ptr",
"tmt",
"vlp",
"vnp",
"alm",
"mrp",
"nrg",
"lmb",
"nsw",
"mnl",
"tsr",
"btr",
"mwo",
"urr",
"mrm",
"mtt",
"tgs",
"msn",
"hiw",
"lht",
"lkn",
"krf",
"lrz",
"vra",
"bgt",
"nlg",
"gri",
"lgr",
"mln",
"brr",
"tlr",
"lgu",
"apb",
"kwd",
"lgl",
"bvc",
"far",
"mlu",
"alu",
"dor",
"ora",
"aia",
"faf",
"dhv",
"nen",
"nee",
"jaz",
"pme",
"piz",
"fwa",
"nem",
"cam",
"pri",
"mrk",
"mkt",
"wmn",
"hvk",
"bwa",
"duf",
"nek",
"ane",
"aji",
"aqr",
"aok",
"cir",
"aty",
"iff",
"erg",
"uur",
"tnn",
"tnp",
"nwi",
"emi",
"tns",
"nlz",
"ntu",
"mla",
"neu",
"tkw",
"utp",
"aua",
"tqp",
"bjk",
"lbv",
"mmx",
"koa",
"sgz",
"kqw",
"rai",
"bxf",
"lbb",
"rri",
"baa",
"tva",
"vrs",
"ttu",
"urv",
"sol",
"nsn",
"ppn",
"pex",
"hao",
"hla",
"hah",
"tio",
"kzk",
"uge",
"mvo",
"mpr",
"rug",
"hoa",
"ksg",
"nke",
"sbb",
"lga",
"tgi",
"blp",
"jaj",
"mrn",
"gga",
"lgb",
"kji",
"grz",
"ksd",
"bjp",
"hrw",
"hrc",
"tbf",
"ncf",
"leu",
"nal",
"tbj",
"tgc",
"lcm",
"bnp",
"bjl",
"sij",
"lbu",
"ylu",
"msu",
"srf",
"adz",
"hob",
"zsa",
"zsu",
"waz",
"mpl",
"una",
"mcy",
"buk",
"kcl",
"kbm",
"tbx",
"pix",
"val",
"goc",
"dac",
"ksl",
"ptp",
"zeg",
"ymp",
"bch",
"kvc",
"ggt",
"mgl",
"mna",
"xsi",
"tmy",
"met",
"roe",
"bcu",
"mpn",
"wab",
"gdd",
"dad",
"mjk",
"tbc",
"apr",
"bbv",
"uvl",
"kdf",
"mee",
"aie",
"akt",
"avb",
"mwg",
"gip",
"aaw",
"bek",
"mbh",
"aix",
"xkx",
"pss",
"mpo",
"ssz",
"lmg",
"mwh",
"kzu",
"orz",
"bpg",
"kbi",
"ism",
"tpf",
"lio",
"sob",
"kxa",
"kbw",
"trb",
"mjm",
"bmc",
"mva",
"spe",
"kis",
"woc",
"svb",
"ykm",
"tmq",
"sry",
"aps",
"mbk",
"sso",
"aui",
"gvs",
"mbq",
"aai",
"ubr",
"mwc",
"dgg",
"pwg",
"bmk",
"mvn",
"tbo",
"grw",
"hgw",
"mum",
"tpa",
"wag",
"ylb",
"wed",
"ykk",
"klx",
"bwd",
"viv",
"yml",
"mzz",
"dob",
"dva",
"sew",
"bwf",
"gar",
"bdd",
"mwa",
"dww",
"kqf",
"kud",
"bxh",
"tte",
"oyy",
"unu",
"wgb",
"sbe",
"swp",
"oum",
"bmn",
"zgr",
"yob",
"snc",
"hul",
"khz",
"kbt",
"meu",
"kse",
"nrz",
"mek",
"don",
"rro",
"btp",
"kij",
"myw",
"nmw",
"tgo",
"nuw",
"mhz",
"tni",
"wrp",
"agf",
"bed",
"erw",
"dsn",
"mvx",
"rnn",
"gop",
"jau",
"amk",
"and",
"mvr",
"wbw",
"wad",
"mth",
"ppm",
"pmo",
"bsm",
"seu",
"kjr",
"wbb",
"yki",
"asz",
"bhc",
"wgo",
"xmt",
"kgb",
"lcc",
"wuy",
"xmx",
"bzq",
"mqa",
"ptn",
"mky",
"gzn",
"due",
"bik",
"mmn",
"dul",
"agk",
"agz",
"atl",
"bno",
"prh",
"msb",
"bvy",
"cbw",
"war",
"kyn",
"mtw",
"btw",
"sgd",
"tgn",
"atm",
"loc",
"srg",
"cyo",
"clu",
"daw",
"kyk",
"kll",
"kqe",
"ksn",
"mrw",
"bne",
"kzp",
"llq",
"swu",
"mog",
"pns",
"atd",
"mbt",
"msm",
"mbd",
"mqk",
"obo",
"mbi",
"mbb",
"bgs",
"mta",
"mbs",
"cgc",
"mba",
"tbw",
"bya",
"tgt",
"pwm",
"plc",
"plw",
"plv",
"bnj",
"twb",
"syb",
"sfe",
"stb",
"skn",
"suc",
"kaw",
"jvn",
"jas",
"osi",
"tes",
"agn",
"abl",
"ljp",
"byd",
"lra",
"bth",
"trx",
"sdo",
"rir",
"scg",
"sdq",
"sas",
"hro",
"cjm",
"cja",
"roc",
"cje",
"rgs",
"rog",
"huq",
"ibh",
"rad",
"dup",
"hji",
"xdy",
"omy",
"knl",
"sbx",
"ebc",
"gef",
"coa",
"pea",
"kvb",
"mui",
"mqg",
"bjn",
"bvu",
"bve",
"msi",
"btj",
"kxd",
"jax",
"mfb",
"lcf",
"zmi",
"pel",
"mhp",
"jak",
"pse",
"orn",
"ors",
"vkt",
"meo",
"mfa",
"zsm",
"mbf",
"mfp",
"ccm",
"mkn",
"lrt",
"pmy",
"abs",
"bpq",
"goq",
"xmm",
"max",
"bac",
"tnw",
"tnt",
"tdn",
"txs",
"mwt",
"mkm",
"skh",
"btz",
"btd",
"bbc",
"akb",
"btm",
"alj",
"iry",
"tdy",
"atz",
"ilo",
"isd",
"tiu",
"ibg",
"azt",
"att",
"atp",
"agt",
"itv",
"yog",
"gdg",
"gad",
"aqn",
"agy",
"itb",
"iti",
"knb",
"kyb",
"kml",
"tis",
"ity",
"kmk",
"bjx",
"kkg",
"blw",
"inn",
"bnc",
"obk",
"kne",
"itt",
"xnn",
"ifa",
"ifk",
"ifb",
"ifu",
"ilk",
"iwk",
"kak",
"kyj",
"duo",
"prf",
"duy",
"mxr",
"bhv",
"kys",
"xkn",
"xkd",
"bfg",
"xay",
"ree",
"mxd",
"sge",
"zbw",
"zbc",
"zbe",
"kyi",
"ttg",
"llk",
"kzi",
"lgi",
"lnd",
"snv",
"tgq",
"ulu",
"xky",
"pez",
"sib",
"pne",
"blj",
"bdg",
"dbj",
"dtr",
"bsy",
"bsb",
"kqr",
"kqt",
"grm",
"dkr",
"tgb",
"dtp",
"mqq",
"kzs",
"drg",
"dmv",
"dtb",
"abf",
"srk",
"txa",
"ruu",
"low",
"dmg",
"dpp",
"slg",
"sbr",
"gnq",
"plz",
"tih",
"mvv",
"bqr",
"ntd",
"itd",
"skp",
"kag",
"lhn",
"mel",
"dro",
"kxn",
"sdx",
"pni",
"xke",
"pud",
"puf",
"pnm",
"snr",
"bvk",
"bkn",
"umi",
"puj",
"pna",
"tld",
"sxn",
"snl",
"bnq",
"rth",
"cml",
"emb",
"tmn",
"kjc",
"bnu",
"mak",
"mqx",
"mdr",
"wmm",
"mli",
"dkk",
"pnc",
"ulm",
"kli",
"mqj",
"rob",
"tln",
"sda",
"lje",
"bhz",
"bep",
"npy",
"sko",
"skx",
"bzl",
"txe",
"uon",
"pzh",
"bzg",
"ppu",
"ayr",
"ayc",
"bbf",
"ckr",
"smg",
"uro",
"zmh",
"gum",
"ttk",
"kwi",
"awh",
"byl",
"adu",
"ahr",
"bpo",
"acb",
"rkw",
"xss",
"bqf",
"bsv",
"bcb",
"bhx",
"bbx",
"bvp",
"bkg",
"bso",
"ctc",
"cqd",
"cno",
"dso",
"fom",
"fum",
"geg",
"gok",
"goj",
"ids",
"ihi",
"nkf",
"irr",
"jya",
"jbe",
"kyp",
"kyv",
"kfj",
"xao",
"xhv",
"kqh",
"kso",
"okg",
"kkn",
"kze",
"kym",
"xnh",
"kex",
"xmq",
"wkb",
"lau",
"kvt",
"lmh",
"yne",
"lbg",
"lso",
"len",
"lrk",
"lov",
"luu",
"zlm",
"mzx",
"zrg",
"unx",
"ned",
"njd",
"nmj",
"nom",
"nrr",
"faz",
"tmk",
"kav",
"npb",
"oda",
"otk",
"olk",
"ont",
"prp",
"prd",
"phw",
"pok",
"npu",
"puc",
"put",
"pxm",
"rui",
"slj",
"szd",
"sdt",
"sls",
"nsv",
"ysp",
"npl",
"tgr",
"twm",
"teb",
"tyl",
"tgv",
"urf",
"whu",
"xin",
"ymg",
"yrs",
"yax",
"nqy",
"dwk",
"cey",
"clj",
"nlq",
"npg",
"rtc",
"csj",
"nby",
"aic",
"kih",
"pgi",
"auw",
"amn",
"smf",
"dnd",
"imn",
"snu",
"wrs",
"sow",
"upi",
"umo",
"otu",
"khs",
"onn",
"siq",
"beo",
"etr",
"gni",
"kii",
"paw",
"apy",
"car",
"ako",
"tri",
"way",
"kui",
"mzo",
"kbb",
"hix",
"waw",
"bkq",
"tmz",
"ciy",
"mcg",
"pev",
"yar",
"mbc",
"pbc",
"ake",
"atr",
"jru",
"dno",
"lmi",
"asv",
"mdi",
"mdk",
"bct",
"efe",
"mxh",
"bvq",
"luc",
"avu",
"log",
"lgg",
"kbo",
"omi",
"lul",
"snm",
"bot",
"bdh",
"blm",
"mwu",
"gbn",
"mgc",
"bex",
"nwm",
"kcm",
"kah",
"vae",
"kyq",
"jyy",
"glu",
"bdo",
"bxv",
"mne",
"hor",
"sba",
"lap",
"gqr",
"mge",
"dgk",
"sbz",
"kwv",
"kwg",
"kxj",
"trz",
"ite",
"orw",
"pay",
"sab",
"gym",
"kvn",
"cuk",
"brn",
"cjp",
"kog",
"mbp",
"tnd",
"tbn",
"tuf",
"tnb",
"gut",
"wac",
"noa",
"cto",
"bdc",
"emp",
"sja",
"tdc",
"cmi",
"ans",
"crf",
"alr",
"krk",
"boi",
"inz",
"puy",
"coj",
"coc",
"yuf",
"mov",
"xcm",
"xgr",
"onj",
"trh",
"mti",
"dgz",
"mnm",
"gnm",
"liu",
"djc",
"dau",
"njl",
"byg",
"daj",
"mdx",
"noz",
"she",
"dds",
"dto",
"dts",
"dbw",
"dbt",
"dbg",
"dtu",
"dti",
"dym",
"djm",
"dtt",
"dtm",
"tde",
"aqd",
"dgb",
"dmb",
"dol",
"tqm",
"kfb",
"nit",
"gau",
"gdb",
"kmj",
"mjt",
"xua",
"hoy",
"xuj",
"sle",
"kan",
"kfe",
"tcx",
"pkr",
"udg",
"kfa",
"all",
"aaf",
"kej",
"kfh",
"mjo",
"mjr",
"mal",
"mjq",
"kpb",
"thn",
"vis",
"ctt",
"wkl",
"wku",
"pty",
"yea",
"ima",
"mjp",
"oty",
"ymr",
"mjv",
"pcf",
"kep",
"ptq",
"yeu",
"kfd",
"vmd",
"brw",
"kfg",
"gno",
"emu",
"mut",
"wsg",
"esg",
"fmu",
"mrr",
"daq",
"kfc",
"uki",
"mha",
"peg",
"mmk",
"wbq",
"mju",
"kwx",
"xmu",
"xel",
"zmo",
"kxw",
"kkc",
"jko",
"smq",
"fiw",
"foi",
"bon",
"tof",
"mud",
"ike",
"kal",
"esi",
"ikt",
"ems",
"wrk",
"wny",
"bvz",
"dei",
"tfo",
"wor",
"brp",
"kpi",
"srt",
"bti",
"trt",
"zme",
"err",
"urc",
"jnj",
"myo",
"bwo",
"moy",
"cra",
"kqy",
"zay",
"bst",
"mdy",
"doz",
"mfx",
"oyd",
"wal",
"dwr",
"gmv",
"gof",
"gac",
"cui",
"gob",
"kbc",
"axb",
"moc",
"plg",
"tob",
"nid",
"wlg",
"hdn",
"hax",
"amr",
"hug",
"had",
"fuj",
"wrn",
"tic",
"hib",
"pnu",
"hmq",
"hea",
"hms",
"muq",
"mmr",
"bwx",
"hmj",
"hml",
"mww",
"hrm",
"hnj",
"hmf",
"hmv",
"huj",
"hmy",
"hmg",
"hmc",
"hme",
"hmi",
"hmh",
"hmm",
"hmp",
"hma",
"hmw",
"pha",
"bwn",
"buh",
"bje",
"bmt",
"mji",
"huu",
"xhu",
"xur",
"ijs",
"nkx",
"iby",
"okr",
"orr",
"ije",
"dbn",
"plq",
"xcr",
"xlu",
"hlu",
"xps",
"xld",
"xsd",
"xve",
"aln",
"aae",
"aat",
"xcl",
"axm",
"hyw",
"lvs",
"olt",
"orv",
"chu",
"svm",
"slv",
"xce",
"xga",
"xcg",
"xlp",
"xtg",
"wlm",
"owl",
"xbm",
"obt",
"oco",
"gla",
"ghc",
"nrc",
"got",
"ovd",
"jut",
"non",
"nob",
"nno",
"yid",
"sli",
"sxu",
"ydd",
"yih",
"ksh",
"lim",
"hrx",
"pdc",
"goh",
"gct",
"swg",
"wae",
"bar",
"geh",
"uln",
"jvd",
"pey",
"afr",
"oor",
"brc",
"dcr",
"skw",
"zea",
"odt",
"osx",
"nds",
"gml",
"pdt",
"gos",
"act",
"drt",
"sdz",
"stl",
"twd",
"vel",
"ang",
"yol",
"pih",
"eng",
"vic",
"bjs",
"gyn",
"trf",
"aig",
"afs",
"gul",
"bah",
"tch",
"svc",
"gcl",
"tgh",
"jam",
"bzj",
"bzk",
"srn",
"kww",
"kri",
"gpe",
"wes",
"pcm",
"hwc",
"rop",
"bis",
"pis",
"tpi",
"tcs",
"frr",
"ofs",
"fry",
"xpg",
"gmy",
"rge",
"cpg",
"pnt",
"yms",
"khw",
"san",
"gwt",
"sts",
"nli",
"bhu",
"keq",
"nhh",
"ksy",
"lbm",
"tnv",
"kfv",
"nag",
"rjs",
"key",
"lah",
"pnb",
"hno",
"hnd",
"phj",
"xhe",
"luv",
"sbn",
"lss",
"kfu",
"gom",
"omr",
"smv",
"vah",
"anr",
"raj",
"dub",
"gjk",
"vgr",
"kxp",
"wry",
"jnd",
"hoj",
"gda",
"gdx",
"rwr",
"bhe",
"gig",
"lmn",
"mve",
"kvx",
"bge",
"duh",
"gbl",
"mke",
"vaa",
"wbr",
"gas",
"gra",
"bhi",
"rtw",
"noi",
"dty",
"jns",
"mjl",
"bht",
"kfs",
"cdh",
"pgg",
"cdj",
"bhd",
"lhl",
"kfx",
"bfz",
"dhn",
"khn",
"pli",
"anp",
"hns",
"xis",
"kyw",
"tdb",
"sdr",
"sck",
"thr",
"the",
"tkt",
"thq",
"thl",
"soi",
"tkb",
"mjz",
"smm",
"kra",
"dry",
"dwz",
"pwr",
"sgj",
"dmk",
"rmn",
"rml",
"rmq",
"rmf",
"bra",
"bjj",
"bha",
"bns",
"hca",
"hif",
"hin",
"urd",
"ghr",
"ggg",
"odk",
"hkh",
"wsv",
"mvy",
"clh",
"gwf",
"nlm",
"tra",
"bkk",
"scl",
"plk",
"ush",
"sdg",
"div",
"ved",
"ave",
"bgp",
"ktl",
"bcc",
"bgn",
"rdb",
"srz",
"gzi",
"ntz",
"soj",
"nyq",
"lsa",
"sgr",
"sqo",
"kur",
"ckb",
"kmr",
"sdh",
"zza",
"hac",
"bjm",
"sdf",
"xkc",
"vmh",
"xkj",
"xkp",
"tov",
"hrz",
"avd",
"esh",
"rat",
"tks",
"atn",
"vaf",
"oos",
"yai",
"yah",
"oru",
"prc",
"wne",
"pst",
"pbu",
"pbt",
"kho",
"xtq",
"peo",
"pal",
"zum",
"jdt",
"ttt",
"jpr",
"aiq",
"prs",
"haz",
"bhh",
"lrl",
"def",
"lrc",
"bqi",
"luz",
"ask",
"xvi",
"trm",
"xfa",
"lat",
"ruo",
"ruq",
"itk",
"sdc",
"rgn",
"pms",
"fro",
"frc",
"rcf",
"cks",
"hat",
"gcr",
"acf",
"gcf",
"scf",
"mfe",
"crs",
"frp",
"osp",
"lad",
"pln",
"cbk",
"tmg",
"fax",
"aoa",
"pre",
"cri",
"mzs",
"tvy",
"kea",
"pap",
"pov",
"mxi",
"sdn",
"sro",
"src",
"osc",
"xum",
"xhr",
"umc",
"pgn",
"xvs",
"sbv",
"spx",
"xae",
"ims",
"xvo",
"xto",
"txb",
"xdc",
"xls",
"cms",
"txh",
"irn",
"lre",
"sqn",
"ntw",
"wdt",
"amg",
"ilg",
"ibd",
"ojp",
"kzg",
"okn",
"tkn",
"ryn",
"ams",
"ryu",
"mvi",
"anq",
"oon",
"acu",
"hub",
"kec",
"tey",
"kgo",
"tbr",
"kcp",
"xtc",
"mbr",
"vkm",
"awi",
"oge",
"jge",
"xat",
"kiq",
"alc",
"kbx",
"kee",
"kjq",
"kqz",
"xii",
"shg",
"tyu",
"xuu",
"nhr",
"pie",
"lax",
"tix",
"bcf",
"kiw",
"kjd",
"kmx",
"kxz",
"mdb",
"mcq",
"aom",
"nvm",
"bbb",
"bdf",
"kpx",
"kbk",
"kqi",
"nqm",
"kig",
"udu",
"jje",
"aja",
"bjw",
"hwa",
"btg",
"kyf",
"bev",
"god",
"bet",
"ney",
"gud",
"dic",
"kwp",
"blh",
"ahm",
"ahi",
"grj",
"gbo",
"gry",
"grv",
"gec",
"pye",
"ktj",
"ted",
"dee",
"ggb",
"tja",
"nwb",
"das",
"glr",
"oub",
"krn",
"krw",
"gxx",
"wec",
"big",
"kup",
"wer",
"mfw",
"huf",
"ksj",
"srl",
"bqb",
"xau",
"tip",
"air",
"kwo",
"huc",
"awr",
"rac",
"spi",
"duv",
"dbf",
"tty",
"tds",
"tcq",
"kkb",
"pas",
"tad",
"fau",
"owi",
"amm",
"nax",
"niw",
"bpw",
"xkw",
"lpe",
"rmh",
"wux",
"can",
"yee",
"xop",
"mtf",
"byz",
"ado",
"grq",
"aki",
"anj",
"brq",
"rmk",
"igg",
"xoi",
"aod",
"tbs",
"tgu",
"gai",
"aya",
"bqs",
"wax",
"mdg",
"sbj",
"kth",
"mde",
"kie",
"rou",
"kgw",
"mjd",
"nmu",
"vmv",
"luf",
"mze",
"bwk",
"mnu",
"zrs",
"etz",
"bqc",
"bus",
"bqp",
"sho",
"stj",
"sym",
"sbd",
"lda",
"neb",
"goa",
"yre",
"xgb",
"moa",
"bxl",
"lig",
"tjn",
"bof",
"rkm",
"emk",
"mku",
"mzj",
"msc",
"mxx",
"jod",
"jud",
"kfo",
"kga",
"mnk",
"xkg",
"mwk",
"jad",
"mlq",
"kao",
"kke",
"knk",
"llc",
"kno",
"yal",
"gkp",
"knu",
"xpe",
"lom",
"tod",
"bza",
"men",
"bbo",
"bwq",
"sos",
"bxw",
"dux",
"dnn",
"cpo",
"bze",
"boo",
"boz",
"skq",
"mpc",
"alh",
"mec",
"wnd",
"djj",
"bvr",
"kqc",
"mds",
"hoz",
"sze",
"mhg",
"mca",
"crt",
"crq",
"mtp",
"wlv",
"mzh",
"kek",
"usp",
"quv",
"qum",
"tzj",
"ckz",
"quc",
"poc",
"poh",
"agu",
"ixl",
"ttc",
"emy",
"ctu",
"chf",
"caa",
"toj",
"mhc",
"jac",
"kjb",
"itz",
"mop",
"nug",
"nji",
"wmb",
"miq",
"ccr",
"mtn",
"yan",
"ulw",
"krb",
"pmw",
"csm",
"nsq",
"skd",
"csi",
"lmw",
"plo",
"pos",
"mto",
"mxp",
"mco",
"mir",
"mzl",
"mxq",
"neq",
"zoh",
"zoc",
"zos",
"zor",
"poi",
"zoq",
"poq",
"yec",
"gjr",
"mue",
"kdw",
"mso",
"zkt",
"mhj",
"bua",
"mon",
"bxu",
"bxm",
"bxr",
"khk",
"mvf",
"xal",
"yuy",
"sce",
"kxs",
"mxk",
"kxq",
"krz",
"jei",
"nkm",
"ncm",
"nex",
"nqn",
"nmx",
"mxw",
"stk",
"bow",
"tci",
"mus",
"mik",
"xap",
"mbj",
"kwa",
"yab",
"kpt",
"xag",
"sae",
"nab",
"wmd",
"lkd",
"ltn",
"xtw",
"naa",
"tlg",
"acz",
"tqr",
"bzf",
"nud",
"abt",
"wos",
"mle",
"kxt",
"spk",
"bry",
"gbf",
"sdk",
"keo",
"mqu",
"ukv",
"imt",
"lgo",
"lqr",
"oie",
"nsg",
"mas",
"kdj",
"nnj",
"kln",
"sgc",
"niq",
"enb",
"pko",
"oki",
"bdi",
"jum",
"mfz",
"dip",
"diw",
"dik",
"dib",
"dks",
"anu",
"bxb",
"lwo",
"thu",
"ach",
"adh",
"luo",
"kdi",
"laj",
"kja",
"grs",
"kmt",
"tby",
"gbi",
"mqo",
"kax",
"pgu",
"tlb",
"tuj",
"ibu",
"saj",
"wli",
"tvo",
"roo",
"onw",
"mei",
"brk",
"drb",
"kdu",
"elh",
"kko",
"wll",
"xeu",
"opo",
"oro",
"bey",
"lkl",
"uri",
"wmo",
"avt",
"elk",
"ong",
"urt",
"aon",
"aah",
"ape",
"ymb",
"eit",
"xbi",
"aur",
"bvn",
"but",
"kms",
"urx",
"niz",
"yll",
"aof",
"aag",
"ygl",
"ymo",
"yde",
"gnu",
"stf",
"sbi",
"okk",
"osu",
"oin",
"onk",
"aun",
"onr",
"aif",
"yyu",
"yis",
"ghs",
"ykr",
"sue",
"zia",
"bhg",
"nou",
"dgx",
"gcn",
"kpr",
"aez",
"hkk",
"okv",
"kgq",
"xse",
"cns",
"asy",
"txt",
"diy",
"tml",
"asi",
"psa",
"awy",
"yir",
"aws",
"ahh",
"awu",
"ktt",
"wms",
"aax",
"bwp",
"tyn",
"wng",
"saw",
"kzv",
"opk",
"aip",
"kwr",
"kti",
"kts",
"bhl",
"fai",
"stm",
"tlf",
"tif",
"urm",
"mpt",
"sug",
"nkj",
"tkx",
"imo",
"ubu",
"mux",
"med",
"mbw",
"gam",
"nac",
"cjv",
"nof",
"gvf",
"sst",
"whg",
"wgi",
"nbq",
"wno",
"dnt",
"hap",
"dni",
"dna",
"wlw",
"ndx",
"yli",
"nlk",
"yac",
"enq",
"ipi",
"kyc",
"leq",
"mme",
"asj",
"bir",
"net",
"hui",
"ssx",
"akh",
"aoe",
"kew",
"kjs",
"kjy",
"mpv",
"nop",
"nif",
"noc",
"fag",
"mhf",
"nis",
"skc",
"nkg",
"nej",
"ufi",
"nnf",
"klt",
"smc",
"klh",
"yuw",
"iou",
"awx",
"frq",
"dge",
"mtv",
"bmp",
"gka",
"ygm",
"nnk",
"mjn",
"bop",
"yut",
"ytw",
"ons",
"slw",
"kqb",
"sej",
"kmg",
"mlh",
"mpp",
"msz",
"noh",
"kco",
"kuo",
"tim",
"spl",
"mci",
"naf",
"ded",
"tbv",
"gaf",
"for",
"gim",
"aso",
"zuh",
"bef",
"snp",
"yby",
"ino",
"kbq",
"kmu",
"kyg",
"ygr",
"abg",
"isa",
"usa",
"awb",
"agd",
"gaj",
"tbg",
"omw",
"waj",
"kyy",
"gat",
"ali",
"koz",
"wsk",
"tnh",
"ped",
"pla",
"bie",
"mvq",
"xow",
"mjj",
"ybm",
"ukg",
"yrw",
"kmf",
"gmu",
"bbd",
"igo",
"pnr",
"bmx",
"gap",
"gyb",
"rmp",
"ydk",
"bpi",
"mcz",
"sra",
"xsp",
"utu",
"mqe",
"nbk",
"rpt",
"mqv",
"mqw",
"swm",
"wmc",
"mtc",
"kpw",
"kmh",
"taw",
"wdg",
"pda",
"msx",
"xes",
"ssj",
"awm",
"lei",
"pup",
"ssd",
"bpu",
"mdc",
"jil",
"rea",
"ynl",
"dnr",
"urg",
"bpm",
"gsp",
"ggl",
"spd",
"ybo",
"eip",
"mtg",
"kpq",
"kkl",
"nps",
"mnz",
"wod",
"auu",
"daz",
"opy",
"kqq",
"acs",
"xkr",
"xav",
"xer",
"xok",
"zkp",
"txu",
"xra",
"pth",
"xxr",
"aft",
"nyi",
"wwr",
"xnm",
"dyd",
"ywr",
"nmp",
"bcj",
"djw",
"dyb",
"nyv",
"azm",
"azg",
"cux",
"cut",
"mbz",
"mix",
"mxb",
"mxa",
"mks",
"mih",
"vmj",
"mxt",
"mjc",
"mtu",
"mio",
"mza",
"xtd",
"vmm",
"mil",
"mqh",
"mxs",
"xtp",
"xts",
"vmx",
"mab",
"mim",
"xta",
"mxv",
"xty",
"mip",
"mxy",
"vmq",
"miz",
"xtu",
"mtx",
"miu",
"xtb",
"mii",
"mit",
"miy",
"vmc",
"jmx",
"mib",
"mce",
"xtm",
"xtn",
"mie",
"xtj",
"mig",
"mdv",
"xti",
"meh",
"xtl",
"mpm",
"mvg",
"trs",
"trc",
"trq",
"coz",
"pbe",
"poe",
"pps",
"pbf",
"pow",
"pca",
"vmp",
"maa",
"maq",
"maj",
"vmy",
"mzi",
"mau",
"vmz",
"zap",
"czn",
"cta",
"cly",
"cya",
"ctp",
"ctz",
"zoo",
"zaf",
"zpy",
"zaw",
"zpf",
"ztn",
"zas",
"ztt",
"ztl",
"zpi",
"zpr",
"zax",
"ztg",
"zpm",
"zpg",
"zpe",
"zpa",
"zpj",
"zpv",
"ztu",
"zab",
"zai",
"zac",
"ztx",
"zpn",
"zts",
"zpb",
"ztp",
"zao",
"ztm",
"zpc",
"zad",
"zat",
"zpu",
"zav",
"zpq",
"zar",
"zty",
"zcd",
"zsr",
"zaq",
"zaa",
"zpd",
"zae",
"zca",
"zpo",
"zpk",
"zpt",
"zps",
"zpx",
"zte",
"zpz",
"zpw",
"zph",
"zpp",
"zpl",
"chj",
"cso",
"cuc",
"csa",
"ctl",
"cpa",
"cnt",
"chz",
"cvn",
"cnl",
"cle",
"cte",
"cco",
"chq",
"pei",
"ocu",
"mat",
"maz",
"mmc",
"otm",
"otn",
"otx",
"ote",
"otq",
"otz",
"otl",
"ots",
"ott",
"pbs",
"pmq",
"pmz",
"cip",
"sut",
"tpc",
"tcf",
"tpx",
"tpl",
"idi",
"atw",
"dbl",
"mwp",
"gbb",
"axl",
"aly",
"adg",
"amx",
"aer",
"are",
"axe",
"wgu",
"bjb",
"gvy",
"nnr",
"nwo",
"jui",
"nnv",
"wrm",
"mem",
"nna",
"wbp",
"wrl",
"wmt",
"gue",
"dmw",
"ddj",
"rxd",
"mpj",
"kux",
"piu",
"ntj",
"pjt",
"kdd",
"ant",
"ktd",
"jan",
"yxg",
"xbe",
"yub",
"ktg",
"ylr",
"yda",
"bzr",
"gnl",
"gdc",
"gyf",
"gwu",
"kgl",
"zmk",
"wdu",
"xyb",
"gyy",
"zmc",
"xpt",
"xwk",
"bxi",
"dif",
"nmv",
"yry",
"ynd",
"yww",
"hrp",
"ard",
"pit",
"xpa",
"dyn",
"nyx",
"jao",
"xtv",
"wga",
"yil",
"nyt",
"ljx",
"ggd",
"ikr",
"tgz",
"typ",
"pkn",
"wua",
"kbe",
"kuy",
"umd",
"fln",
"wie",
"wih",
"wij",
"wim",
"uwa",
"ugb",
"xmp",
"wik",
"lby",
"xmy",
"nxn",
"xyt",
"xyj",
"xyk",
"wnn",
"mvl",
"nlw",
"xut",
"aea",
"yxm",
"awg",
"gwm",
"dgt",
"xgd",
"amz",
"avm",
"aid",
"xpj",
"kkp",
"uky",
"bjy",
"xgm",
"gmr",
"yia",
"nha",
"bia",
"vml",
"wbv",
"lkm",
"nju",
"kba",
"xbp",
"xgg",
"pnj",
"xwj",
"wxw",
"bxj",
"pnv",
"bxn",
"dhl",
"dze",
"iin",
"dhr",
"wri",
"nhf",
"tju",
"vka",
"nrl",
"ywg",
"vku",
"yij",
"nrk",
"nly",
"bdy",
"zmu",
"nbn",
"awk",
"kda",
"xbj",
"xrd",
"xul",
"dhu",
"xjt",
"xni",
"kgs",
"xya",
"gnr",
"dhx",
"wkw",
"wlu",
"ddr",
"pmd",
"yxy",
"wth",
"llj",
"dmd",
"rnr",
"xwd",
"xwt",
"weg",
"dgw",
"wyi",
"xbg",
"dda",
"xth",
"yga",
"wdk",
"yxl",
"kky",
"djf",
"gvn",
"vmu",
"dax",
"dhg",
"djr",
"guf",
"dwu",
"gnn",
"dwy",
"djb",
"dji",
"lja",
"jay",
"cbr",
"ktx",
"tux",
"cao",
"kuq",
"pcp",
"pno",
"sni",
"kaq",
"shp",
"amc",
"cbs",
"swo",
"mcd",
"yaa",
"ywn",
"mts",
"atc",
"mzr",
"knt",
"isc",
"nuc",
"pyn",
"mpq",
"xor",
"xpk",
"cav",
"tna",
"aro",
"tno",
"enr",
"yuj",
"wfg",
"dmu",
"ttn",
"pnn",
"nef",
"mod",
"dep",
"cpi",
"tas",
"bxo",
"gib",
"bpl",
"hmo",
"njt",
"fng",
"pom",
"poo",
"pej",
"peq",
"prr",
"qvp",
"qvl",
"qxa",
"qub",
"qvm",
"qxh",
"qvh",
"qwh",
"qxn",
"qxo",
"qwa",
"qws",
"qvw",
"qxw",
"qva",
"qvn",
"qxt",
"qvc",
"quf",
"qwc",
"quk",
"qvs",
"qxu",
"quy",
"qul",
"qus",
"quh",
"qud",
"qxl",
"qvj",
"qxr",
"qvi",
"qvo",
"quw",
"qvz",
"qup",
"quz",
"qve",
"qxp",
"qxc",
"qux",
"ras",
"tqn",
"uma",
"byt",
"kgf",
"kbl",
"txj",
"krt",
"knc",
"bms",
"kby",
"dzg",
"tuq",
"blc",
"hur",
"sec",
"str",
"slh",
"ska",
"sno",
"clm",
"cow",
"col",
"fla",
"spo",
"slc",
"wpc",
"kbv",
"nxx",
"set",
"aau",
"aad",
"iwm",
"cjn",
"wog",
"kmo",
"kwj",
"sim",
"kmn",
"xrw",
"bye",
"ayq",
"psq",
"nux",
"bjh",
"bnw",
"mbx",
"siv",
"dju",
"amp",
"knr",
"sny",
"ham",
"gbe",
"pin",
"akq",
"nnm",
"sht",
"aen",
"asw",
"mzg",
"psd",
"afg",
"sqk",
"aed",
"csx",
"gsm",
"hsl",
"mdl",
"lsy",
"mzy",
"ncs",
"psg",
"sqs",
"tza",
"lsn",
"tsm",
"zsl",
"zib",
"esl",
"lbs",
"sdl",
"nsr",
"bfi",
"nzs",
"asf",
"pgz",
"nbs",
"sfs",
"csg",
"pys",
"ugy",
"hab",
"hos",
"csl",
"gsg",
"isr",
"pso",
"sgg",
"nsp",
"ins",
"pks",
"jsl",
"kvk",
"tss",
"asp",
"asq",
"bzs",
"eso",
"fsl",
"gss",
"isg",
"lsl",
"mfs",
"psp",
"ssr",
"doq",
"eth",
"gse",
"gus",
"xms",
"psl",
"fcs",
"esn",
"sgx",
"tsq",
"lst",
"ase",
"jls",
"csr",
"hds",
"lsp",
"xml",
"kgi",
"cds",
"nsi",
"rsn",
"ugn",
"bvl",
"csn",
"ecs",
"prl",
"csc",
"vsv",
"bqn",
"cse",
"hsh",
"rms",
"svk",
"dse",
"sfb",
"vgt",
"ise",
"slf",
"tse",
"dsl",
"icl",
"mzc",
"nsl",
"ysl",
"haf",
"csd",
"lls",
"vsi",
"msr",
"ukl",
"rsl",
"ssp",
"vsl",
"psr",
"swl",
"fss",
"fse",
"csf",
"ils",
"ads",
"lsc",
"syy",
"bfk",
"rib",
"rnb",
"gds",
"iks",
"jcs",
"jhs",
"jus",
"dsz",
"mre",
"rsm",
"ehs",
"okl",
"lsw",
"lsv",
"szs",
"tsy",
"uks",
"msd",
"prz",
"ole",
"dka",
"dzl",
"tgf",
"kjz",
"xkf",
"xkz",
"xct",
"zau",
"prx",
"bod",
"hut",
"lhm",
"ola",
"dre",
"tcn",
"ttz",
"kgy",
"muk",
"jul",
"nao",
"khg",
"tsk",
"nes",
"sbu",
"jda",
"spt",
"sgt",
"cgk",
"gro",
"dzo",
"lya",
"luk",
"kbg",
"adx",
"kzq",
"ghh",
"ghe",
"tge",
"skj",
"gvr",
"npa",
"chx",
"taj",
"tdg",
"rnp",
"rgk",
"cdn",
"bee",
"xns",
"tpq",
"jna",
"scu",
"lae",
"kkf",
"tsj",
"trp",
"ria",
"tpe",
"usi",
"xac",
"aot",
"kdq",
"ruh",
"ckh",
"zkd",
"tcl",
"nbc",
"nbe",
"nph",
"nnp",
"kix",
"lzn",
"umn",
"njb",
"tvt",
"ugo",
"hpo",
"mhx",
"bxd",
"tco",
"dnv",
"int",
"obr",
"tvn",
"rmz",
"yip",
"phq",
"bzi",
"lwm",
"pyy",
"cnc",
"how",
"byo",
"enu",
"ktp",
"aeu",
"ahk",
"ycp",
"ymd",
"slt",
"jiy",
"jiu",
"lkc",
"lhi",
"kaf",
"ysd",
"lwu",
"yiq",
"ylm",
"ymh",
"ysg",
"yku",
"ykn",
"yik",
"ywl",
"ywt",
"yit",
"llh",
"ylo",
"lgh",
"ytp",
"ymq",
"ybk",
"ypm",
"ymx",
"ymc",
"ypn",
"ypb",
"yhl",
"ykl",
"yzk",
"nsd",
"nos",
"yiv",
"iii",
"ygp",
"smh",
"ysy",
"ywq",
"yyz",
"ych",
"ywu",
"yig",
"yna",
"yif",
"aub",
"ypp",
"ypz",
"ypa",
"ypo",
"aza",
"yix",
"yiz",
"yso",
"nuf",
"zal",
"ers",
"nru",
"qvy",
"pmi",
"pmj",
"qxs",
"tji",
"tjs",
"txo",
"lep",
"lhp",
"drq",
"kgj",
"kip",
"kif",
"kjl",
"mgp",
"mrd",
"raq",
"rav",
"cuw",
"kle",
"ncd",
"rab",
"raa",
"wly",
"cur",
"aph",
"byw",
"lbr",
"lrr",
"ybi",
"emg",
"raf",
"jee",
"bhj",
"vay",
"dus",
"brd",
"jkm",
"kvq",
"kxf",
"kvy",
"eky",
"kyu",
"ghk",
"kvu",
"blk",
"kjp",
"pwo",
"kjt",
"pww",
"jkp",
"wea",
"bgg",
"mni",
"nkh",
"njm",
"nri",
"nbi",
"pmx",
"nnl",
"npo",
"nre",
"nsm",
"njo",
"njh",
"nsa",
"pzn",
"yim",
"lpn",
"jmn",
"ajz",
"bgr",
"cbl",
"cfm",
"biu",
"dln",
"hmr",
"sez",
"czt",
"mrh",
"shl",
"aim",
"anm",
"kmm",
"nmh",
"rnl",
"cek",
"cnk",
"cnw",
"zom",
"gnb",
"vap",
"kfw",
"pck",
"pub",
"ral",
"ctd",
"tcz",
"csh",
"csv",
"cnb",
"dao",
"ckn",
"mwq",
"nng",
"nma",
"nbu",
"nki",
"njn",
"nme",
"nzm",
"adl",
"nbt",
"tgj",
"bca",
"bfs",
"mro",
"duu",
"rji",
"rau",
"jnl",
"och",
"wxa",
"lzh",
"gan",
"hak",
"hsn",
"cjy",
"cmn",
"wuh",
"wuu",
"yue",
"cdo",
"cpx",
"mnp",
"czo",
"oma",
"iow",
"ofo",
"uni",
"suo",
"pux",
"rwa",
"wmx",
"vam",
"mmb",
"mqf",
"hmb",
"ses",
"tst",
"ddn",
"khq",
"dsq",
"uka",
"xod",
"bzp",
"jbj",
"dim",
"aiw",
"gyl",
"amf",
"kxh",
"uis",
"smz",
"nas",
"lni",
"kqj",
"lbi",
"rmi",
"ngm",
"rmd",
"rmu",
"rmg",
"sth",
"caw",
"cmt",
"sui",
"ggw",
"aac",
"wrv",
"xwg",
"mym",
"muz",
"mur",
"tex",
"did",
"loh",
"cuq",
"lic",
"yzg",
"enc",
"yln",
"yha",
"lha",
"aou",
"gir",
"gqu",
"lbt",
"lwh",
"onb",
"zgm",
"nut",
"tys",
"khb",
"tyt",
"tpo",
"nyw",
"tyj",
"thi",
"ksu",
"try",
"tdd",
"tiz",
"pdi",
"tmm",
"tts",
"yoy",
"zzj",
"zch",
"zeh",
"zgn",
"zgb",
"zln",
"zlj",
"zlq",
"zqe",
"tnu",
"tsl",
"zyj",
"zyn",
"zyb",
"mlm",
"kmc",
"cov",
"doc",
"tct",
"aih",
"mkg",
"cdy",
"mmd",
"lbc",
"mgb",
"sjg",
"tma",
"gcd",
"gyd",
"tsz",
"pua",
"tuh",
"mps",
"ppo",
"chd",
"clo",
"bfn",
"swt",
"kvd",
"woi",
"adn",
"hmu",
"klz",
"jka",
"twg",
"nec",
"ddg",
"oia",
"ury",
"bkl",
"itx",
"kwt",
"mqr",
"mrx",
"bnv",
"dbe",
"jbr",
"kdy",
"vto",
"tee",
"tpp",
"tpt",
"tlc",
"top",
"toc",
"tos",
"too",
"tcw",
"tku",
"bao",
"yui",
"arj",
"ynu",
"ten",
"mcl",
"ude",
"oaa",
"juc",
"nco",
"orh",
"kpn",
"ait",
"ktn",
"mav",
"awe",
"kay",
"xet",
"nhd",
"gug",
"gnw",
"tpj",
"jor",
"yuq",
"yrl",
"tpn",
"cod",
"omg",
"pog",
"tpk",
"asn",
"ama",
"aan",
"awt",
"taf",
"pak",
"mdz",
"asu",
"twt",
"gub",
"jua",
"paf",
"wir",
"pah",
"api",
"kgm",
"kyz",
"adw",
"urz",
"urb",
"oym",
"sru",
"cin",
"gvo",
"kyr",
"myu",
"pur",
"arr",
"uru",
"mpu",
"aqz",
"tpr",
"jur",
"xiy",
"msp",
"jbk",
"jmw",
"xbo",
"tyv",
"aib",
"ybe",
"uig",
"uzn",
"kir",
"kaa",
"xpc",
"krc",
"qxq",
"slq",
"azj",
"azb",
"giy",
"wma",
"vms",
"pax",
"rer",
"std",
"tme",
"tka",
"waf",
"wsu",
"woy",
"avo",
"aga",
"hir",
"dek",
"dbv",
"esm",
"kce",
"ruy",
"nsc",
"ksa",
"kku",
"kch",
"ays",
"dyg",
"agi",
"nbg",
"pch",
"bdz",
"znk",
"ygu",
"apv",
"xyl",
"wif",
"pig",
"wai",
"xmo",
"tkf",
"nrx",
"bfr",
"xcc",
"xly",
"ecr",
"ecy",
"gic",
"hvc",
"xil",
"xai",
"xpn",
"kzw",
"ktq",
"zkg",
"xle",
"omn",
"nrp",
"nxm",
"pkc",
"xpi",
"pij",
"pld",
"quq",
"xrr",
"txr",
"trl",
"uam",
"urp",
"wwb",
"liv",
"olo",
"lud",
"fkv",
"mvh",
"mhr",
"mrj",
"kpv",
"koi",
"yrk",
"enf",
"enh",
"sel",
"par",
"ute",
"mnr",
"pao",
"tbu",
"mfy",
"azz",
"nhq",
"nhy",
"nht",
"ppl",
"nch",
"nhe",
"nhw",
"nhk",
"nhp",
"nhx",
"nhc",
"nlv",
"ncx",
"nhz",
"nsu",
"nhi",
"nhn",
"nci",
"nhm",
"ncj",
"nhg",
"xpo",
"nhv",
"naz",
"nuz",
"ncl",
"azd",
"azn",
"crn",
"cok",
"tar",
"tac",
"thh",
"twr",
"tcu",
"ood",
"ntp",
"stp",
"tla",
"tep",
"hei",
"tww",
"ybx",
"wla",
"ppq",
"mxn",
"sbg",
"kzz",
"msg",
"zmm",
"zmt",
"zmg",
"zmj",
"zmd",
"zmy",
"xru",
"zmr",
"amy",
"zma",
"wil",
"wub",
"gma",
"gww",
"vmi",
"xgu",
"wro",
"xud",
"xun",
"jbw",
"dgn",
"wrr",
"jng",
"bjc",
"yrb",
"yva",
"xrn",
"xpm",
"cga",
"mvk",
"bwm",
"buv",
"ykg",
"xcv",
"wao",
"ayo",
"anb",
"cah",
"iqu",
"avs",
"zro",
"aab",
"aaq",
"aas",
"abd",
"abe",
"abk",
"abp",
"ace",
"acm",
"adb",
"add",
"adi",
"aee",
"afe",
"afk",
"agv",
"ain",
"ajn",
"ajs",
"als",
"alw",
"alx",
"anl",
"aol",
"apf",
"apo",
"arc",
"arx",
"asg",
"ash",
"ate",
"ato",
"ava",
"awv",
"aww",
"axx",
"ayd",
"ayt",
"ayz",
"bab",
"bal",
"bcg",
"bck",
"bcl",
"bcr",
"bcz",
"bdj",
"beg",
"bei",
"bfc",
"bfu",
"bgf",
"bgl",
"bgx",
"bhn",
"biz",
"bjg",
"bjv",
"bkd",
"bks",
"bkw",
"bmj",
"bmu",
"bnr",
"bog",
"bok",
"bor",
"bpa",
"bpp",
"bpy",
"bql",
"bqm",
"bqy",
"brx",
"brz",
"bsh",
"buq",
"bva",
"bvv",
"bwi",
"bxa",
"bxe",
"bxz",
"byk",
"bym",
"bzv",
"bzx",
"cas",
"cbi",
"cbq",
"cbv",
"ccd",
"cdr",
"cet",
"chh",
"chm",
"chn",
"ckm",
"ckt",
"cky",
"clc",
"clk",
"clt",
"cmg",
"cmm",
"cmr",
"cnp",
"cnu",
"cnx",
"cof",
"cry",
"csk",
"csp",
"csq",
"css",
"cst",
"csy",
"csz",
"cth",
"ctn",
"cts",
"cty",
"cvg",
"czh",
"czk",
"dbu",
"dcc",
"ddi",
"ddo",
"del",
"den",
"dga",
"dgc",
"dgl",
"dgo",
"dho",
"dhw",
"dih",
"diq",
"diu",
"dja",
"djd",
"djk",
"dmf",
"dmm",
"dmo",
"dny",
"doi",
"dri",
"dsi",
"dta",
"dth",
"dtk",
"dtn",
"duk",
"dum",
"duz",
"dyy",
"eaa",
"ebo",
"egl",
"ekk",
"ell",
"eme",
"emq",
"enm",
"esk",
"esu",
"etc",
"eto",
"fab",
"faj",
"fap",
"fat",
"fay",
"fbl",
"fit",
"flh",
"fly",
"fnb",
"fpe",
"frm",
"frs",
"frt",
"ful",
"fuv",
"gae",
"gal",
"gba",
"gbd",
"gbg",
"gbu",
"gbw",
"gdh",
"gdo",
"gdt",
"gek",
"gel",
"gev",
"gge",
"ggu",
"gha",
"ghl",
"ght",
"gia",
"gie",
"gih",
"gin",
"giq",
"giu",
"giw",
"gjm",
"gkd",
"gku",
"glb",
"glh",
"gll",
"gmg",
"gmh",
"gmz",
"gnk",
"goz",
"gqn",
"grc",
"grr",
"gsn",
"gsw",
"gtu",
"gup",
"gva",
"gvc",
"gvp",
"gwd",
"gwj",
"hba",
"hbs",
"hed",
"hem",
"hgm",
"hhr",
"hhy",
"hio",
"hks",
"hlt",
"hmd",
"hmk",
"hmz",
"hnh",
"hov",
"hps",
"hrt",
"htx",
"hue",
"hum",
"huv",
"hve",
"hvn",
"hvv",
"icr",
"idb",
"ify",
"ihb",
"ihw",
"iku",
"ilm",
"ilp",
"inb",
"inj",
"inl",
"ipk",
"ire",
"izz",
"jaa",
"jat",
"jbi",
"jbt",
"jek",
"jgk",
"jid",
"jih",
"jiq",
"jkr",
"jks",
"jog",
"jos",
"jrb",
"jup",
"kac",
"kbp",
"kcd",
"kcx",
"kfi",
"kfr",
"kgn",
"khd",
"khv",
"khy",
"kim",
"kit",
"kiu",
"kjj",
"kjo",
"kjv",
"kkq",
"kld",
"klg",
"klm",
"kmd",
"kmq",
"kmv",
"kmz",
"knd",
"kng",
"knj",
"knm",
"knn",
"knw",
"kod",
"koe",
"kok",
"kow",
"kqd",
"kqo",
"krj",
"krs",
"ksc",
"ksi",
"ktz",
"kue",
"kvz",
"kwb",
"kwk",
"kwl",
"kxk",
"kxo",
"kxr",
"kyl",
"kyo",
"laa",
"lab",
"lay",
"lbl",
"lbn",
"ldb",
"lev",
"lez",
"lgk",
"lgn",
"lhs",
"lie",
"lik",
"lin",
"lir",
"ljw",
"lku",
"lme",
"lmf",
"lng",
"lnj",
"lnm",
"lnn",
"lnw",
"lou",
"loy",
"lro",
"lsb",
"lsh",
"ltc",
"lth",
"ltz",
"lui",
"lus",
"lut",
"lvi",
"lvu",
"lxm",
"lyg",
"man",
"mbm",
"mch",
"mcm",
"mcu",
"mcv",
"mdh",
"mep",
"mev",
"mfg",
"mga",
"mgs",
"mgt",
"mhn",
"mhu",
"mis",
"mjb",
"mjg",
"mjy",
"mkr",
"mkx",
"mkz",
"mlg",
"mlv",
"mlx",
"mlz",
"mmf",
"mmi",
"mmq",
"mnx",
"moe",
"mpb",
"mpw",
"mpx",
"mqz",
"mrb",
"msa",
"mte",
"mtm",
"mul",
"mwf",
"mwi",
"mwr",
"mxj",
"mzk",
"mzu",
"nam",
"nat",
"nay",
"nbd",
"nbj",
"nbl",
"nck",
"nct",
"nde",
"ndf",
"neh",
"nei",
"nep",
"new",
"nfl",
"nfr",
"nfu",
"nga",
"ngk",
"ngq",
"ngr",
"ngt",
"ngu",
"nib",
"niv",
"njs",
"njz",
"nkb",
"nlo",
"nlx",
"nmf",
"nmm",
"nmn",
"nmo",
"nny",
"npi",
"npx",
"nqg",
"nqq",
"nrf",
"nrt",
"nsb",
"nsf",
"nst",
"ntg",
"ntk",
"ntx",
"nua",
"nun",
"nwc",
"nwg",
"nwx",
"nwy",
"nxk",
"nyh",
"nys",
"nzz",
"oav",
"oci",
"ocm",
"oht",
"ohu",
"ojv",
"okc",
"okh",
"okm",
"oko",
"omk",
"omp",
"onx",
"oog",
"opt",
"ori",
"ort",
"osn",
"ota",
"otb",
"oua",
"oue",
"oui",
"pad",
"pan",
"pav",
"pbh",
"pbm",
"pby",
"pcj",
"pdu",
"pef",
"pep",
"pes",
"pfe",
"pfl",
"pga",
"pgd",
"pgl",
"phl",
"phr",
"pir",
"piv",
"pka",
"pkh",
"plj",
"pls",
"pmh",
"pmk",
"pml",
"pmr",
"png",
"pnw",
"pop",
"prg",
"prk",
"prn",
"pro",
"prt",
"psc",
"psh",
"psi",
"psm",
"psu",
"pti",
"puo",
"pus",
"pyx",
"que",
"qug",
"qur",
"qwm",
"qwt",
"qyp",
"ram",
"rar",
"ray",
"rbk",
"rbl",
"rem",
"ret",
"rga",
"rif",
"ril",
"rit",
"rmc",
"rmo",
"rom",
"rrt",
"rsb",
"rts",
"rup",
"rxw",
"rzh",
"sbf",
"sbq",
"sci",
"scp",
"scw",
"scx",
"sdb",
"sde",
"sef",
"seo",
"seq",
"sfm",
"sga",
"sgb",
"sgi",
"sgp",
"shm",
"shv",
"shy",
"sia",
"sjb",
"sjd",
"sje",
"sjk",
"sjl",
"sjt",
"sju",
"skf",
"skg",
"skm",
"sld",
"slz",
"sma",
"sme",
"smj",
"smn",
"sms",
"smu",
"sne",
"sns",
"soe",
"soo",
"sox",
"spg",
"spq",
"sqr",
"sqx",
"sre",
"srv",
"ssq",
"ssv",
"sta",
"stq",
"suq",
"svx",
"swa",
"swh",
"swn",
"sxc",
"sxg",
"sxk",
"sxl",
"sxm",
"sxo",
"tab",
"tbh",
"tcc",
"tcp",
"tdx",
"teg",
"ter",
"tew",
"tfn",
"thd",
"thm",
"tia",
"tiq",
"tjj",
"tjo",
"tjp",
"tlo",
"tlp",
"tlt",
"tmb",
"tmh",
"tmv",
"tnr",
"tnz",
"tpw",
"tqb",
"tqt",
"tro",
"trv",
"tsw",
"ttw",
"twe",
"twf",
"tye",
"tzm",
"ubl",
"uji",
"ukk",
"ulk",
"umg",
"und",
"unn",
"url",
"uss",
"uth",
"vaj",
"van",
"vbk",
"vkp",
"vls",
"vma",
"vmb",
"vmf",
"vnk",
"vnm",
"vwa",
"waa",
"waq",
"wbf",
"wbk",
"wbs",
"wbt",
"wca",
"wdy",
"wei",
"wep",
"weu",
"wew",
"wgg",
"wha",
"whk",
"wig",
"wkr",
"wky",
"wlr",
"wmg",
"wnb",
"woa",
"wob",
"wrb",
"wrg",
"wrw",
"wrx",
"wrz",
"wsi",
"wsr",
"wwo",
"wyb",
"xaj",
"xam",
"xaq",
"xas",
"xbb",
"xbd",
"xby",
"xcb",
"xco",
"xcu",
"xda",
"xdk",
"xeb",
"xeg",
"xep",
"xgf",
"xgi",
"xgl",
"xha",
"xhc",
"xhm",
"xiv",
"xjb",
"xkb",
"xki",
"xkk",
"xlb",
"xlg",
"xli",
"xln",
"xme",
"xmh",
"xmk",
"xmn",
"xnb",
"xng",
"xnj",
"xnk",
"xnq",
"xnt",
"xnu",
"xny",
"xom",
"xpb",
"xpd",
"xpf",
"xph",
"xpl",
"xpp",
"xpv",
"xpw",
"xpx",
"xpy",
"xpz",
"xre",
"xrg",
"xri",
"xrm",
"xrt",
"xsa",
"xsb",
"xsc",
"xsv",
"xtr",
"xtt",
"xvn",
"xwo",
"xxb",
"xxk",
"xzm",
"xzp",
"yaf",
"yak",
"yau",
"ybh",
"ybn",
"yel",
"ygi",
"ygs",
"yhs",
"yii",
"yin",
"ykt",
"yly",
"yok",
"yon",
"yrm",
"yrn",
"yro",
"ysc",
"ysm",
"ysr",
"yta",
"ytl",
"yty",
"yua",
"yug",
"yuz",
"yxa",
"yyr",
"zam",
"zba",
"zbu",
"zha",
"zkb",
"zkh",
"zkn",
"zko",
"zkv",
"zkz",
"zml",
"zne",
"zra",
"zrn",
"zsk",
"ztq",
"zxx",
"zyp"
] | TAGS
#size_categories-1K<n<10K #language-Afade #language-Pará Arára #language-Afar #language-Aka-Bea #language-Abon #language-Abaza #language-Pal #language-Aneme Wake #language-Abui #language-Aka-Cari #language-Aka-Kora #language-Akar-Bale #language-Achang #language-Achi #language-Achumawi #language-Adele #language-Adonara #language-Adnyamathanha #language-Adyghe #language-Haeke #language-Aer #language-Ambakich #language-Amele #language-Andai #language-Akrukay #language-Defaka #language-Eloyi #language-Obokuitai #language-Agatu #language-Angal #language-Angor #language-Ngelima #language-Fembe #language-Tainae #language-Aghem #language-Aguaruna #language-Kahua #language-Aghul #language-Qimant #language-Ahom #language-Ake #language-Aimele #language-Aiton #language-Aka-Jeru #language-Akkadian #language-Aklanon #language-Aka-Bo #language-Siwu #language-Akhvakh #language-Aka-Kede #language-Aka-Kol #language-Alabama #language-Alago #language-Aleut #language-Alege #language-Algonquin #language-Southern Altai #language-Alur #language-Yanesha' #language-Amis #language-Amdang #language-Guerrero Amuzgo #language-Ambelau #language-Andaqui #language-Nend #language-Andi #language-Obolo #language-Andoque #language-Denya #language-Anyin #language-Pemon #language-Angoram #language-Anindilyakwa #language-Mufian #language-Taikat #language-Atorada #language-Uab Meto #language-Apinayé #language-A-Pucikwar #language-Apatani #language-Western Apache #language-Safeyoka #language-Archi #language-Atohwaim #language-Atakapa #language-Angaité #language-Aragonese #language-Arhuaco #language-Arikara #language-Arikapú #language-Arabela #language-Arapaho #language-Arawak #language-Assiniboine #language-Casuarina Coast Asmat #language-Assamese #language-Ipulo #language-Asturian #language-Muratayak #language-Zaiwa #language-Atikamekw #language-Aralle-Tabulahan #language-Reel #language-Northern Altai #language-Arutani #language-Waorani #language-Aguna #language-Aushi #language-Heyo #language-Makayam #language-Anus #language-Aurá #language-Awiyaana #language-Avatime #language-Avá-Canoeiro #language-Awadhi #language-Mato Grosso Arára #language-Ginyanga #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bambara #language-Balinese #language-Bantawa #language-Vengo #language-Barama #language-Babanki #language-Bats #language-Uneapa #language-Bamali #language-Girawa #language-Baba #language-Bannoni #language-Kaluli #language-Bench #language-Budukh #language-Baldemu #language-Bahnar #language-Bokoto #language-Oroko #language-Bodo Parja #language-Baham #language-Budong-Budong #language-Iceve-Maci #language-Beja #language-Belarusian #language-Bengali #language-Blagar #language-Betawi #language-Bari #language-Pauri Bareli #language-Betaf #language-Bofi #language-Blafe #language-Mmen #language-Badaga #language-Balti #language-Bantayanon #language-Bagheli #language-Gwamhi-Wuri #language-Haryanvi #language-Rathwi Bareli #language-Bagri #language-Bhatri #language-Bhili #language-Bhojpuri #language-Bima #language-Buwal #language-Biak #language-Bhele #language-Bissa #language-Bile #language-Nai #language-Bila #language-Berinomo #language-Southern Birifor #language-Budza #language-Burji #language-Binumarien #language-Baruga #language-Beeke #language-Pande #language-Buhid #language-Bekwarra #language-Bokyi #language-Bolango #language-Buol #language-Biloxi #language-Southern Catanduanes Bikol #language-Baluan-Pam #language-Blang #language-Tai Dam #language-Notre #language-Balantak #language-Lame #language-Kein #language-Bagirmi #language-Bomu #language-Muinane #language-Bookan #language-Masiwang #language-Benga #language-Bangi #language-Bunun #language-Bintulu #language-Bora #language-Boma #language-Anjam #language-Bole #language-Berom #language-Bosnian #language-Buamu #language-Bauni #language-Botlikh #language-Orowe #language-Dzao Min #language-Barrow Point #language-Palya Bareli #language-Bilba #language-Baima #language-Bandial #language-Biritai #language-Bamukumbit #language-Koro Wachi #language-Baangi #language-Breton #language-Bira #language-Brahui #language-Brokkat #language-Abinomn #language-Bassari #language-Wushi #language-Bashkardi #language-Bangwinji #language-Basa-Gumna #language-Barasana-Eduria #language-Bassa #language-Yangkam #language-Bata #language-Gamo-Ningi #language-Ratagnon #language-Rinconada Bikol #language-Batak Simalungun #language-Bete-Bendi #language-Batu #language-Bateri #language-Batak Karo #language-Bushi #language-Ntcham #language-Beothuk #language-Buginese #language-Bulgarian #language-Terei #language-Budu #language-Baeggu #language-Belanda Viri #language-Baan #language-Bolgo #language-Bwe Karen #language-Bafaw-Balong #language-Bwa #language-Cwi Bwamu #language-Bebil #language-Bhujel #language-Burak #language-Medumba #language-Qaqet #language-Andio #language-Bribri #language-Mapos Buang #language-Chuj #language-Caddo #language-Nivaclé #language-Kaqchikel #language-Carolinian #language-Chipaya #language-Catalan #language-Chiquitano #language-Cayuga #language-Carapana #language-Carijona #language-Chimila #language-Chayahuita #language-Candoshi-Shapra #language-Carabayo #language-Chamicuro #language-Chopi #language-Atsam #language-Chakma #language-Choni #language-Chenchu #language-Chiru #language-Chodri #language-Chepang #language-Lower Chehalis #language-Cebuano #language-Chamacoco #language-Czech #language-Cara #language-Chamorro #language-Chibcha #language-Catawba #language-Chechen #language-Chagatai #language-Chuukese #language-Cahuilla #language-Choctaw #language-Chipewyan #language-Cherokee #language-Cholón #language-Chuvash #language-Chuwabu #language-Cheyenne #language-Cia-Cia #language-Chickasaw #language-Chinali #language-Chitkuli Kinnauri #language-Cimbrian #language-Upper Chehalis #language-Chamalal #language-Chokwe #language-Shor #language-Cibak #language-Koasati #language-Kavalan #language-Chulym #language-Cerma #language-Changthang #language-Northern Qiang #language-Hakha Chin #language-Asháninka #language-Chung #language-Montenegrin #language-Chicomuceltec #language-Koreguaje #language-Chong #language-Comanche #language-Cofán #language-Comox #language-Coptic #language-Cornish #language-Corsican #language-Caquinte #language-Wamey #language-Nanti #language-Capiznon #language-Lonwolwol #language-Coeur d'Alene #language-Cree #language-Crimean Tatar #language-Plains Cree #language-Moose Cree #language-Crow #language-Carolina Algonquian #language-Chaura #language-Carrier #language-Cruzeño #language-Kashubian #language-Swampy Cree #language-Chittagonian #language-Chitimacha #language-Cubeo #language-Mashco Piro #language-Cumanagoto #language-Cupeño #language-Tai Ya #language-Kwere #language-Welsh #language-Dangaléat #language-Dagbani #language-Gwahatike #language-Dakota #language-Danish #language-Dargwa #language-Bangime #language-Dadiya #language-Dibiyaso #language-Dongotono #language-Dagik #language-Dehwari #language-Dem #language-Deori #language-Desano #language-German #language-Domung #language-Dogrib #language-Dogoso #language-Dhundari #language-Dhimal #language-Zemba #language-Dia #language-Digo #language-Dilling #language-Dinka #language-Dibo #language-Dimasa #language-Ding #language-Zarma #language-Jawoyn #language-Jangkang #language-Dolgan #language-Dahalik #language-Dalmatian #language-Gavak #language-Dameli #language-East Damar #language-Demta #language-Dungan #language-Dan #language-Dengka #language-Danau #language-Western Dani #language-Dom #language-Domu #language-Bussa #language-Minderico #language-Darmiya #language-Paakantyi #language-West Damar #language-Rukai #language-Lower Sorbian #language-Ditidaht #language-Dumun #language-Jola-Fonyi #language-Dyula #language-Tunzu #language-Eastern Bontok #language-Ebrié #language-Embu #language-E #language-Efik #language-Eggon #language-Askopan #language-Ekari #language-Koti #language-Yace #language-Elepi #language-Nding #language-Mamulique #language-Erromintxela #language-Apali #language-Enlhet #language-Engenni #language-Enxet #language-Eravallan #language-Ogea #language-Horpa #language-Eritai #language-Ese Ejja #language-Esselen #language-Central Siberian Yupik #language-Estonian #language-Eskayan #language-Eten #language-Basque #language-Even #language-Uvbie #language-Evenki #language-Ewe #language-Extremaduran #language-Keiyo #language-Fasu #language-Wagi #language-Faroese #language-Persian #language-Foia Foia #language-Fongoro #language-Nobiin #language-Faifi #language-Fijian #language-Filipino #language-Finnish #language-Fipa #language-Firan #language-Kirya-Konzəl #language-Fania #language-Fon #language-Fas #language-French #language-Fordata #language-Frankish #language-Pulaar #language-Friulian #language-Furu #language-Fur #language-Fwe #language-Ga #language-Gagauz #language-Alekano #language-Gamkonora #language-Gants #language-Nobonob #language-Gayo #language-Gaddi #language-Garhwali #language-Zoroastrian Dari #language-Mali #language-Galice #language-Gurdjar #language-Dirasha #language-Laal #language-Umanakaina #language-Wipi #language-Geruma #language-Kire #language-Gebe #language-Gen #language-Gera #language-Garre #language-Enya #language-Patpatar #language-Kungarakany #language-Ghanongga #language-Gidar #language-Gilbertese #language-Gitxsan #language-Gujari #language-Kok-Nar #language-Nanai #language-Irish #language-Galician #language-Gilaki #language-Manx #language-Glavda #language-Gula'alaa #language-Kaansa #language-Ngangam #language-Guntai #language-Gongduk #language-Gogo #language-Gobasi #language-Gondi #language-Gorontalo #language-Goo #language-Guiqiong #language-Grebo #language-Gbiri-Niragu #language-Guarani #language-Garo #language-Shiki #language-Wayuu #language-Guahibo #language-Eastern Bolivian Guaraní #language-Gujarati #language-Mbyá Guaraní #language-Guayabero #language-Aché #language-Farefare #language-Yanomamö #language-Gun #language-Gusii #language-Duwet #language-Guajá #language-Gulay #language-Gawri #language-Gweno #language-Gwichʼin #language-Gwere #language-Gyalsumdo #language-Guarayu #language-Ganza #language-Haida #language-Hajong #language-Hangaza #language-Ha #language-Harari #language-Haisla #language-Hausa #language-Havu #language-Hawaiian #language-Haya #language-Huba #language-Heiban #language-Huichol #language-Hebrew #language-Hehe #language-Herero #language-Hoia Hoia #language-Hidatsa #language-Pamosu #language-Hinduri #language-Hiligaynon #language-Hittite #language-Hunde #language-Halbi #language-Hlersu #language-Hmong #language-Hamtai #language-Chhattisgarhi #language-Hani #language-Hanunoo #language-Ho #language-Horom #language-Holikachuk #language-Holu #language-Holoholo #language-Hopi #language-Hote #language-Hrangkhol #language-Hruso #language-Croatian #language-Upper Sorbian #language-Minica Huitoto #language-Hadza #language-Huilliche #language-Hungarian #language-Hupa #language-Huastec #language-Hukumina #language-Nüpode Huitoto #language-Hunzib #language-Armenian #language-Iaai #language-Iatmul #language-Iban #language-Ibibio #language-Ibaloi #language-Agoi #language-Igbo #language-Idon #language-Idoma #language-Kanggape #language-Iha #language-Izon #language-Kalabari #language-Ik #language-Ikizu #language-Ila #language-Ili Turki #language-Anamgura #language-Miluk #language-Milyan #language-Indonesian #language-Ingush #language-Inor #language-Irarutu #language-Rigwe #language-Iraqw #language-Irula #language-Kamberau #language-Esan #language-Nkem-Nkum #language-Ishkashimi #language-Icelandic #language-Isanzu #language-Istriot #language-Italian #language-Itelmen #language-Itonama #language-Iteri #language-Iu Mien #language-Ivatan #language-Iwur #language-Sepik Iwam #language-Ixcatec #language-Mesaka #language-Ingrian #language-Izere #language-Hyam #language-Yabem #language-Yalahatan #language-Javanese #language-Nafusi #language-Jukun Takum #language-Krymchak #language-Jadgali #language-Jebero #language-Yelmek #language-Manem #language-Ngbee #language-Ngomba #language-Tol #language-Jingulu #language-Jiamao #language-Jita #language-Shuar #language-Labir #language-Ngile #language-Dima #language-Zumbun #language-Jumli #language-Janji #language-Jowulu #language-Japanese #language-Jaqaru #language-Jarai #language-Wapan #language-Juang #language-Jiba #language-Jwira-Pepesa #language-Kabyle #language-Adara #language-Jju #language-Bezhta #language-Kashmiri #language-Georgian #language-Kanuri #language-Kazakh #language-Kabardian #language-Kari #language-Kafa #language-Kabutra #language-Duhwa #language-Khanty #language-Tyap #language-Kalanga #language-Nubi #language-Kamo #language-Katla #language-Kaian #language-Kabwari #language-Korandje #language-Makonde #language-Tem #language-Numèè #language-Kunda #language-Karaim #language-Kuy #language-Kam #language-Kerewe #language-Tese #language-Keak #language-Kenyang #language-Ket #language-Kanikkaran #language-Koya #language-Kinnauri #language-Khunsari #language-Korwa #language-Korku #language-Kanjari #language-Kumaoni #language-Komering #language-Kusunda #language-Kaiwá #language-Kaingang #language-Somyev #language-Kobol #language-Karas #language-Khasi #language-Korowai #language-Lusi #language-Khmer #language-Kharia #language-Khamti #language-Koalib #language-Kikuyu #language-Kariya #language-Kiowa #language-Kimbu #language-Kirikiri #language-Khmu #language-Khakas #language-Highland Konjo #language-Kháng #language-Kunjen #language-Kashaya #language-Ramopa #language-Kinuku #language-Khün #language-Kokota #language-Kiong #language-Giiwo #language-Koi #language-Kangean #language-Kaska #language-Kiliwa #language-Kendeje #language-Khalaj #language-Rumu #language-Khaling #language-Kalasha #language-Klao #language-Kalao #language-Konni #language-Kanufi #language-Kwanja #language-Tabo #language-Kendayan #language-Kalamsé #language-Komi #language-Kongo #language-Waube #language-Korean #language-Lagwan #language-Koyukon #language-Kutto #language-Kpelle #language-Komba #language-Kapingamarangi #language-Karajá #language-Koho #language-Tehit #language-Kafoa #language-Koryak #language-Kupsabiny #language-Mum #language-Khe #language-Kyenele #language-Kaonde #language-Kimré #language-Seroa #language-Okolod #language-Panará #language-Kurama #language-Karelian #language-Kurukh #language-Kryts #language-Shambala #language-Kansa #language-Kumba #language-Kaba #language-Borong #language-S'gaw Karen #language-Nubri #language-Kurti #language-Kwinsu #language-Kuria #language-Kumyk #language-Kunama #language-Kusaal #language-Kutenai #language-Upper Kuskokwim #language-Kunza #language-Bagvalal #language-Kalabakan #language-Kabalai #language-Kayaw #language-Kerinci #language-Wersing #language-Kwerba #language-Kwara'ae #language-Kowiai #language-Kwangali #language-Kwese #language-Kwadi #language-Keningau Murut #language-Kuvi #language-Kayagar #language-Rapoisi #language-Kayeli #language-Kais #language-Karang #language-Lacandon #language-Lambya #language-Lamba #language-Laru #language-Lao #language-Qabiao #language-Latvian #language-Aribwatsa #language-Lak #language-Tinani #language-Ladakhi #language-Central Bontok #language-Wampar #language-Lardil #language-Loncong #language-Lisela #language-Luhu #language-Luri #language-Lemoro #language-Kaan #language-Loo #language-Tso #language-Lala-Bisa #language-Leco #language-Lendu #language-Lyélé #language-Lelemi #language-Lenje #language-Lengola #language-Lese #language-Lesing-Gelimi #language-Luang #language-Lemolang #language-Logba #language-Pahi #language-Lahu #language-Limbu #language-Lihir #language-Ligurian #language-Lillooet #language-Lisu #language-Lithuanian #language-Col #language-Laiyolo #language-Lakha #language-Laki #language-Remun #language-Khayo #language-Päri #language-Lakota #language-Lokoya #language-Ladin #language-Lole #language-Lilau #language-North Efate #language-Lau #language-Limilngan #language-Lumun #language-Lamkang #language-Lombard #language-Limbum #language-Lanoh #language-Longuda #language-Loloda #language-Lobi #language-Saluan #language-Logol #language-Loko #language-Mongo #language-Malawi Lomwe #language-Lopa #language-Otuho #language-Lozi #language-Lipo #language-Lopit #language-Marachi #language-Lashi #language-Aruop #language-Latgalian #language-Luba-Katanga #language-Lunda #language-Lumbu #language-Lwalu #language-Luyana #language-Litzlitz #language-Laz #language-Madurese #language-Magahi #language-Marshallese #language-Maithili #language-Mam #language-Marathi #language-Mampruli #language-Maxakalí #language-Macaguán #language-Mbula-Bwazza #language-Memoni #language-Bitur #language-Matsés #language-Mvanip #language-Mbunda #language-Moksha #language-Mangbetu #language-Mbole #language-Mbere #language-Ikobi #language-Megam #language-Meyah #language-Meru #language-Maaka #language-Menominee #language-Naki #language-Wandala #language-Mbe #language-Marrithiyel #language-Moru #language-Maklew #language-Mpumpong #language-Abureni #language-Malila #language-Mambwe-Lungu #language-Mailu #language-Matengo #language-Matumbi #language-Mbugu #language-Ma'di #language-Mauwake #language-Mandan #language-Mbukushu #language-Mi'kmaq #language-Mandaic #language-Minangkabau #language-Akoye #language-Muskum #language-Miship #language-Karbi #language-Mbre #language-Mal Paharia #language-Siliput #language-Macedonian #language-Dhatki #language-Mokilese #language-Byep #language-Mingang Doso #language-Moikodi #language-Bay Miwok #language-Cao Lan #language-Mal #language-Ilwana #language-Bargam #language-Vame #language-Masalit #language-Maltese #language-Moloko #language-Mangga Buang #language-Siawi #language-Malalamai #language-Miriti #language-Emae #language-Muna #language-Manchu #language-Mondé #language-Munji #language-Mansi #language-Mon #language-Mohawk #language-Mboi #language-Morori #language-Mangue #language-Moro #language-Barí #language-Molima #language-Mpoto #language-Majang #language-Marba #language-Maung #language-Mpi #language-Manipa #language-West Makian #language-Maricopa #language-Elseng #language-Mising #language-Mangareva #language-Mandaya #language-Mekwei #language-Mansaka #language-Caac #language-Aruamu #language-Mualang #language-Moskona #language-Montol #language-Muong #language-Mewari #language-Nabi #language-Mundang #language-Musgu #language-Nyong #language-Malvi #language-Muthuvan #language-Duri #language-Massep #language-Marfa #language-Juwal #language-Mirandese #language-Sar #language-Mentawai #language-Mele-Fila #language-Malgbe #language-Meramera #language-Mbowe #language-Burmese #language-Mbay #language-Myene #language-Bambassi #language-Manta #language-Makah #language-Pirahã #language-Erzya #language-Macuna #language-Mumuye #language-Mazanderani #language-Movima #language-Mintil #language-Deg #language-Nakanai #language-Neapolitan #language-Khoekhoe #language-Navajo #language-Ndoe #language-Nkukoli #language-Nnam #language-Iyo #language-Nisga'a #language-Natchez #language-Nde-Nsele-Nta #language-Ndengereko #language-Ndali #language-Ndo #language-Lutos #language-Negidal #language-Ná-Meo #language-Yahadian #language-Nyaheun #language-Nez Perce #language-Dhao #language-Ahwai #language-Nǁng #language-Lomwe #language-Ngwo #language-Ngulu #language-Nagumi #language-Tibea #language-Beng #language-Nias #language-Niellim #language-Ngalakgan #language-Nii #language-Southern Nicobarese #language-Ninzo #language-Nganasan #language-Nimboran #language-Niuean #language-Hema #language-Ngiti #language-Nkoya #language-Koireng #language-Nukuoro #language-North Asmat #language-Nalca #language-Dutch #language-Nyali #language-Big Nambas #language-Ngam #language-Kwasio #language-Namakura #language-Nambya #language-Nimbari #language-Namuyi #language-Nawdm #language-Nande #language-Ngiemboon #language-Ngindo #language-Dwang #language-Northern Thai #language-Nimadi #language-Nogai #language-Nonuya #language-Nooksack #language-Nomlaki #language-Norwegian #language-Nomatsiguenga #language-Nyambo #language-Noy #language-Nara #language-Narom #language-Norn #language-Nsenga #language-Naskapi #language-Nsongo #language-Nisenan #language-Natioro #language-Delo #language-Mantsi #language-Nuu-chah-nulth #language-Nuer #language-Nunggubuyu #language-Nyokon #language-Nawaru #language-Naxi #language-Ninggerum #language-Nyanga #language-Nyaneka #language-Nyoro #language-Nyang'i #language-Nyungwe #language-Njebi #language-Nzadi #language-Nzakambay #language-Oroch #language-Obispeño #language-Ocaina #language-Ogbia #language-Khana #language-Ogbronuagum #language-Okanagan #language-Okodia #language-Oko-Juwoi #language-Oku #language-Olrat #language-Mochica #language-Utarmbung #language-Omotik #language-Ona #language-Oneida #language-Onondaga #language-Sartang #language-Oksapmin #language-Orejón #language-Oromo #language-Odia #language-Osage #language-Ososo #language-Ossetian #language-Oti #language-Otoro #language-Pagibete #language-Pangasinan #language-Pe #language-Parya #language-Palauan #language-Pankararú #language-Páez #language-Paraujano #language-Parkwa #language-Badyara #language-Pangwa #language-Pnar #language-Pear #language-Bouyei #language-Picard #language-Paniya #language-Duruwa #language-Pardhi #language-Piti #language-Podena #language-Eastern Pomo #language-Bonan #language-Phudagi #language-Phuong #language-Phukha #language-Phake #language-Phunoi #language-Phu Thai #language-Phuan #language-Pahlavani #language-Pima Bajo #language-Yine #language-Pinji #language-Piaroa #language-Piapoco #language-Pero #language-Pimbwe #language-Pokomo #language-Maleng #language-Palu'e #language-Palikúr #language-Tuamotuan #language-Penrhyn #language-Paleni #language-Polish #language-Pohnpeian #language-Portuguese #language-Potawatomi #language-Polabian #language-Pogolo #language-Paipai #language-Uma #language-Pare #language-Puragi #language-Parawen #language-Panasuan #language-Pai Tavytera #language-Zo'é #language-Enrekang #language-Bambam #language-Port Vato #language-Pentlatch #language-Puelche #language-Puinave #language-Puma #language-Punu #language-Patwin #language-Paiwan #language-Quapaw #language-Quileute #language-Quinault #language-Logooli #language-Rabha #language-Riantana #language-Rao #language-Rawang #language-Barababaraba #language-Reli #language-Rejang #language-Rengao #language-Reshe #language-Reyesano #language-Ringgou #language-Rohingya #language-Yahang #language-Nungu #language-Rikbaktsa #language-Rakhine #language-Rangpuri #language-Rama #language-Rembarrnga #language-Angloromani #language-Domari #language-Welsh Romani #language-Vlax Romani #language-Ruund #language-Rungwa #language-Rombo #language-Romansh #language-Romblomanon #language-Romanian #language-Dela-Oenale #language-Ruthenian #language-Rotuman #language-Gungu #language-Ruuli #language-Rusyn #language-Luguru #language-Russian #language-Rutul #language-Ruma #language-Rawa #language-Yaeyama #language-Sandawe #language-Sango #language-Yakut #language-Sake #language-Samaritan Aramaic #language-Samburu #language-Santali #language-Saleman #language-Saya #language-Saurashtra #language-Safwa #language-Sabüm #language-Kimki #language-Soli #language-Sakachep #language-Sicilian #language-Scots #language-Sa'och #language-Suundi #language-Sherdukpen #language-Semai #language-Seneca #language-Seri #language-Sekani #language-Serrano #language-Secoya #language-Sehwi #language-Shughni #language-Sangkong #language-Singa #language-Samogitian #language-Sanglechi #language-Ninam #language-Sonde #language-Kundal Shahi #language-Shoshoni #language-Shatt #language-Shilluk #language-Shan #language-Shi #language-Shuswap #language-Shwai #language-She #language-Siamou #language-Paasaal #language-Zire #language-Sikiana #language-Sinhala #language-Sikkimese #language-Siuslaw #language-Sinagen #language-Siwai #language-Sumau #language-Sivandi #language-Siwi #language-Xibe #language-Surjapuri #language-Siar-Lak #language-Shawnee #language-Saek #language-Saraiki #language-Maia #language-Skou #language-Slovak #language-Salt-Yui #language-Salar #language-Salampasu #language-Selayar #language-Bolinao #language-Samoan #language-Simeulue #language-Simte #language-Sumbawa #language-Semnani #language-Shona #language-Sindhi #language-Noon #language-Soninke #language-Siona #language-Sam #language-Kou #language-Thai Song #language-Sogdian #language-Aka #language-Somali #language-Kanasi #language-Somrai #language-Southern Thai #language-Spanish #language-Sapé #language-Akukem #language-Sanapaná #language-Saposa #language-Sapuan #language-Sambalpuri #language-Sabaot #language-Shau #language-Albanian #language-Soqotri #language-Squamish #language-Sora #language-Sardinian #language-Sarikoli #language-Siriano #language-Saramaccan #language-Serbian #language-Sirionó #language-Serer #language-Sirmauri #language-Thao #language-Sansi #language-Sunam #language-Semnam #language-Owa #language-Stoney #language-Siberian Tatar #language-Suku #language-Sukuma #language-Sundanese #language-Susu #language-Puroik #language-Sumbwa #language-Sumerian #language-Suyá #language-Sunwar #language-Svan #language-Swedish #language-Sui #language-Saweru #language-Shekhawati #language-Sighu #language-Saaroa #language-Sukur #language-Sylheti #language-Suoy #language-Syriac #language-Sinyar #language-Kagate #language-Samay #language-Ngalum #language-Silesian #language-Sula #language-Suabo #language-Sawai #language-Lower Tanana #language-Tagoi #language-Tahitian #language-Tamil #language-Yami #language-Taabwa #language-Tamasheq #language-Tatar #language-Upper Tanana #language-Tatuyo #language-Tocho #language-Aikanã #language-Tanimbili #language-Gaam #language-Calamian Tagbanwa #language-Taworta #language-Tembo (Kitembo) #language-Ticuna #language-Tanacross #language-Tamagario #language-Tulu #language-Tagdal #language-Thulung #language-Toro #language-Terik #language-Teressa #language-Tehuelche #language-Torricelli #language-Telugu #language-Teso #language-Temein #language-Tetum #language-Soo #language-Tetserret #language-Teribe #language-Ternate #language-Tajik #language-Tagalog #language-Tangoa #language-Tagish #language-Thai #language-Thangmi #language-Thompson #language-Thakali #language-Tahltan #language-Tha #language-Tigre #language-Tiene #language-Tilung #language-Tillamook #language-Tindi #language-Tigrinya #language-Tinigua #language-Tiv #language-Tai Laing #language-Djabwurrung #language-Takelma #language-Tsakhur #language-Mur Pano #language-Klingon #language-Tlingit #language-Tetela #language-Tai Loi #language-Khehek #language-Talysh #language-Haruai #language-Toba-Maskoy #language-Samarokena #language-Tima #language-Iau #language-Temuan #language-Tanimuca-Retuarã #language-Tobanga #language-Kwamera #language-Lenakel #language-Tabla #language-Tanema #language-Tongwe #language-Tolowa #language-Tombulu #language-Toposa #language-Jemez #language-Tobian #language-Kula #language-Trumai #language-Tinputz #language-Lehali #language-Toaripi #language-Taushiro #language-Turoyo #language-Torwali #language-Tsaangi #language-Tsamai #language-Tswa #language-Tsakonian #language-Tausug #language-Tswana #language-Tsonga #language-Tsou #language-Tsogo #language-Mubami #language-Tutelo #language-Gaa #language-Tobati #language-Tooro #language-Totela #language-Titan #language-Wiarumus #language-Tübatulabal #language-Mutu #language-Tuyuca #language-Turkmen #language-Tumbuka #language-Tunica #language-Tucano #language-Turkish #language-Tuscarora #language-Tututni #language-Turkana #language-Tugen #language-Turka #language-Southeast Ambrym #language-Taivoan #language-Twana #language-Tai Dón #language-Twendi #language-Tasawaq #language-Termanu #language-Tsetsaut #language-Tangut #language-Ikpeng #language-Tii #language-Tatana #language-Tauya #language-Tai Daeng #language-Tày #language-Tzeltal #language-Tzotzil #language-Tabriak #language-Kuan #language-Tairuma #language-Ubykh #language-Udi #language-Udmurt #language-Kubachi #language-Ukrainian #language-Ukwuani-Aboh-Ndoni #language-Ulukwumi #language-Ulch #language-Lule #language-Usku #language-Ulithian #language-Ullatan #language-Umpila #language-Munsee #language-Uneme #language-Ngarinyin #language-Mundari #language-Urarina #language-Uru #language-Urak Lawoi' #language-Sop #language-Uya #language-Urum #language-U #language-West Uvean #language-Uri #language-Uzbek #language-Southern Uzbek #language-Vai #language-Huarijio #language-Vasavi #language-Vanuma #language-Varli #language-Venetian #language-Venda #language-Ventureño #language-Veps #language-Vietnamese #language-Vili #language-Kaur #language-Lungalunga #language-Makhuwa #language-Votic #language-Võro #language-Vumbu #language-Wan #language-Washo #language-Kaninuwa #language-Waritai #language-Wanda #language-Vwanji #language-Wakhi #language-Wa #language-Wadjiginy #language-Warrgamay #language-Wichita #language-Minidien #language-Ho-Chunk #language-Vitu #language-Waja #language-Wakde #language-Walloon #language-Wallisian #language-Wambule #language-Wamin #language-Mwani #language-Wantoat #language-Wanggamala #language-Wanap #language-Usan #language-Wintu #language-Wolof #language-Wongo #language-Wiradjuri #language-Warembori #language-Watiwa #language-Berta #language-Watakataui #language-Mewati #language-Silimo #language-Wurrugu #language-Wutung #language-Waama #language-Wymysorys #language-Wyandot #language-Wayoró #language-Adai #language-Xamtanga #language-Kawaiisu #language-Bactrian #language-Kambiwá #language-Chemakum #language-Kaitag #language-Hdi #language-Kembayan #language-Guwa #language-Xhosa #language-Kalkoti #language-Mainstream Kenyah #language-Kiorr #language-Kgalagadi #language-Kamula #language-Lycian #language-Mbudum #language-Mingrelian #language-Mengaka #language-Anglo-Norman #language-Kangri #language-Kenzi #language-Soga #language-Konkomba #language-Mohegan-Pequot #language-Parthian #language-Karakhanid #language-Solano #language-Sherpa #language-Sanumá #language-Saisiyat #language-Ketengban #language-Betta Kurumba #language-Kunigami #language-Kuo #language-Kwaza #language-Woccon #language-Kwerba Mamberamo #language-Wemba Wemba #language-Yorta Yorta #language-Zhang-Zhung #language-Yagua #language-Yao #language-Yapese #language-Yaqui #language-Yala #language-Yemba #language-Hasha #language-Yukuben #language-Lolopo #language-Yucuna #language-Yidgha #language-Yevanic #language-Tarok #language-Nyankpa #language-Yapunda #language-Yeyi #language-Awu #language-Yasa #language-Yaul #language-Yele #language-Yelogu #language-Yameo #language-Moji #language-Makwe #language-Yamna #language-Muzi #language-Naukan Yupik #language-Yong #language-Yansi #language-Yonaguni #language-Yoron #language-Phola #language-Phupha #language-Sani #language-Yessan-Mayo #language-Yuchi #language-Yuki #language-Yulu #language-Quechan #language-Yukpa #language-Yurok #language-Southern Yukaghir #language-Kalou #language-Yuyu #language-Zaghawa #language-Zenaga #language-Kinga #language-Zhaba #language-Dai Zhuang #language-Zhire #language-Nong Zhuang #language-Chinese #language-Zialo #language-Mesme #language-Zinza #language-Zigula #language-Zizilivakan #language-Karankawa #language-Zakhring #language-Kaurna #language-Zimba #language-Mfinu #language-Mbangwe #language-Mpuono #language-Mbariman-Gudhinma #language-Zarphatic #language-Zulu #language-Zuni #language-Zay #language-Yang Zhuang #language-Abun #language-Anem #language-Bilua #language-Bogaya #language-Burmeso #language-Burushaski #language-Camsá #language-Canichana #language-Cayuse #language-Cayubaba #language-Chimariko #language-Coahuilteco #language-Cotoname #language-Cuitlatec #language-Damal #language-Duna #language-Elamite #language-Etruscan #language-Fulniô #language-Fuyug #language-Guató #language-Gule #language-Gumuz #language-Guriaso #language-Hattic #language-Iberian #language-Kaki Ae #language-Kapori #language-Karami #language-Karok #language-Kehu #language-Kenaboi #language-Kibiri #language-Klamath-Modoc #language-Kol (Papua New Guinea) #language-Kujarge #language-Kuot #language-Lafofa #language-Laragia #language-Lavukaleve #language-Máku #language-Mawes #language-Meroitic #language-Minkin #language-Molale #language-Molof #language-Mor (Bomberai Peninsula) #language-Mpur #language-Muniche #language-Nihali #language-Odiai #language-Omurano #language-Papi #language-Pawaia #language-Pele-Ata #language-Pumé #language-Puquina #language-Purari #language-Salinan #language-Sause #language-Savosavo #language-Shom Peng #language-Sulka #language-Taiap #language-Tambora #language-Tanahmerah #language-Taruma #language-Tauade #language-Timucua #language-Tiwi #language-Tonkawa #language-Touo #language-Tsimshian #language-Tuxá #language-Umbugarla #language-Vilela #language-Warao #language-Wiru #language-Xukurú #language-Yale #language-Yámana #language-Yana #language-Yerakai #language-Yetfa #language-Hoti #language-Awjilah #language-Tumzabt #language-Sened #language-Tachelhit #language-Standard Moroccan Tamazight #language-Ghomara #language-Senhaja De Srair #language-Tahaggart Tamahaq #language-Tawallammat Tamajaq #language-Tayart Tamajeq #language-Guanche #language-Mbuko #language-Mbara (Chad) #language-Hya #language-Psikye #language-Bana #language-Kamwe #language-Buduma #language-Jina #language-Majera #language-Mser #language-Maslam #language-Mpade #language-Lamang #language-Vemgo-Mabas #language-Marghi Central #language-Marghi South #language-Bura-Pabir #language-Nggwahyi #language-Putai #language-Dghwede #language-Gvoko #language-Cineni #language-Guduf-Gava #language-Matal #language-Dugwor #language-Merey #language-Zulgo-Gemzek #language-Mofu-Gudur #language-North Mofu #language-Mada (Cameroon) #language-Muyang #language-Wuzlam #language-North Giziga #language-South Giziga #language-Bacama #language-Gudu #language-Ngwaba #language-Jimi (Cameroon) #language-Fali #language-Gude #language-Holma #language-Nzanyi #language-Sharwa #language-Tsuvan #language-Mina (Cameroon) #language-Gavar #language-Mazagway #language-Daba #language-Boga #language-Ga'anda #language-Hwana #language-Jara #language-Tera #language-Cuvok #language-Mafa #language-Mefele #language-Jilbe #language-Mukulu #language-Mabire #language-Birgit #language-Mogum #language-Toram #language-Bidiyo #language-Migaama #language-Jonkor Bourmataguil #language-Kajakse #language-Masmaje #language-Mubi #language-Mawa (Chad) #language-Ubi #language-Boor #language-Miltu #language-Saba #language-Sokoro #language-Tamki #language-Kera #language-Kwang #language-Lele (Chad) #language-Nancere #language-Gabri #language-Ndam #language-Tumak #language-Gadang #language-Sarua #language-Musey #language-Masana #language-Zumaya #language-Ngete #language-Fyer #language-Tambas #language-Kulere #language-Ron #language-Gwandara #language-Karekare #language-Galambu #language-Ngamo #language-Beele #language-Deno #language-Kubi #language-Bure #language-Kholok #language-Nyam #language-Dera (Nigeria) #language-Kushi #language-Piya-Kwonci #language-Tangale #language-Kwaami #language-Mwaghavul #language-Ngas #language-Goemai #language-Tal #language-Koenoem #language-Pyapun #language-Jakattoe #language-Nteng #language-Duwai #language-Ngizim #language-Bade #language-Auyokawa #language-Teshenawa #language-Ajawa #language-Ciwogai #language-Diri #language-Mburku #language-Pa'a #language-Siri #language-Miya #language-Warji #language-Boghom #language-Kir-Balar #language-Mangas #language-Guruntum-Mbaaru #language-Jimi (Nigeria) #language-Ju #language-Tala #language-Zangwal #language-Geji #language-Dass #language-Zeem #language-Zari #language-Awngi #language-Bilin #language-Dahalo #language-Hadiyya #language-Libido #language-Kambaata #language-Gedeo #language-Sidamo #language-Saho #language-Konso #language-West Central Oromo #language-Borana-Arsi-Guji Oromo #language-Orma #language-Eastern Oromo #language-Waata #language-Girirra #language-Maay #language-Rendille #language-Baiso #language-Jiiddu #language-Dabarre #language-Tunni #language-Aweer #language-Arbore #language-Daasanach #language-El Molo #language-Yaaku #language-Boon #language-Kw'adza #language-Burunge #language-Alagwa #language-Gorowa #language-Egyptian (Ancient) #language-Ancient North Arabian #language-Arabic #language-Standard Arabic #language-Hadrami Arabic #language-Hijazi Arabic #language-Judeo-Yemeni Arabic #language-Sanaani Arabic #language-Shihhi Arabic #language-Ta'izzi-Adeni Arabic #language-Baharna Arabic #language-Dhofari Arabic #language-Gulf Arabic #language-Najdi Arabic #language-Omani Arabic #language-Tajiki Arabic #language-Uzbeki Arabic #language-Judeo-Iraqi Arabic #language-North Mesopotamian Arabic #language-Eastern Egyptian Bedawi Arabic #language-Egyptian Arabic #language-Saidi Arabic #language-Chadian Arabic #language-Sudanese Arabic #language-Cypriot Arabic #language-Levantine Arabic #language-South Levantine Arabic #language-Algerian Arabic #language-Algerian Saharan Arabic #language-Hassaniyya #language-Judeo-Tripolitanian Arabic #language-Judeo-Moroccan Arabic #language-Libyan Arabic #language-Tunisian Arabic #language-Andalusian Arabic #language-Moroccan Arabic #language-Classical Syriac #language-Assyrian Neo-Aramaic #language-Chaldean Neo-Aramaic #language-Jewish Babylonian Aramaic (ca. 200-1200 CE) #language-Senaya #language-Barzani Jewish Neo-Aramaic #language-Lishana Deni #language-Hulaulá #language-Lishán Didán #language-Lishanid Noshan #language-Classical Mandaic #language-Western Neo-Aramaic #language-Jewish Palestinian Aramaic #language-Old Aramaic (up to 700 BCE) #language-Ancient Hebrew #language-Samaritan #language-Edomite #language-Moabite #language-Ugaritic #language-Phoenician #language-Punic #language-Hadrami #language-Minaean #language-Qatabanian #language-Geez #language-Amharic #language-Argobba #language-Silt'e #language-Wolane #language-Gafat #language-Kistane #language-Mesqan #language-Sebat Bet Gurage #language-Mesmes #language-Hobyót #language-Bathari #language-Harsusi #language-Mehri #language-Wiyot #language-Siksika #language-Nawathinehena #language-Gros Ventre #language-Northern East Cree #language-Southern East Cree #language-Woods Cree #language-Michif #language-Malecite-Passamaquoddy #language-Powhatan #language-Unami #language-Nanticoke #language-Piscataway #language-Loup A #language-Wampanoag #language-Miami #language-Kickapoo #language-Meskwaki #language-Ojibwa #language-Ottawa #language-Central Ojibwa #language-Chippewa #language-Eastern Ojibwa #language-Northwestern Ojibwa #language-Western Ojibwa #language-Severn Ojibwa #language-Alsea #language-Amto #language-Angaataha #language-Yagwoia #language-Baruya #language-Simbari #language-Menya #language-Kawacha #language-Kamasa #language-Susuami #language-Ankave #language-Ipiko #language-Kuni-Boazi #language-Zimakani #language-Bian Marind #language-Marind #language-Warkay-Bipim #language-Yaqay #language-Abom #language-Baramu #language-Tapei #language-Mapudungun #language-Yavitero #language-Baré #language-Taino #language-Garifuna #language-Island Carib #language-Enawené-Nawé #language-Parecís #language-Saraveca #language-Yawalapití #language-Mehináku #language-Waurá #language-Cabiyarí #language-Tariana #language-Curripaco #language-Achagua #language-Mandahuaca #language-Resígaro #language-Xiriâna #language-Wapishana #language-Baure #language-Paunaka #language-Ignaciano #language-Trinitario #language-Chané #language-Ajyíninka Apurucayali #language-Ashéninka Perené #language-Pichis Ashéninka #language-Ucayali-Yurúa Ashéninka #language-Ashéninka Pajonal #language-South Ucayali Ashéninka #language-Machiguenga #language-Apurinã #language-Iñapari #language-Machinere #language-Aruá (Amazonas State) #language-Suruahá #language-Madi #language-Culina #language-Afrihili #language-Blissymbols #language-Brithenig #language-Dutton World Speedwords #language-Interlingua (International Auxiliary Language Association) #language-Interglossa #language-Interlingue #language-Kotava #language-Láadan #language-Lingua Franca Nova #language-Lojban #language-Malawian Sign Language #language-N'Ko #language-Novial #language-Quenya #language-Romanova #language-Sindarin #language-Talossan #language-Toki Pona #language-Volapük #language-Esperanto #language-Ido #language-Eyak #language-Sarsi #language-Kiowa Apache #language-Jicarilla Apache #language-Lipan Apache #language-Mescalero-Chiricahua Apache #language-Southern Carrier #language-Han #language-Degexit'an #language-Northern Tutchone #language-Southern Tutchone #language-Beaver #language-North Slavey #language-South Slavey #language-Kato #language-Mattole #language-Wailaki #language-Upper Umpqua #language-Coquille #language-Ahtena #language-Gola #language-Mansoanka #language-East Limba #language-West-Central Limba #language-Sherbro #language-Bom-Kim #language-Bullom So #language-Northern Kissi #language-Southern Kisi #language-Baga Manduri #language-Baga Sitemu #language-Baga Koga #language-Landoma #language-Timne #language-Ndut #language-Saafi-Saafi #language-Lehar #language-Balanta-Kentohe #language-Balanta-Ganja #language-Bayot #language-Ejamat #language-Kuwaataay #language-Karon #language-Mlomp #language-Gusilay #language-Mankanya #language-Mandjak #language-Papel #language-Biafada #language-Mbulungish #language-Nalu #language-Borgu Fulfulde #language-Maasina Fulfulde #language-Pular #language-Western Niger Fulfulde #language-Central-Eastern Niger Fulfulde #language-Adamawa Fulfulde #language-Bagirmi Fulfulde #language-Kasanga #language-Kobiana #language-Gambian Wolof #language-Ega #language-Gade #language-Oko-Eni-Osayen #language-Ukaan #language-Akpes #language-Epie #language-Degema #language-Ghotuo #language-Yekhee #language-Bini #language-Emai-Iuleha-Ora #language-Enwan (Edo State) #language-Ikpeshi #language-Ivbie North-Okpela-Arhe #language-Igwe #language-Sasaru #language-Iyayu #language-Uhami #language-Ehueun #language-Ukue #language-Okpamheri #language-Oloma #language-Akuku #language-Okpe (Northwestern Edo) #language-Eruwa #language-Isoko #language-Okpe (Southwestern Edo) #language-Urhobo #language-Tikar #language-Samba Daka #language-Dirim #language-Lamja-Dengsa-Tola #language-Dong #language-Ndoola #language-Bung #language-Luo (Cameroon) #language-Njerep #language-Yeni #language-Mbongno #language-Ndunda #language-Vute #language-Wawa #language-Bishuo #language-Busuu #language-Bikya #language-Bukwen #language-Mashi (Nigeria) #language-Noone #language-Mbuk #language-Ncane #language-Bumaji #language-Obanliku #language-Bete #language-Ubang #language-Ukpe-Bayobiri #language-Buru (Nigeria) #language-Ejagham #language-Efutop #language-Abanyom #language-Ekajuk #language-Kendem #language-Seki #language-Kande #language-Simba #language-Bubi #language-Dimbong #language-Bafia #language-Lefa #language-Bankon #language-Barombi #language-Bakoko #language-Basa (Cameroon) #language-Hijuk #language-Bulu (Cameroon) #language-Fang (Equatorial Guinea) #language-Mengisa #language-Bebele #language-Ewondo #language-Kota (Gabon) #language-Mahongwe #language-Ndasa #language-Wumbvu #language-Kélé #language-Ngom #language-Ndambomo #language-Bonkeng #language-Nkongho #language-Mokpwe #language-Bassossi #language-Mbo (Cameroon) #language-Akoose #language-Bakaka #language-Kako #language-Kwakum #language-Bomwali #language-Mpiemo #language-Ukhwejo #language-Koonzime #language-Njyem #language-Makaa #language-Kol (Cameroon) #language-Gyele #language-Pomo #language-Batanga #language-Molengue #language-Ngumbi #language-Duala #language-Malimba #language-Bakole #language-Isu (Fako Division) #language-Mashi (Zambia) #language-Nyengo #language-Simaa #language-Sanga (Democratic Republic of Congo) #language-Kanyok #language-Bangubangu #language-Luba-Lulua #language-Binji #language-Luna #language-Songe #language-Zula #language-Mbangala #language-Phende #language-Mbala #language-Kibala #language-Kimbundu #language-Mpinda #language-Luvale #language-Luchazi #language-Nkangala #language-Nyemba #language-Luimbi #language-Mbwela #language-Kete #language-Umbundu #language-Kuvale #language-Kwandu #language-Ngendelengo #language-Kuanyama #language-Kwambi #language-Ndonga #language-Mbalanhu #language-Ngandyera #language-Nkhumbi #language-Ndombe #language-Mbesa #language-Lombo #language-Poke #language-Moingi #language-So (Democratic Republic of Congo) #language-Mbo (Democratic Republic of Congo) #language-Ndaka #language-Sengele #language-Bolia #language-Ntomba #language-Lalia #language-Ngando (Democratic Republic of Congo) #language-Ombo #language-Bushoong #language-Lele (Democratic Republic of Congo) #language-Dengese #language-Nkutu #language-Kusu #language-Kela (Democratic Republic of Congo) #language-Akwa #language-Mboko #language-Koyo #language-Mbosi #language-Dibole #language-Mbati #language-Ngundi #language-Yaka (Central African Republic) #language-Bomitaba #language-Bongili #language-Ngando (Central African Republic) #language-Lusengo #language-Bamwe #language-Dzando #language-Ndolo #language-Bomboma #language-Bomboli #language-Bozaba #language-Bali (Democratic Republic of Congo) #language-Amba (Uganda) #language-Kango (Tshopo District) #language-Komo (Democratic Republic of Congo) #language-Kango (Bas-Uélé District) #language-Nyanga-li #language-Homa #language-Mayeka #language-Bodo (Central African Republic) #language-Boguru #language-Ligenza #language-Ngombe (Democratic Republic of Congo) #language-Bwela #language-Bolondo #language-Babango #language-Boko (Democratic Republic of Congo) #language-Lobala #language-Boloki #language-Moi (Congo) #language-Bangala #language-Likuba #language-Likwala #language-Mabaale #language-Ndobo #language-Libinza #language-Samba #language-Beembe #language-Kaamba #language-Kunyi #language-Doondo #language-Laari #language-Hungu #language-Kituba (Congo) #language-Kituba (Democratic Republic of Congo) #language-San Salvador Kongo #language-Yombe #language-Bwisi #language-Sangu (Gabon) #language-Sira #language-Lonzo #language-Pelende #language-Ngongo #language-Ibali Teke #language-Sakata #language-Teke-Fuumu #language-Teke-Tyee #language-Teke-Kukuya #language-Teke-Tsaayi #language-Tchitchege #language-Kaningi #language-Ndumu #language-Teke-Laali #language-Yaka (Congo) #language-Duma #language-Wandji #language-Ngungwel #language-Teke-Nzikou #language-Dombe #language-Sala #language-Tonga (Zambia) #language-Subiya #language-Bungu #language-Nyamwanga #language-Nyika (Tanzania) #language-Nyika (Malawi and Zambia) #language-Nyiha (Malawi) #language-Nyiha (Tanzania) #language-Nyakyusa-Ngonde #language-Rangi #language-Mbugwe #language-Dhaiso #language-Kamba (Kenya) #language-Chuka #language-Tharaka #language-Temi #language-Mwimbi-Muthambi #language-Suba #language-Suba-Simbiti #language-Kabwa #language-Zanaki #language-Kara (Tanzania) #language-Kwaya #language-Luyia #language-Idakho-Isukha-Tiriki #language-Bukusu #language-Kabras #language-Masaaba #language-East Nyala #language-Kisa #language-Marama #language-Nyore #language-Tachoni #language-Tsotso #language-Wanga #language-Saamia #language-Nyole #language-Ganda #language-Kenyi #language-Talinga-Bwisi #language-Chiga #language-Nyankole #language-Subi #language-Nyindu #language-Fuliiru #language-Joba #language-Kinyarwanda #language-Rundi #language-Vinza #language-Shubi #language-Konzo #language-Kahe #language-Mochi #language-Vunjo #language-Machame #language-Rwa #language-Sagalla #language-Taita #language-Mwali Comorian #language-Ngazidja Comorian #language-Maore Comorian #language-Ndzwani Comorian #language-Chonyi-Dzihana-Kauma #language-Duruma #language-Giryama #language-Segeju #language-Congo Swahili #language-Cutchi-Swahili #language-Taveta #language-Asu (Tanzania) #language-Kagulu #language-Doe #language-Kami (Tanzania) #language-Kutu #language-Zaramo #language-Bondei #language-Mushungulu #language-Sagala #language-Vidunda #language-Bena (Tanzania) #language-Benamanga #language-Magoma #language-Kisi #language-Sangu (Tanzania) #language-Nyamwezi #language-Konongo #language-Ruwila #language-Bende #language-Bembe #language-Songoora #language-Buyu #language-Lega-Mwenga #language-Kanu #language-Lega-Shabunda #language-Mituku #language-Kwami #language-Nilamba #language-Nyaturu #language-Ndamba #language-Mbunga #language-Ndwewe #language-Ndendeule #language-Nindi #language-Machinga #language-Mwera (Chimwera) #language-Bwile #language-Bemba (Zambia) #language-Seba #language-Ndau #language-Manyika #language-Tewe #language-Tawara #language-Dema #language-Gitonga #language-Swati #language-Ronga #language-Kokola #language-Maindo #language-Manyawa #language-Nathembo #language-Lolo #language-Marenje #language-Takwane #language-Makhuwa-Shirima #language-Makhuwa-Meetto #language-Makhuwa-Marrevone #language-Makhuwa-Moniga #language-Makhuwa-Saka #language-Birwa #language-Pedi #language-Tswapong #language-Southern Sotho #language-Koma #language-Mwera (Nyasa) #language-Nyanja #language-Barwe #language-Malawi Sena #language-Sena #language-Phimbi #language-Tonga (Nyasa) #language-Bube #language-Mbonga #language-Kulung (Nigeria) #language-Mama #language-Dulbu #language-Bada (Nigeria) #language-Duguri #language-Bankal #language-Gwa #language-Nubaca #language-Bati (Cameroon) #language-Mbule #language-Yangben #language-Mmaala #language-Elip #language-Nugunu (Cameroon) #language-Leti (Cameroon) #language-Tuki #language-Tuotomb #language-Yambeta #language-Nomaande #language-Tunen #language-Esimbi #language-Evant #language-Iyive #language-Otank #language-Caka #language-Eman #language-Ambo #language-Bitare #language-Ambele #language-Befang #language-Ndemli #language-Mbe' #language-Yamba #language-Kwaja #language-Fe'fe' #language-Ghomálá' #language-Kwa' #language-Nda'nda' #language-Ngombale #language-Ngwe #language-Bafanji #language-Bambalang #language-Bamun #language-Bangolan #language-Mungaka #language-Bamenyam #language-Awing #language-Beba #language-Pinyin #language-Bafut #language-Bambili-Bambui #language-Mendankwe-Nkwen #language-Ngemba #language-Kpati #language-Mundani #language-Njen #language-Ngie #language-Ngoshie #language-Meta' #language-Ngamambo #language-Lamnso' #language-Kung #language-Kom (Cameroon) #language-Mbessa #language-Bum #language-Kuk #language-Laimbue #language-Isu (Menchum Division) #language-Zhoa #language-Weh #language-Bamunka #language-Kenswei Nsei #language-Balo #language-Busam #language-Osatu #language-Menka #language-Viti #language-Fang (Cameroon) #language-Koshin #language-Ajumbu #language-Abar #language-Mundabli #language-Fam #language-Sambe #language-Lijili #language-Cen #language-Ganang #language-Shall-Zwall #language-Doka #language-Iku-Gora-Ankwa #language-Kuturmi #language-Bo-Rukul #language-Fyam #language-Sur #language-Tiyaa #language-Bijim #language-Kadung #language-Ikulu #language-Aninka #language-Ayu #language-Numana #language-Kaningdon-Nindem #language-Che #language-Mada (Nigeria) #language-Kagoma #language-Kamantan #language-Shamang #language-Ashe #language-Koro Nulu #language-Kapya #language-Akum #language-Beezen #language-Lufu #language-Arigidi #language-Àhàn #language-Ayere #language-Igala #language-Isekiri #language-Mokole #language-Ede Cabe #language-Ede Ije #language-Lucumi #language-Yoruba #language-Kura Ede Nago #language-Ede Idaca #language-Ede Ica #language-Ifè #language-Abua #language-Odual #language-Kugbo #language-Ogbogolo #language-Obulom #language-O'chi'chi' #language-Ebughu #language-Ibino #language-Iko #language-Ilue #language-Okobo #language-Oro #language-Usaghade #language-Efai #language-Anaang #language-Ukwa #language-Ekit #language-Etebi #language-Ibuoro #language-Ito #language-Itu Mbon Uzo #language-Nkari #language-Enwan (Akwa Ibom State) #language-Uda #language-Eki #language-Idere #language-Gokana #language-Tee #language-Eleme #language-Ukpet-Ehom #language-Bakpinka #language-Doko-Uyanga #language-Olulumo-Ikom #language-Lokaa #language-Lubila #language-Cross River Mbembe #language-Legbo #language-Lenyima #language-Leyigha #language-Oring #language-Kukele #language-Uzekwe #language-Ubaghara #language-Agwagwune #language-Kohumono #language-Umon #language-Durop #language-Ebira #language-Gbagyi #language-Gbari #language-Asu (Nigeria) #language-Nupe-Nupe-Tako #language-Kakanda #language-Kupa #language-Kami (Nigeria) #language-Gupa-Abawa #language-Koro Zuba #language-Igede #language-Etulo #language-Akpa #language-Ekpeye #language-Ika #language-Ikwere #language-Ogbah #language-Ezaa #language-Ikwo #language-Kutep #language-Tigon Mbembe #language-Wãpha #language-Jibu #language-Hõne #language-Wannu #language-Como Karim #language-Jiru #language-Shoo-Minda-Nye #language-Etkywan #language-Kpan #language-Basa (Nigeria) #language-Basa-Gurmana #language-Bassa-Kontagora #language-Amo #language-Bina (Nigeria) #language-Kono (Nigeria) #language-Lere #language-Gyem #language-Kudu-Camo #language-Iguta #language-Jere #language-Panawa #language-Izora #language-Sanga (Nigeria) #language-Sheni #language-Damakawa #language-Cicipu #language-Tsuvadi #language-Tsikimba #language-Rogo #language-Eastern Acipa #language-Shama-Sambuga #language-Bauchi #language-Fungwa #language-Gurmana #language-Baissa Fali #language-Tita #language-Adangme #language-Aja (Benin) #language-Eastern Xwla Gbe #language-Tofin Gbe #language-Ci Gbe #language-Defi Gbe #language-Maxi Gbe #language-Weme Gbe #language-Wudu #language-Ayizo Gbe #language-Gbesi Gbe #language-Kotafon Gbe #language-Saxwe Gbe #language-Western Xwla Gbe #language-Xwela Gbe #language-Adangbe #language-Kpessi #language-Waci Gbe #language-Nyangbo #language-Tafi #language-Akebu #language-Animere #language-Igo #language-Ikposo #language-Tuwuli #language-Anii #language-Sekpele #language-Selee #language-Attié #language-Abé #language-Abidji #language-Adioukrou #language-Alladian #language-Avikam #language-Mbato #language-Krobu #language-Abron #language-Akan #language-Wasa #language-Twi #language-Anufo #language-Baoulé #language-Anyin Morofo #language-Ahanta #language-Nzima #language-Dompo #language-Gonja #language-Nkami #language-Nkonya #language-Nawuri #language-Foodo #language-Gikyode #language-Kplang #language-Krache #language-Chumburung #language-Tchumbuli #language-Nchumbulu #language-Awutu #language-Larteh #language-Cherepon #language-Gua #language-Abure #language-Beti (Côte d'Ivoire) #language-Day #language-Tunia #language-Bua #language-Bon Gula #language-Zan Gula #language-Gula Iro #language-Koke #language-Besme #language-Goundo #language-Kim #language-Lala-Roba #language-Bena (Nigeria) #language-Voro #language-Mághdì #language-Mak (Nigeria) #language-Kyak #language-Leelau #language-Moo #language-Dza #language-Mbum #language-Kare (Central African Republic) #language-Pana (Central African Republic) #language-Ndai #language-Mambai #language-Tupuri #language-Mono (Cameroon) #language-To #language-Pangseng #language-Rang #language-Bali (Nigeria) #language-Kpasam #language-Yotti #language-Teme #language-Waka #language-Yendang #language-Doyayo #language-Gimme #language-Gimnime #language-Mom Jango #language-Longto #language-Dii #language-Dugun #language-Duupa #language-Kolbila #language-Samba Leko #language-Wom (Nigeria) #language-Mbandja #language-Ngbundu #language-West Central Banda #language-Banda-Yangere #language-Banda-Mbrès #language-Banda-Banda #language-Banda-Bambari #language-Banda-Ndélé #language-Togbo-Vara Banda #language-Gobu #language-Kpagua #language-Mid-Southern Banda #language-Mono (Democratic Republic of Congo) #language-Ngundu #language-Langbashe #language-South Central Banda #language-Ma (Democratic Republic of Congo) #language-Dongo #language-Mba #language-Ndunga #language-Gbayi #language-Dendi (Central African Republic) #language-Mbangi #language-Northern Ngbandi #language-Southern Ngbandi #language-Yakoma #language-Riverain Sango #language-Mündü #language-Bangba #language-Mayogo #language-Gundi #language-Limassa #language-Baka (Cameroon) #language-Ganzi #language-Gilima #language-Ngbaka Ma'bo #language-Monzombo #language-Kpala #language-Yango #language-Feroge #language-Mangayat #language-Indri #language-Togoyo #language-Ndogo #language-Sere #language-Tagbu #language-Barambu #language-Pambia #language-Geme #language-Nzakara #language-Oblo #language-Gbanu #language-Manza #language-Ali #language-Ngbaka Manza #language-Gbaya-Mbodomo #language-Northwest Gbaya #language-Gbaya-Bozoum #language-Gbaya-Bossangoa #language-Suma #language-Southwest Gbaya #language-Viemo #language-Koromfé #language-Láá Láá Bwamu #language-Buli (Ghana) #language-Gourmanchéma #language-Bimoba #language-Moba #language-Akaselem #language-Yom #language-Kantosi #language-Mossi #language-Safaliba #language-Dagaari Dioula #language-Wali (Ghana) #language-Northern Dagara #language-Malba Birifor #language-Hanga #language-Kamara #language-Biali #language-Nateni #language-Ditammari #language-Mbelime #language-Baatonum #language-Dogosé #language-Khisa #language-Lama (Togo) #language-Lukpa #language-Bago-Kusuntu #language-Chala #language-Phuie #language-Winyé #language-Vagla #language-Chakali #language-Tampulma #language-Tumulung Sisaala #language-Western Sisaala #language-Pana (Burkina Faso) #language-Kasem #language-Northern Nuni #language-Southern Nuni #language-Dyan #language-Dijim-Bwilim #language-Awak #language-Tula #language-Bondoukou Kulango #language-Bouna Kulango #language-Loma (Côte d'Ivoire) #language-Téén #language-Northern Toussian #language-Southern Toussian #language-Eastern Karaboro #language-Western Karaboro #language-Mamara Senoufo #language-Nanerigé Sénoufo #language-Sìcìté Sénoufo #language-Supyire Senoufo #language-Syenara Senoufo #language-Shempire Senoufo #language-Nyarafolo Senoufo #language-Palaka Senoufo #language-Djimini Senoufo #language-Tagwana Senoufo #language-Miyobe #language-Aproumu Aizi #language-North Fali #language-South Fali #language-Jah Hut #language-Chewong #language-Kensiu #language-Kintaq #language-Jehai #language-Minriq #language-Batek #language-Temiar #language-Besisi #language-Semaq Beri #language-Semelai #language-Temoq #language-Cua #language-Katua #language-Takua #language-Monom #language-Todrah #language-Hre #language-Sedang #language-Kayong #language-Halang #language-Jeh #language-Halang Doan #language-Romam #language-Alak #language-Brao #language-Oy #language-Kavet #language-Krung #language-Laven #language-Sou #language-Maa #language-Chrau #language-Eastern Mnong #language-Central Mnong #language-Kraol #language-Southern Mnong #language-Budeh Stieng #language-Bulo Stieng #language-Mel-Khaonh #language-Tampuan #language-Talieng #language-Trieng #language-Pacoh #language-Eastern Katu #language-Western Katu #language-Lower Ta'oih #language-Upper Ta'oih #language-Eastern Bru #language-Northern Katang #language-Southern Katang #language-Sô #language-Western Bru #language-Nyeu #language-War-Jaintia #language-Hu #language-Man Met #language-Mok #language-Bit #language-Samtao #language-Eastern Lawa #language-Western Lawa #language-Rumai Palaung #language-Ruching Palaung #language-Shwe Palaung #language-Northern Khmer #language-Old Khmer #language-Mlabri #language-Khuen #language-O'du #language-Phong-Kniang #language-Mang #language-Bolyu #language-Bugan #language-Nyahkur #language-Old Mon #language-Gata' #language-Bodo Gadaba #language-Bondo #language-Birhor #language-Koda #language-Majhwar #language-Turi #language-Asuri #language-Bijori #language-Kodaku #language-Kol (Bangladesh) #language-Mahali #language-Juray #language-Car Nicobarese #language-Central Nicobarese #language-Arem #language-Chut #language-Hung #language-Tho #language-Nguôn #language-Puyuma #language-Atayal #language-Sakizaya #language-Basay #language-Ketangalan #language-Siraya #language-Ati #language-Enggano #language-Nasal #language-Basap #language-Dusun Malang #language-Dusun Deyah #language-Ampanang #language-Tunjung #language-Lawangan #language-Tawoyan #language-Kohin #language-Ot Danum #language-Siang #language-Inabaknon #language-Yakan #language-Pangutaran Sama #language-Indonesian Bajau #language-Mapun #language-West Coast Bajau #language-Balangingi #language-Central Sama #language-Southern Sama #language-Dusun Witu #language-Ma'anyan #language-Paku #language-Plateau Malagasy #language-Southern Betsimisaraka Malagasy #language-Antankarana Malagasy #language-Northern Betsimisaraka Malagasy #language-Tsimihety Malagasy #language-Tesaka Malagasy #language-Bara Malagasy #language-Tanosy Malagasy #language-Masikoro Malagasy #language-Bakumpai #language-Ngaju #language-Ibatan #language-Giangan #language-Tiruray #language-Tboli #language-Koronadal Blaan #language-Sarangani Blaan #language-Banggai #language-Bobongko #language-Batui #language-Moronene #language-Bahonsuai #language-Bungku #language-Koroni #language-Kulisusu #language-Mori Bawah #language-Taloki #language-Wawonii #language-Mori Atas #language-Padoe #language-Tomadino #language-Kodeoha #language-Rahambuu #language-Tolaki #language-Waru #language-Kumbewaha #language-Lasalimu #language-Busoa #language-Kaimbulawa #language-Kioko #language-Liabuku #language-Pancana #language-Bonerate #language-Tukang Besi North #language-Tukang Besi South #language-Dondo #language-Lauje #language-Tomini #language-Balaesang #language-Dampelas #language-Pendau #language-Taje #language-Tajio #language-Topoiyo #language-Sedoa #language-Baras #language-Da'a Kaili #language-Ledo Kaili #language-Unde Kaili #language-Moma #language-Tado #language-Pamona #language-Tombelala #language-Sarudu #language-Wotu #language-Kamaru #language-Wolio #language-Pampanga #language-Ambala Ayta #language-Botolan Sambal #language-Mag-Indi Ayta #language-East Tarangan #language-West Tarangan #language-Batuley #language-Mariri #language-Lola #language-Lorang #language-Manombai #language-Dobel #language-Koba #language-Barakai #language-Karey #language-Ujir #language-Kola #language-Kompane #language-Kedang #language-Sika #language-Lamaholot #language-Lewotobi #language-Lamalera #language-Ile Ape #language-West Lembata #language-Lamatuka #language-Lewo Eleng #language-Kepo' #language-Komodo #language-Manggarai #language-Riung #language-Rembong #language-Rajong #language-Ende #language-Li'o #language-Nage #language-Ngad'a #language-Rongga #language-Eastern Ngad'a #language-Kambera #language-Mamboru #language-Anakalangu #language-Wanukaka #language-Lamboya #language-Laura #language-Banda (Indonesia) #language-Watubela #language-Bati (Indonesia) #language-Geser-Gorom #language-Bobot #language-Benggoi #language-Liana-Seti #language-Salas #language-Huaulu #language-North Nuaulu #language-South Nuaulu #language-Sepa (Indonesia) #language-Paulohi #language-Kaibobo #language-Laha (Indonesia) #language-Seit-Kaitetu #language-Hitu #language-Tulehu #language-Kamarian #language-Haruku #language-Amahai #language-Nusa Laut #language-Latu #language-Saparua #language-Asilulu #language-Boano (Maluku) #language-Larike-Wakasihu #language-Wemale #language-Hulung #language-Lisabata-Nuniali #language-Loun #language-Alune #language-Naka'ela #language-Kur #language-Teor #language-Buru (Indonesia) #language-Mangole #language-Kadai #language-Taliabu #language-Kei #language-Yamdena #language-Onin #language-Sekar #language-Uruangnirin #language-Helong #language-Idaté #language-Lakalei #language-Habu #language-Tetun Dili #language-Kairui-Midiki #language-Nauete #language-Waima'a #language-Amarasi #language-Baikeno #language-Maku'a #language-Dai #language-Dawera-Daweloor #language-North Babar #language-Central Masela #language-East Masela #language-Serili #language-Southeast Babar #language-West Masela #language-Emplawas #language-Imroing #language-Tela-Masbuar #language-Kisar #language-Roma #language-Leti (Indonesia) #language-Selaru #language-Seluwasan #language-Te'un #language-Nila #language-Serua #language-Ili'uun #language-Tugun #language-Aputai #language-Perai #language-Mambae #language-Welaun #language-Kemak #language-Tukudede #language-Pak-Tong #language-Andra-Hus #language-Leipon #language-Ponam #language-Lele (Papua New Guinea) #language-Nali #language-Ere #language-Kele (Papua New Guinea) #language-Elu #language-Loniu #language-Mokerang #language-Bipi #language-Hermit #language-Nyindrou #language-Sori-Harengan #language-Mondropolon #language-Tulu-Bohuai #language-Likum #language-Lenkau #language-Nauna #language-Penchal #language-Lou #language-Pam #language-Seimat #language-Wuvulu-Aua #language-Kaniet #language-Gone Dau #language-Lauan #language-Lomaiviti #language-Anuta #language-East Futuna #language-Rennell-Bellona #language-Tikopia #language-Niuafo'ou #language-Niuatoputapu #language-Tuvalu #language-Pukapuka #language-Tokelau #language-Sikaiana #language-Nukumanu #language-Nukuria #language-Takuu #language-Rapanui #language-North Marquesan #language-South Marquesan #language-Maori #language-Rakahanga-Manihiki #language-Austral #language-Futuna-Aniwa #language-Tonga (Tonga Islands) #language-Namosi-Naitasiri-Serua #language-Western Fijian #language-Pingelapese #language-Mapia #language-Woleaian #language-Mortlockese #language-Puluwatese #language-Satawalese #language-Namonuito #language-Pááfang #language-Tanapag #language-Sonsorol #language-Kosraean #language-Nauru #language-Paama #language-North Ambrym #language-Lelepa #language-Eton (Vanuatu) #language-South Efate #language-Baki #language-Bierebo #language-Bieria #language-Maii #language-Lamenu #language-Lewo #language-Uripiv-Wala-Rano-Atchin #language-Aulua #language-Burmbar #language-Maskelynes #language-Axamb #language-Port Sandwich #language-Rerep #language-Unua #language-Malua Bay #language-Mpotovoro #language-Vao #language-Larevat #language-Maragus #language-Dixon Reef #language-Nasarian #language-Letemboi #language-Repanbitip #language-Apma #language-Sa #language-Seke (Vanuatu) #language-Sowa #language-Hano #language-East Ambae #language-West Ambae #language-Mafea #language-Tutuba #language-Polonombauk #language-Tambotalo #language-Ngen #language-Aore #language-Araki #language-Sakao #language-Tolomako #language-Nokuku #language-Piamatsina #language-Tasmate #language-Valpei #language-Vunapu #language-Amblong #language-Morouas #language-Narango #language-Merei #language-Navut #language-Tiale #language-Akei #language-Baetora #language-Central Maewo #language-Lehalurup #language-Merlav #language-Mota #language-Nume #language-Vurës #language-Hiw #language-Lo-Toga #language-Lakon #language-Koro (Vanuatu) #language-Lemerig #language-Vera'a #language-Bughotu #language-Gela #language-Ghari #language-Lengo #language-Malango #language-Birao #language-Talise #language-Longgu #language-Sa'a #language-Kwaio #language-Wala #language-Baelelea #language-Fataleka #language-To'abaita #language-'Are'are #language-Dori'o #language-Oroha #language-Arosi #language-Fagani #language-Dehu #language-Nengone #language-Nêlêmwa-Nixumwak #language-Jawe #language-Pwaamei #language-Pije #language-Fwâi #language-Nemi #language-Cemuhî #language-Paicî #language-Hmwaveke #language-Vamale #language-Waamwang #language-Haveke #language-Bwatoo #language-Dumbea #language-Neku #language-Xârâcùù #language-Ajië #language-Arhâ #language-Arhö #language-Tiri #language-Aneityum #language-Ifo #language-Sie #language-Ura (Vanuatu) #language-North Tanna #language-Whitesands #language-Southwest Tanna #language-Mussau-Emira #language-Tenis #language-Nalögo #language-Natügu #language-Malo #language-Neo #language-Teanu #language-Amba (Solomon Islands) #language-Asumboa #language-Tomoip #language-Barok #language-Lavatbura-Lamusong #language-Madak #language-Konomala #language-Sursurunga #language-Kandas #language-Ramoaaina #language-Bilur #language-Label #language-Ririo #language-Babatana #language-Vaghua #language-Varisi #language-Torau #language-Uruava #language-Solos #language-Nehan #language-Papapana #language-Petats #language-Hakö #language-Halia #language-Hahon #language-Teop #language-Kazukuru #language-Ughele #language-Marovo #language-Vangunu #language-Roviana #language-Hoava #language-Kusaghe #language-Duke #language-Simbo #language-Lungga #language-Lawunuia #language-Blablanga #language-Zazao #language-Cheke Holo #language-Gao #language-Laghu #language-Zabana #language-Guramalum #language-Kuanua #language-Fanamaket #language-Warwar Feni #language-Niwer Mil #language-Mandara #language-Notsi #language-Kara (Papua New Guinea) #language-Nalik #language-Tiang #language-Tigak #language-Tungag #language-Bola #language-Bulu (Papua New Guinea) #language-Numbami #language-Labu #language-Aribwaung #language-Musom #language-Nafi #language-Adzera #language-Mari (Madang Province) #language-Sarasira #language-Sukurum #language-Wampur #language-Middle Watut #language-North Watut #language-South Watut #language-Bugawac #language-Kela (Papua New Guinea) #language-Iwal #language-Kapin #language-Piu #language-Vehes #language-Gorakor #language-Dambi #language-Kumalu #language-Patep #language-Zenag #language-Yamap #language-Bariai #language-Kove #language-Gitua #language-Maleu-Kilenge #language-Mbula #language-Sio #language-Tami #language-Mato #language-Ronji #language-Awad Bing #language-Mindiri #language-Wab #language-Gedaged #language-Marik #language-Matukar #language-Takia #language-Arop-Lokep #language-Karnai #language-Lote #language-Mamusi #language-Mengen #language-Amara #language-Akolet #language-Avau #language-Aiklep #language-Gimi (West New Britain) #language-Solong #language-Bebeli #language-Mangseng #language-Aighon #language-Karore #language-Kaulong #language-Miu #language-Sengseng #language-Lamogai #language-Mouk-Aria #language-Kayupulau #language-Ormu #language-Bonggo #language-Kaptiau #language-Masimasi #language-Tarpia #language-Liki #language-Sobei #language-Kairiru #language-Kaiep #language-Terebu #language-Medebur #language-Biem #language-Manam #language-Sepa (Papua New Guinea) #language-Kis #language-Wogeo #language-Ulau-Suain #language-Kap #language-Tumleo #language-Sera #language-Arop-Sissano #language-Malol #language-Sissano #language-Anuki #language-Gumawana #language-Maisin #language-Arifama-Miniafia #language-Ubir #language-Are #language-Doga #language-Gapapaiwa #language-Ghayavi #language-Minaveha #language-Tawala #language-Gweda #language-Haigwai #language-Maiwala #language-Taupota #language-Wa'ema #language-Yaleba #language-Wedau #language-Yakaikeke #language-Koluwawa #language-Bwaidoka #language-Iduna #language-Iamalele #language-Maiadomu #language-Dobu #language-Duau #language-Sewa Bay #language-Boselewa #language-Galeya #language-Bunama #language-Mwatebu #language-Dawawa #language-Kakabai #language-'Auhelawa #language-Buhutu #language-Bwanabwana #language-Oya'oya #language-Unubahe #language-Wagawaga #language-Saliba #language-Suau #language-Ouma #language-Bina (Papua New Guinea) #language-Magori #language-Yoba #language-Sinaugoro #language-Hula #language-Keapara #language-Abadi #language-Motu #language-Kuni #language-Lala #language-Mekeo #language-Toura (Papua New Guinea) #language-Waima #language-Budibud #language-Kilivila #language-Muyuw #language-Nimoa #language-Sudest #language-Nguluwan #language-Mor (Mor Islands) #language-Tandia #language-Waropen #language-Arguni #language-Bedoanas #language-Erokwanas #language-Dusner #language-Meoswar #language-Roon #language-Yeretuar #language-Yaur #language-Ambai #language-Ansus #language-Marau #language-Woi #language-Wamesa #language-Munggui #language-Papuma #language-Pom #language-Busami #language-Serui-Laut #language-Kurudu #language-Wabo #language-Yoke #language-As #language-Biga #language-Waigeo #language-Matbat #language-Kawe #language-Legenyem #language-Wauyai #language-Salawati #language-Buli (Indonesia) #language-Maba (Indonesia) #language-Patani #language-East Makian #language-Gane #language-Umiray Dumaget Agta #language-Bikol #language-Mamanwa #language-Alabat Island Agta #language-Isarog Agta #language-Mt. Iriga Agta #language-Mt. Iraya Agta #language-Bantoanon #language-Porohanon #language-Masbatenyo #language-Baybayanon #language-Kinabalian #language-Waray (Philippines) #language-Northern Binukidnon #language-Southern Binukidnon #language-Butuanon #language-Surigaonon #language-Tandaganon #language-Ata #language-Inonhan #language-Sulod #language-Cuyonon #language-Caluyanun #language-Davawenyo #language-Kamayo #language-Kagan Kalagan #language-Kalagan #language-Kasiguranin #language-Maranao #language-Bintauna #language-Kaidipang #language-Lolak #language-Suwawa #language-Mongondow #language-Ponosakan #language-Ata Manobo #language-Matigsalug Manobo #language-Agusan Manobo #language-Dibabawon Manobo #language-Rajah Kabunsuwan Manobo #language-Obo Manobo #language-Ilianen Manobo #language-Western Bukidnon Manobo #language-Tagabawa #language-Cotabato Manobo #language-Sarangani Manobo #language-Kagayanen #language-Higaonon #language-Tagbanwa #language-Batak #language-Central Tagbanwa #language-Molbog #language-Central Palawano #language-Brooke's Point Palawano #language-Southwest Palawano #language-Eastern Tawbuid #language-Western Tawbuid #language-Central Subanen #language-Eastern Subanen #language-Northern Subanen #language-Kolibugan Subanon #language-Western Subanon #language-Kawi #language-Caribbean Javanese #language-New Caledonian Javanese #language-Osing #language-Tengger #language-Agutaynen #language-Lampung Nyo #language-Lampung Api #language-Benyadu' #language-Rara Bakati' #language-Biatah Bidayuh #language-Tringgus-Sembaan Bidayuh #language-Bukar-Sadung Bidayuh #language-Ribun #language-Sanggau #language-Semandang #language-Sasak #language-Haroi #language-Eastern Cham #language-Western Cham #language-Cacgia Roglai #language-Chru #language-Southern Roglai #language-Northern Roglai #language-Tsat #language-Bih #language-Rade #language-Duano #language-Haji #language-Malayic Dayak #language-Old Malay #language-Keninjal #language-Seberuang #language-Beginci #language-Gerai #language-Cocos Islands Malay #language-Peranakan Indonesian #language-Kubu #language-Musi #language-Kota Bangun Kutai Malay #language-Banjar #language-Bukit Malay #language-Berau Malay #language-Sabah Malay #language-Bacanese Malay #language-Brunei #language-Jambi Malay #language-Bangka #language-Lubu #language-Negeri Sembilan Malay #language-Pekal #language-Balinese Malay #language-Jakun #language-Central Malay #language-Orang Kanaq #language-Orang Seletar #language-Tenggarong Kutai Malay #language-Kedah Malay #language-Pattani Malay #language-Standard Malay #language-Baba Malay #language-Makassar Malay #language-Malaccan Creole Malay #language-Kupang Malay #language-Larantuka Malay #language-Papuan Malay #language-Ambonese Malay #language-Banda Malay #language-Gorap #language-Manado Malay #language-North Moluccan Malay #language-Badui #language-Tonsawang #language-Tontemboan #language-Tondano #language-Tonsea #language-Moken #language-Moklen #language-Sikule #language-Batak Alas-Kluet #language-Batak Dairi #language-Batak Toba #language-Batak Angkola #language-Batak Mandailing #language-Alangan #language-Iraya #language-Tadyawan #language-Arta #language-Iloko #language-Isnag #language-Adasen #language-Ibanag #language-Faire Atta #language-Pamplona Atta #language-Pudtol Atta #language-Central Cagayan Agta #language-Itawit #language-Yogad #language-Ga'dang #language-Gaddang #language-Northern Alta #language-Southern Alta #language-Binongan Itneg #language-Inlaod Itneg #language-Lubuagan Kalinga #language-Butbut Kalinga #language-Tanudan Kalinga #language-Masadiit Itneg #language-Moyadan Itneg #language-Limos Kalinga #language-Banao Itneg #language-Mabaka Valley Kalinga #language-Balangao #language-Isinai #language-Bontok #language-Southern Bontok #language-Kankanaey #language-Maeng Itneg #language-Northern Kankanay #language-Amganad Ifugao #language-Tuwali Ifugao #language-Batad Ifugao #language-Mayoyao Ifugao #language-Ilongot #language-I-Wak #language-Kalanguya #language-Karao #language-Dupaninan Agta #language-Paranan #language-Dicamay Agta #language-Murik (Malaysia) #language-Bahau #language-Baram Kayan #language-Kayan River Kayan #language-Mendalam Kayan #language-Busang Kayan #language-Kayan Mahakam #language-Rejang Kayan #language-Modang #language-Segai #language-West Berawan #language-Central Berawan #language-East Berawan #language-Kiput #language-Tutong #language-Lelak #language-Kelabit #language-Lengilu #language-Lundayeh #language-Sa'ban #language-Tring #language-Uma' Lung #language-Uma' Lasan #language-Eastern Penan #language-Sebop #language-Western Penan #language-Bolongan #language-Bonggi #language-Ida'an #language-Lotud #language-Sabah Bisaya #language-Brunei Bisaya #language-Kimaragang #language-Klias River Kadazan #language-Kota Marudu Talantang #language-Kuijau #language-Tobilung #language-Kadazan Dusun #language-Minokok #language-Sugut Dusun #language-Rungus #language-Dumpas #language-Labuk-Kinabatangan Kadazan #language-Abai Sungai #language-Serudung Murut #language-Tombonuo #language-Lanas Lobu #language-Tampias Lobu #language-Upper Kinabatangan #language-Papar #language-Selungai Murut #language-Sembakung Murut #language-Gana #language-Paluan #language-Timugon Murut #language-Tagal Murut #language-Burusu #language-Northern Tidung #language-Southern Tidung #language-Sekapan #language-Kajaman #language-Lahanan #language-Central Melanau #language-Daro-Matu Melanau #language-Kanowit-Tanjong Melanau #language-Sibu Melanau #language-Aoheng #language-Kereho #language-Punan Aput #language-Punan Merah #language-Punan Batu 1 #language-Sihan #language-Bukat #language-Bukitan #language-Ukit #language-Punan Tubu #language-Punan Bah-Biau #language-Talaud #language-Sangir #language-Sangil #language-Bantik #language-Ratahan #language-Campalagian #language-Embaloh #language-Taman (Indonesia) #language-Coastal Konjo #language-Bentong #language-Makasar #language-Mamuju #language-Mandar #language-Maiwa (Indonesia) #language-Malimpung #language-Dakka #language-Pannei #language-Ulumanda' #language-Kalumpang #language-Mamasa #language-Tae' #language-Talondo' #language-Toraja-Sa'dan #language-Rampi #language-Bada (Indonesia) #language-Besoa #language-Napu #language-Seko Tengah #language-Seko Padang #language-Boano (Sulawesi) #language-Totoli #language-Kulon #language-Pazeh #language-Babuza #language-Papora #language-Central Aymara #language-Southern Aymara #language-Baibai #language-Kairak #language-Simbali #language-Ura (Papua New Guinea) #language-Makolkol #language-Guambiano #language-Totoro #language-Awa-Cuaiquer #language-Awbono #language-Bayono #language-Aduge #language-Ahirani #language-Anasi #language-Áncá #language-Arakwal #language-xss #language-Baga Kaloum #language-Baga Sobané #language-Bainouk-Samik #language-Bhalay #language-Bubia #language-Bumang #language-Buraka #language-Buso #language-Chetco #language-Chuanqiandian Cluster Miao #language-Con #language-Desiya #language-Foma #language-Fum #language-Gengle #language-Gowli #language-Gowlan #language-Idesa #language-Ihievbe #language-Inpui Naga #language-Ir #language-Jiarong #language-Judeo-Berber #language-Kang #language-Kayort #language-Kemiehua #language-Khao #language-Khua #language-Kisankasa #language-Kofa #language-Koko Babangk #language-Kon Keu #language-Kosena #language-Kpatili #language-Kuanhua #language-Kukna #language-Kuku-Mangk #language-Kumbaran #language-Laba #language-Lahta Karen #language-Lambichhong #language-Lang'e #language-Laopang #language-Laos Sign Language #language-Lenca #language-Loarki #language-Lopi #language-Lumba-Yakkha #language-Malay (individual language) #language-Mawayana #language-Mirgan #language-Munda #language-Nde-Gbite #language-Ndonde Hamba #language-Ngombe (Central African Republic) #language-nom #language-Norra #language-Northwestern Fars #language-tmk #language-Katukína #language-Nupbikha #language-Odut #language-Old Turkish #language-Olkol #language-Ontenu #language-Parsi #language-Parsi-Dari #language-Phangduwali #language-Pokangá #language-Puimei Naga #language-Punan Merap #language-Putoh #language-Quetzaltepec Mixe #language-Rufiji #language-Salumá #language-szd #language-Shuadit #language-Singapore Sign Language #language-Southwestern Nisu #language-Southern Lolopo #language-Southeastern Puebla Nahuatl #language-Tareng #language-Tawang Monpa #language-Tetete #language-Thu Lao #language-Tingui-Boto #language-Uradhi #language-Wahau Kayan #language-Xinca #language-Yamongeri #language-Yarsun #language-Yauma #language-Akyaung Ari Naga #language-Dawik Kui #language-Ekai Chin #language-Laitu Chin #language-Lao Naga #language-Ponyo-Gongwang Naga #language-Rungtu Chin #language-Songlai Chin #language-Ningera #language-Ainbai #language-Kilmeri #language-Pagi #language-Awyi #language-Amanab #language-Auwe #language-Daonda #language-Imonda #language-Senggi #language-Waris #language-Sowanda #language-Umeda #language-Umotína #language-Otuke #language-Kasua #language-Onobasulu #language-Sonia #language-Beami #language-Edolo #language-Gooniyandi #language-Kitsai #language-Pawnee #language-Apalaí #language-Galibi Carib #language-Akurio #language-Trió #language-Wayana #language-Kuikúro-Kalapálo #language-Matipuhy #language-Kaxuiâna #language-Hixkaryána #language-Waiwai #language-Bakairí #language-Tamanaku #language-Chaima #language-Mapoyo #language-Pémono #language-Yabarana #language-Macushi #language-Patamona #language-Akawaio #language-Waimiri-Atroari #language-Japrería #language-Ndrulo #language-Lombi #language-Asoa #language-Mamvu #language-Mangbutu #language-Bendi #language-Efe #language-Mvuba #language-Birri #language-Aringa #language-Avokaya #language-Logo #language-Lugbara #language-Keliko #language-Omi #language-Olu'bo #language-Southern Ma'di #language-Bongo #language-Baka (South Sudan) #language-Beli (South Sudan) #language-Mittu #language-Mo'da #language-Morokodo #language-Jur Modo #language-Nyamusa-Molo #language-Gula (Central African Republic) #language-Kara (Central African Republic) #language-Vale #language-Kenga #language-Jaya #language-Gula (Chad) #language-Morom #language-Berakou #language-Naba #language-Horo #language-Ngambay #language-Laka (Chad) #language-Gor #language-Mango #language-Dagba #language-Sara Kaba #language-Sara Kaba Náà #language-Sara Kaba Deme #language-Kulfa #language-Torá #language-Itene #language-Oro Win #language-Pech #language-Buglere #language-Ngäbere #language-Border Kuna #language-San Blas Kuna #language-Boruca #language-Cabécar #language-Cogui #language-Malayo #language-Angosturas Tunebo #language-Barro Negro Tunebo #language-Central Tunebo #language-Western Tunebo #language-Maléku Jaíka #language-Wasco-Wishram #language-Woun Meu #language-Emberá-Catío #language-Emberá-Baudó #language-Northern Emberá #language-Epena #language-Emberá-Tadó #language-Emberá-Chamí #language-Anserma #language-Caramanta #language-Alutor #language-Kerek #language-Barbareño #language-Ineseño #language-Purisimeño #language-Cochimi #language-Cocopa #language-Havasupai-Walapai-Yavapai #language-Mohave #language-Comecrudo #language-Garza #language-Onjob #language-Turaka #language-Maiwa (Papua New Guinea) #language-Daga #language-Mapena #language-Ginuman #language-Logorik #language-Dar Daju Daju #language-Dar Sila Daju #language-Njalgulgule #language-Baygo #language-Dar Fur Daju #language-Dizin #language-Nayi #language-Sheko #language-Donno So Dogon #language-Tommo So Dogon #language-Toro So Dogon #language-Bankan Tey Dogon #language-Ben Tey Dogon #language-Dogul Dom Dogon #language-Tebul Ure Dogon #language-Ana Tinga Dogon #language-Yanda Dom Dogon #language-Jamsay Dogon #language-Toro Tegu Dogon #language-Tomo Kan Dogon #language-Tiranige Diga Dogon #language-Ampari Dogon #language-Bunoge Dogon #language-Mombo Dogon #language-Doso #language-Turumsa #language-Northwestern Kolami #language-Southeastern Kolami #language-Mudhili Gadaba #language-Pottangi Ollar Gadaba #language-Kumarbhag Paharia #language-Sauria Paharia #language-Alu Kurumba #language-Holiya #language-Jennu Kurumba #language-Sholaga #language-Kannada #language-Kota (India) #language-Toda #language-Attapady Kurumba #language-Muduga #language-Kodava #language-Allar #language-Aranadan #language-Kadar #language-Kurichiya #language-Malankuravan #language-Malavedan #language-Malayalam #language-Malaryan #language-Mullu Kurumba #language-Thachanadan #language-Vishavan #language-Wayanad Chetti #language-Kalanadi #language-Kunduvadi #language-Pathiya #language-Ravula #language-Mala Malasar #language-Malapandaram #language-Old Tamil #language-Malasar #language-Mannan #language-Paliyan #language-Kaikadi #language-Pattapu #language-Yerukula #language-Korra Koraga #language-Mudu Koraga #language-Bellari #language-Kudiya #language-Northern Gondi #language-Eastern Muria #language-Western Muria #language-Adilabad Gondi #language-Aheri Gondi #language-Far Western Muria #language-Maria (India) #language-Dandami Maria #language-Konda-Dora #language-Kui (India) #language-Manda (India) #language-Pengo #language-Mukha-Dora #language-Waddar #language-Manna-Dora #language-Khirwar #language-Kamu #language-Kelo #language-Molo #language-Konai #language-Odoodee #language-Kubo #language-Samo #language-Fiwaga #language-Foi #language-Bine #language-Gizrra #language-Mednyj Aleut #language-Eastern Canadian Inuktitut #language-Kalaallisut #language-North Alaskan Inupiatun #language-Inuinnaqtun #language-Pacific Gulf Yupik #language-Garrwa #language-Wanyi #language-Bauzi #language-Demisa #language-Tefaro #language-Woria #language-Barapasi #language-Kofei #language-Sauri #language-Burate #language-Tunggare #language-Mangerr #language-Erre #language-Urningangg #language-Yemsa #language-Anfillo #language-Boro (Ethiopia) #language-Shekkacho #language-Chara #language-Koorete #language-Zayse-Zergulla #language-Basketo #language-Male (Ethiopia) #language-Dorze #language-Melo #language-Oyda #language-Wolaytta #language-Dawro #language-Gamo #language-Gofa #language-Mixed Great Andamanese #language-Cuiba #language-Playero #language-Kadiwéu #language-Abipon #language-Mocoví #language-Pilagá #language-Toba #language-Ngandi #language-Kunbarlang #language-Northern Haida #language-Southern Haida #language-Amarakaeri #language-Huachipaeri #language-Hatam #language-Ko #language-Warnang #language-Tira #language-Hibito #language-Jiongnai Bunu #language-Eastern Qiandong Miao #language-Northern Qiandong Miao #language-Southern Qiandong Miao #language-Eastern Xiangxi Miao #language-Western Xiangxi Miao #language-Bu-Nao Bunu #language-Ge #language-Luopohe Hmong #language-Hmong Daw #language-Horned Miao #language-Hmong Njua #language-Hmong Don #language-Hmong Dô #language-Northern Guiyang Hmong #language-Southern Guiyang Hmong #language-Southwestern Guiyang Hmong #language-Central Huishui Hmong #language-Eastern Huishui Hmong #language-Northern Huishui Hmong #language-Southwestern Huishui Hmong #language-Central Mashan Hmong #language-Northern Mashan Hmong #language-Southern Mashan Hmong #language-Western Mashan Hmong #language-Pa-Hng #language-Wunai Bunu #language-Younuo Bunu #language-Biao-Jiao Mien #language-Biao Mon #language-Kim Mun #language-Murui Huitoto #language-Hurrian #language-Urartian #language-Southeast Ijo #language-Nkoroo #language-Ibani #language-Kirike #language-Oruma #language-Biseni #language-Duriankere #language-Palaic #language-Carian #language-Cuneiform Luwian #language-Hieroglyphic Luwian #language-Pisidian #language-Lydian #language-Sidetic #language-Venetic #language-Gheg Albanian #language-Arbëreshë Albanian #language-Arvanitika Albanian #language-Classical Armenian #language-Middle Armenian #language-Western Armenian #language-Standard Latvian #language-Old Lithuanian #language-Old Russian #language-Church Slavic #language-Slavomolisano #language-Slovenian #language-Celtiberian #language-Galatian #language-Cisalpine Gaulish #language-Lepontic #language-Transalpine Gaulish #language-Middle Welsh #language-Old Welsh #language-Middle Breton #language-Old Breton #language-Old Cornish #language-Scottish Gaelic #language-Hiberno-Scottish Gaelic #language-Noric #language-Gothic #language-Elfdalian #language-Jutish #language-Old Norse #language-Norwegian Bokmål #language-Norwegian Nynorsk #language-Yiddish #language-Lower Silesian #language-Upper Saxon #language-Eastern Yiddish #language-Western Yiddish #language-Kölsch #language-Limburgan #language-Hunsrik #language-Pennsylvania German #language-Old High German (ca. 750-1050) #language-Colonia Tovar German #language-Swabian #language-Walser #language-Bavarian #language-Hutterite German #language-Unserdeutsch #language-Javindo #language-Petjo #language-Afrikaans #language-Oorlams #language-Berbice Creole Dutch #language-Negerhollands #language-Skepi Creole Dutch #language-Zeeuws #language-Old Dutch #language-Old Saxon #language-Low German #language-Middle Low German #language-Plautdietsch #language-Gronings #language-Achterhoeks #language-Drents #language-Sallands #language-Stellingwerfs #language-Twents #language-Veluws #language-Old English (ca. 450-1100) #language-Yola #language-Pitcairn-Norfolk #language-English #language-Virgin Islands Creole English #language-Bajan #language-Guyanese Creole English #language-Trinidadian Creole English #language-Antigua and Barbuda Creole English #language-Afro-Seminole Creole #language-Sea Island Creole English #language-Bahamas Creole English #language-Turks And Caicos Creole English #language-Vincentian Creole English #language-Grenadian Creole English #language-Tobagonian Creole English #language-Jamaican Creole English #language-Belize Kriol English #language-Nicaragua Creole English #language-Sranan Tongo #language-Kwinti #language-Krio #language-Ghanaian Pidgin English #language-Cameroon Pidgin #language-Nigerian Pidgin #language-Hawai'i Creole English #language-Kriol #language-Bislama #language-Pijin #language-Tok Pisin #language-Torres Strait Creole #language-Northern Frisian #language-Old Frisian #language-Western Frisian #language-Phrygian #language-Mycenaean Greek #language-Romano-Greek #language-Cappadocian Greek #language-Pontic #language-Mysian #language-Khowar #language-Sanskrit #language-Gawar-Bati #language-Shumashti #language-Grangali #language-Bhunjia #language-Kamar #language-Nahari #language-Kharia Thar #language-Lodhi #language-Tangchangya #language-Kurmukar #language-Naga Pidgin #language-Rajbanshi #language-Kupia #language-Lahnda #language-Western Panjabi #language-Northern Hindko #language-Southern Hindko #language-Pahari #language-Khetrani #language-Luwati #language-Sindhi Bhil #language-Lasi #language-Katkari #language-Goan Konkani #language-Old Marathi #language-Samvedi #language-Varhadi-Nagpuri #language-Andh #language-Rajasthani #language-Dubli #language-Kachi Koli #language-Vaghri #language-Wadiyara Koli #language-Merwari #language-Jandavra #language-Hadothi #language-Gade Lohar #language-Godwari #language-Marwari (India) #language-Bhaya #language-Goaria #language-Lambadi #language-Marwari (Pakistan) #language-Parkari Koli #language-Bauria #language-Dungra Bhil #language-Gamit #language-Mawchi #language-Vaagri Booli #language-Wagdi #language-Adiwasi Garasia #language-Rajput Garasia #language-Bhilali #language-Rathawi #language-Noiri #language-Dotyali #language-Jaunsari #language-Mandeali #language-Bhattiyali #language-Bilaspuri #language-Chambeali #language-Pangwali #language-Churahi #language-Bhadrawahi #language-Lahul Lohar #language-Kullu Pahari #language-Mahasu Pahari #language-Dhanki #language-Khandesi #language-Pali #language-Angika #language-Caribbean Hindustani #language-Kisan #language-Kudmali #language-Panchpargania #language-Oraon Sadri #language-Sadri #language-Rana Tharu #language-Chitwania Tharu #language-Kathoriya Tharu #language-Kochila Tharu #language-Dangaura Tharu #language-Sonha #language-Buksa #language-Majhi #language-Musasa #language-Kumhali #language-Darai #language-Dewas Rai #language-Powari #language-Surgujia #language-Domaaki #language-Balkan Romani #language-Baltic Romani #language-Caló #language-Kalo Finnish Romani #language-Braj #language-Kanauji #language-Bharia #language-Bundeli #language-Andaman Creole Hindi #language-Fiji Hindi #language-Hindi #language-Urdu #language-Ghera #language-Gurgula #language-Od #language-Khah #language-Wotapuri-Katarqalai #language-Indus Kohistani #language-Chilisso #language-Gowro #language-Mankiyali #language-Tirahi #language-Brokskat #language-Shina #language-Kohistani Shina #language-Ushojo #language-Savi #language-Dhivehi #language-Veddah #language-Avestan #language-Eastern Balochi #language-Koroshi #language-Southern Balochi #language-Western Balochi #language-Rudbari #language-Shahmirzadi #language-Gazi #language-Natanzi #language-Soi #language-Nayini #language-Lasgerdi #language-Sangisari #language-Sorkhei #language-Kurdish #language-Central Kurdish #language-Northern Kurdish #language-Southern Kurdish #language-Zaza #language-Gurani #language-Bajelani #language-Sarli #language-Kho'ini #language-Maraghei #language-Kajali #language-Kabatei #language-Upper Taromi #language-Harzani #language-Alviri-Vidari #language-Eshtehardi #language-Razajerdi #language-Takestani #language-Ashtiani #language-Vafsi #language-Old Ossetic #language-Yagnobi #language-Yazgulyam #language-Ormuri #language-Parachi #language-Waneci #language-Central Pashto #language-Northern Pashto #language-Southern Pashto #language-Khotanese #language-Tumshuqese #language-Old Persian (ca. 600-400 B.C.) #language-Pahlavi #language-Kumzari #language-Judeo-Tat #language-Muslim Tat #language-Judeo-Persian #language-Aimaq #language-Dari #language-Hazaragi #language-Bukharic #language-Lari #language-Dezfuli #language-Northern Luri #language-Bakhtiari #language-Southern Luri #language-Ashkun #language-Kamviri #language-Tregami #language-Faliscan #language-Latin #language-Istro Romanian #language-Megleno Romanian #language-Judeo-Italian #language-Sassarese Sardinian #language-Romagnol #language-Piemontese #language-Old French (842-ca. 1400) #language-Cajun French #language-Réunion Creole French #language-Tayo #language-Haitian #language-Guianese Creole French #language-Saint Lucian Creole French #language-Guadeloupean Creole French #language-San Miguel Creole French #language-Morisyen #language-Seselwa Creole French #language-Arpitan #language-Old Spanish #language-Ladino #language-Palenquero #language-Chavacano #language-Ternateño #language-Fala #language-Angolar #language-Principense #language-Sãotomense #language-Macanese #language-Timor Pidgin #language-Kabuverdianu #language-Papiamento #language-Upper Guinea Crioulo #language-Mozarabic #language-Gallurese Sardinian #language-Campidanese Sardinian #language-Logudorese Sardinian #language-Oscan #language-Umbrian #language-Hernican #language-Marrucinian #language-Paelignian #language-Vestinian #language-Sabine #language-South Picene #language-Aequian #language-Marsian #language-Volscian #language-Tokharian A #language-Tokharian B #language-Dacian #language-Lusitanian #language-Messapic #language-Thracian #language-Irántxe #language-Laurentian #language-Susquehannock #language-Nottoway #language-Wendat #language-Amurdak #language-Garig-Ilgar #language-Iwaidja #language-Old Japanese #language-Kikai #language-Oki-No-Erabu #language-Toku-No-Shima #language-Northern Amami-Oshima #language-Southern Amami-Oshima #language-Central Okinawan #language-Miyako #language-Jarawa (India) #language-Önge #language-Achuar-Shiwiar #language-Huambisa #language-Keiga #language-Tulishi #language-Krongo #language-Tumtum #language-Kanga #language-Katcha-Kadugli-Miri #language-Nukak Makú #language-Kamakan #language-Aekyom #language-Old Georgian #language-Judeo-Georgian #language-Katawixi #language-Kosadle #language-Qawasqar #language-Ap Ma #language-Eastern Keres #language-Western Keres #language-Korana #language-Xiri #language-Shua #language-Kua #language-Kxoe #language-Naro #language-Piro #language-Tiwa #language-Southern Tiwa #language-Bamu #language-Northeast Kiwai #language-Southern Kiwai #language-Waboda #language-Kerewo #language-Morigi #language-Ese #language-Ömie #language-Namiae #language-Barai #language-Biage #language-Mountain Koiali #language-Grass Koiari #language-Koitabu #language-Ndom #language-Kimaama #language-Uduk #language-Jejueo #language-Aja (South Sudan) #language-Bakwé #language-Wané #language-Gagnoa Bété #language-Kouya #language-Daloa Bété #language-Godié #language-Guiberoua Béte #language-Neyo #language-Yocoboué Dida #language-Lakota Dida #language-Kodia #language-Kuwaa #language-Mobumrin Aizi #language-Tiagbamrin Aizi #language-Southern Grebo #language-Northern Grebo #language-Barclayville Grebo #language-Central Grebo #language-Gboloo Grebo #language-Pye Krumen #language-Plapo Krumen #language-Tepo Krumen #language-Dewoin #language-Gbii #language-Tajuasohn #language-Nyabwa #language-Daho-Doo #language-Glaro-Twabo #language-Glio-Oubi #language-Sapo #language-Western Krahn #language-Wè Southern #language-Wè Western #language-Biangai #language-Kunimaipa #language-Weri #language-Mulaha #language-Humene #language-Uare #language-Isirawa #language-Bagusa #language-Kauwera #language-Trimuris #language-Airoran #language-Kwomtari #language-ǂHua #language-Awera #language-Rasawa #language-Saponi #language-Duvle #language-Edopi #language-Sikaritai #language-Doutai #language-Kaiy #language-Kwerisa #language-Papasena #language-Tause #language-Fayu #language-Owiniga #language-Ama (Papua New Guinea) #language-Nakwi #language-Nimo #language-Bo (Papua New Guinea) #language-Kembra #language-Lepki #language-Murkim #language-Wulna #language-Chambri #language-Yimas #language-Kopar #language-Murik (Papua New Guinea) #language-Banaro #language-Abu #language-Gorovu #language-Aiome #language-Anor #language-Breri #language-Romkun #language-Igana #language-Kominimung #language-Andarum #language-Tanguat #language-Tanggu #language-Borei #language-Awar #language-Bosngun #language-Watam #language-Massalat #language-Surbakhal #language-Karanga #language-Maba (Chad) #language-Kibet #language-Runga #language-Karon Dori #language-Northwest Maidu #language-Northeast Maidu #language-Valley Maidu #language-Laua #language-Morawa #language-Bauwaki #language-Mer #language-Mairasi #language-Semimi #language-Boko (Benin) #language-Bokobaru #language-Busa #language-Shanga #language-Matya Samo #language-Maya Samo #language-Southern Samo #language-Kla-Dan #language-Toura (Côte d'Ivoire) #language-Guro #language-Yaouré #language-Gbin #language-Mwan #language-Jalkunan #language-Ligbi #language-Tonjon #language-Bolon #language-Marka #language-Eastern Maninkakan #language-Konyanka Maninka #language-Manya #language-Sankaran Maninka #language-Mahou #language-Wojenaka #language-Worodougou #language-Koro (Côte d'Ivoire) #language-Koyaga #language-Mandinka #language-Kagoro #language-Kita Maninkakan #language-Jahanka #language-Western Maninkakan #language-Xaasongaxango #language-Kakabe #language-Kuranko #language-Lele (Guinea) #language-Kono (Sierra Leone) #language-Yalunka #language-Guinea Kpelle #language-Kono (Guinea) #language-Liberia Kpelle #language-Loma (Liberia) #language-Toma #language-Bandi #language-Mende (Sierra Leone) #language-Northern Bobo Madaré #language-Southern Bobo Madaré #language-Seeku #language-Bankagooma #language-Duungooma #language-Dzùùngoo #language-Kpeego #language-Jenaama Bozo #language-Tiemacèwè Bozo #language-Tiéyaxo Bozo #language-Sininkere #language-Mangarrayi #language-Alawa #language-Marra #language-Wandarang #language-Djeebbana #language-Burarra #language-Doromu-Koki #language-Maria (Papua New Guinea) #language-Hozo #language-Seze #language-Margu #language-Maca #language-Iyojwa'ja Chorote #language-Iyo'wujwa Chorote #language-Wichí Lhamtés Nocten #language-Wichí Lhamtés Vejoz #language-Wichí Lhamtés Güisnay #language-Kekchí #language-Uspanteco #language-Sacapulteco #language-Sipacapense #language-Tz'utujil #language-Cakchiquel-Quiché Mixed Language #language-K'iche' #language-Poqomam #language-Poqomchi' #language-Aguacateco #language-Ixil #language-Tektiteko #language-Epigraphic Mayan #language-Chol #language-Tabasco Chontal #language-Chortí #language-Tojolabal #language-Mocho #language-Popti' #language-Q'anjob'al #language-Itzá #language-Mopán Maya #language-Nungali #language-Gudanji #language-Wambaya #language-Mískito #language-Cacaopera #language-Matagalpa #language-Mayangna #language-Ulwa #language-Karkin #language-Plains Miwok #language-Central Sierra Miwok #language-Northern Sierra Miwok #language-Southern Sierra Miwok #language-Coast Miwok #language-Lake Miwok #language-Oluta Popoluca #language-Sayula Popoluca #language-Totontepec Mixe #language-Tlahuitoltepec Mixe #language-Coatlán Mixe #language-Isthmus Mixe #language-Mazatlán Mixe #language-Juquila Mixe #language-North Central Mixe #language-Chimalapa Zoque #language-Copainalá Zoque #language-Francisco León Zoque #language-Rayón Zoque #language-Highland Popoluca #language-Tabasco Zoque #language-Texistepec Popoluca #language-Yeniche #language-Gurindji Kriol #language-Media Lengua #language-Koneraw #language-Mombum #language-Kitan #language-Mogholi #language-Buriat #language-Mongolian #language-China Buriat #language-Mongolia Buriat #language-Russia Buriat #language-Halh Mongolian #language-Peripheral Mongolian #language-Kalmyk #language-East Yugur #language-Dongxiang #language-Kangjia #language-Monumbo #language-Smärky Kanum #language-Sota Kanum #language-Yei #language-Namat #language-Nambo #language-Neme #language-Nen #language-Nama (Papua New Guinea) #language-Namo #language-Arammba #language-Rema #language-Wára #language-Creek #language-Mikasuki #language-Apalachee #language-Nadëb #language-Dâw #language-Yuhup #language-Karata #language-Aghwan #language-Sabanê #language-Southern Nambikuára #language-Mamaindé #language-Lakondê #language-Latundê #language-Tawandê #language-Namla #language-Tofanma #language-Acheron #language-Torona #language-Boikin #language-Ngala #language-Ambulas #language-Hanga Hundi #language-Manambu #language-Koiwat #language-Sengo #language-Burui #language-Gaikundi #language-Sos Kundi #language-Kakwa #language-Mandari #language-Kuku #language-Imotong #language-Lango (South Sudan) #language-Logir #language-Okolie #language-Ngasa #language-Masai #language-Karamojong #language-Nyangatom #language-Kalenjin #language-Kipsigis #language-Nandi #language-Markweeta #language-Pökoot #language-Okiek #language-Burun #language-Jumjum #language-Mabaan #language-Northeastern Dinka #language-Northwestern Dinka #language-Southwestern Dinka #language-South Central Dinka #language-Southeastern Dinka #language-Anuak #language-Belanda Bor #language-Luwo #language-Thuri #language-Acoli #language-Adhola #language-Luo (Kenya and Tanzania) #language-Kumam #language-Lango (Uganda) #language-Mlap #language-Gresi #language-Kemtuik #language-Tabaru #language-Galela #language-Modole #language-Kao #language-Pagu #language-Tobelo #language-Tugutil #language-Ibu #language-Sahu #language-Waioli #language-Tidore #language-Rotokas #language-Old Nubian #language-Midob #language-Birked #language-Dair #language-Kadaru #language-El Hugeirat #language-Karko #language-Wali (Sudan) #language-Keoru-Ahia #language-Opao #language-Orokolo #language-Beli (Papua New Guinea) #language-Laeko-Libuat #language-Urim #language-Wom (Papua New Guinea) #language-Au #language-Elkei #language-Olo #language-Urat #language-Bumbita Arapesh #language-Abu' Arapesh #language-Bukiyip #language-Yambes #language-Eitiep #language-Kombio #language-Aruek #language-Buna #language-Bungain #language-Kamasau #language-Urimo #language-Ningil #language-Yil #language-Bragat #language-Ambrak #language-Yangum Gel #language-Yangum Mon #language-Yangum Dey #language-Gnau #language-Seta #language-Seti #language-Kwamtim One #language-Southern One #language-Inebu One #language-Kabore One #language-Molmo One #language-Northern One #language-Agi #language-Yau (Sandaun Province) #language-Yis #language-Guhu-Samane #language-Yekora #language-Suena #language-Zia #language-Binandere #language-Ewage-Notu #language-Doghoro #language-Gaina #language-Korafe-Yegha #language-Aeka #language-Hunjara-Kaina Ke #language-Orokaiva #language-Kamoro #language-Sempan #language-Central Asmat #language-Yaosakor Asmat #language-Citak #language-Diuwe #language-Tamnim Citak #language-Buruwai #language-Asue Awyu #language-Edera Awyu #language-North Awyu #language-South Awyu #language-Aghu #language-Central Awyu #language-Ketum #language-Wambon #language-Mandobo Atas #language-Mandobo Bawah #language-Kombai #language-Wanggom #language-Sawi #language-Komyandaret #language-Kopkaka #language-Burumakok #language-Kwer #language-North Muyu #language-South Muyu #language-Bimin #language-Faiwol #language-Setaman #language-Telefol #language-Tifal #language-Urapmin #language-Mian #language-Suganga #language-Nakai #language-Tangko #language-Imbongu #language-Umbu-Ungu #language-Bo-Ung #language-Melpa #language-Maring #language-Kandawo #language-Narak #language-Chuave #language-Nomane #language-Golin #language-Sinasina #language-North Wahgi #language-Wahgi #language-Nggem #language-Wano #language-Mid Grand Valley Dani #language-Hupla #language-Lower Grand Valley Dani #language-Upper Grand Valley Dani #language-Walak #language-Nduga #language-Angguruk Yali #language-Ninia Yali #language-Pass Valley Yali #language-Enga #language-Ipili #language-Kyaka #language-Lembena #language-Mae #language-Sari #language-Bisorio #language-Nete #language-Huli #language-Samberigi #language-Angal Heneng #language-Angal Enen #language-West Kewa #language-East Kewa #language-Erave #language-Mungkip #language-Numanggang #language-Nek #language-Nuk #language-Finongan #language-Mamaa #language-Nimi #language-Ma Manda #language-Nekgini #language-Neko #language-Ufim #language-Ngaing #language-Nukna #language-Som #language-Weliki #language-Yau (Morobe Province) #language-Tuma-Irumu #language-Awara #language-Forak #language-Degenan #language-Asaro'o #language-Bulgebi #language-Guya #language-Yagomi #language-Nankina #language-Ma (Papua New Guinea) #language-Bonkiman #language-Yopno #language-Yout Wam #language-Ono #language-Sialum #language-Kovai #language-Sene #language-Kâte #language-Mape #language-Migabac #language-Momare #language-Nomu #language-Kinalakna #language-Kumukio #language-Timbe #language-Selepet #language-Mese #language-Nabak #language-Dedua #language-Tobo #language-Gende #language-Fore #language-Gimi (Eastern Highlands) #language-Dano #language-Tokano #language-Benabena #language-Siane #language-Yaweyuha #language-Inoke-Yate #language-Kamano #language-Kanite #language-Keyagana #language-Yagaria #language-Abaga #language-Isabi #language-Usarufa #language-Awa (Papua New Guinea) #language-Agarabi #language-Gadsup #language-North Tairora #language-South Tairora #language-Waffa #language-Kambaira #language-Kenati #language-Amaimon #language-Korak #language-Waskia #language-Maiani #language-Mala (Papua New Guinea) #language-Miani #language-Bepour #language-Moere #language-Kowaki #language-Mawak #language-Yaben #language-Ukuriguma #language-Yarawata #language-Kare (Papua New Guinea) #language-Gumalu #language-Bau #language-Isebe #language-Panim #language-Baimak #language-Gal #language-Garus #language-Rempi #language-Yoidik #language-Bagupi #language-Mawan #language-Saruga #language-Silopi #language-Utu #language-Matepi #language-Nake #language-Rapting #language-Mosimo #language-Murupi #language-Samosa #language-Wamas #language-Munit #language-Kobon #language-Kalam #language-Tai #language-Wadaginam #language-Anam #language-Moresada #language-Kesawai #language-Sausi #language-Arawum #language-Lemio #language-Pulabu #language-Siroi #language-Bongu #language-Male (Papua New Guinea) #language-Jilim #language-Rerau #language-Yangulam #language-Danaru #language-Urigina #language-Biyom #language-Wasembo #language-Ganglau #language-Saep #language-Yabong #language-Eipomek #language-Una #language-Korupun-Sela #language-Kosarek Yale #language-Nipsan #language-Moni #language-Wolani #language-Auye #language-Dao #language-Ofayé #language-Krenak #language-Acroá #language-Xakriabá #language-Xavánte #language-Xerénte #language-Xokleng #language-São Paulo Kaingáng #language-Kayapó #language-Krahô #language-Pataxó Hã-Ha-Hãe #language-Koropó #language-Afitti #language-Ama (Sudan) #language-Warrwa #language-Ngumbarl #language-Dyugun #language-Yawuru #language-Nimanbur #language-Bardi #language-Djawi #language-Dyaberdyaber #language-Nyulnyul #language-Ipalapa Amuzgo #language-San Pedro Amuzgos Amuzgo #language-Tepeuxila Cuicatec #language-Teutila Cuicatec #language-Amoltepec Mixtec #language-Mixtepec Mixtec #language-Tezoatlán Mixtec #language-Northwest Oaxaca Mixtec #language-Silacayoapan Mixtec #language-Chayuco Mixtec #language-Ixtayutla Mixtec #language-Jamiltepec Mixtec #language-San Juan Colorado Mixtec #language-Tututepec Mixtec #language-Pinotepa Nacional Mixtec #language-Santa María Zacatepec Mixtec #language-Diuxi-Tilantongo Mixtec #language-Mitlatongo Mixtec #language-Peñoles Mixtec #language-Tlazoyaltepec Mixtec #language-Huitepec Mixtec #language-San Miguel Piedras Mixtec #language-Sindihui Mixtec #language-Tamazola Mixtec #language-Yutanduchi Mixtec #language-Alacatlatzala Mixtec #language-Alcozauca Mixtec #language-Metlatónoc Mixtec #language-Yoloxochitl Mixtec #language-Apasco-Apoala Mixtec #language-Southeastern Nochixtlán Mixtec #language-Soyaltepec Mixtec #language-Coatzospan Mixtec #language-Cuyamecalco Mixtec #language-Tidaá Mixtec #language-Cacaloxtepec Mixtec #language-Chazumba Mixtec #language-Chigmecatitlán Mixtec #language-Southern Puebla Mixtec #language-Ayutla Mixtec #language-Juxtlahuaca Mixtec #language-Western Juxtlahuaca Mixtec #language-Atatláhuca Mixtec #language-Itundujia Mixtec #language-Magdalena Peñasco Mixtec #language-Northern Tlaxiaco Mixtec #language-Ocotepec Mixtec #language-San Juan Teita Mixtec #language-San Miguel El Grande Mixtec #language-Santa Lucía Monteverde Mixtec #language-Sinicahua Mixtec #language-Southwestern Tlaxiaco Mixtec #language-Tijaltepec Mixtec #language-Yosondúa Mixtec #language-Yucuañe Mixtec #language-Chicahuaxtla Triqui #language-Copala Triqui #language-San Martín Itunyoso Triqui #language-Chochotec #language-Mezontla Popoloca #language-San Juan Atzingo Popoloca #language-San Luís Temalacayuca Popoloca #language-Coyotepec Popoloca #language-San Felipe Otlaltepec Popoloca #language-Santa Inés Ahuatempan Popoloca #language-Soyaltepec Mazatec #language-San Jerónimo Tecóatl Mazatec #language-Chiquihuitlán Mazatec #language-Jalapa De Díaz Mazatec #language-Ayautla Mazatec #language-Ixcatlán Mazatec #language-Huautla Mazatec #language-Mazatlán Mazatec #language-Zapotec #language-Zenzontepec Chatino #language-Tataltepec Chatino #language-Eastern Highland Chatino #language-Nopala Chatino #language-Western Highland Chatino #language-Zacatepec Chatino #language-Asunción Mixtepec Zapotec #language-Ayoquesco Zapotec #language-Mazaltepec Zapotec #language-Mitla Zapotec #language-San Pedro Quiatoni Zapotec #language-Santa Catarina Albarradas Zapotec #language-Santo Domingo Albarradas Zapotec #language-Tejalapan Zapotec #language-Lapaguía-Guivini Zapotec #language-Santa María Quiegolani Zapotec #language-Santiago Xanica Zapotec #language-Xadani Zapotec #language-Xanaguía Zapotec #language-Mixtepec Zapotec #language-Guevea De Humboldt Zapotec #language-Petapa Zapotec #language-Lachiguiri Zapotec #language-Quiavicuzas Zapotec #language-Chichicapan Zapotec #language-Güilá Zapotec #language-Western Tlacolula Valley Zapotec #language-Isthmus Zapotec #language-Ocotlán Zapotec #language-Zaachila Zapotec #language-Santa Inés Yatzechi Zapotec #language-Tilquiapan Zapotec #language-Yautepec Zapotec #language-Loxicha Zapotec #language-Ozolotepec Zapotec #language-San Agustín Mixtepec Zapotec #language-Choapan Zapotec #language-Cajonos Zapotec #language-Tabaa Zapotec #language-Yalálag Zapotec #language-Yatzachi Zapotec #language-Zoogocho Zapotec #language-Rincón Zapotec #language-Yatee Zapotec #language-Las Delicias Zapotec #language-Southern Rincon Zapotec #language-Aloápam Zapotec #language-Sierra de Juárez Zapotec #language-Southeastern Ixtlán Zapotec #language-Yareni Zapotec #language-Coatecas Altas Zapotec #language-Amatlán Zapotec #language-Tlacolulita Zapotec #language-San Vicente Coatlán Zapotec #language-Coatlán Zapotec #language-San Baltazar Loxicha Zapotec #language-Elotepec Zapotec #language-Texmelucan Zapotec #language-Zaniza Zapotec #language-Totomachapan Zapotec #language-El Alto Zapotec #language-Lachixío Zapotec #language-Ojitlán Chinantec #language-Sochiapam Chinantec #language-Usila Chinantec #language-Chiltepec Chinantec #language-Tlacoatzintepec Chinantec #language-Palantla Chinantec #language-Tepetotutla Chinantec #language-Ozumacín Chinantec #language-Valle Nacional Chinantec #language-Lalana Chinantec #language-Lealao Chinantec #language-Tepinapa Chinantec #language-Comaltepec Chinantec #language-Quiotepec Chinantec #language-Chichimeca-Jonaz #language-Atzingo Matlatzinca #language-San Francisco Matlatzinca #language-Central Mazahua #language-Michoacán Mazahua #language-Eastern Highland Otomi #language-Tenango Otomi #language-Texcatepec Otomi #language-Mezquital Otomi #language-Querétaro Otomi #language-Ixtenco Otomi #language-Tilapa Otomi #language-Estado de México Otomi #language-Temoaya Otomi #language-Central Pame #language-Northern Pame #language-Southern Pame #language-Chiapanec #language-Subtiaba #language-Azoyú Me'phaa #language-Malinaltepec Me'phaa #language-Acatepec Me'phaa #language-Tlacoapa Me'phaa #language-Idi #language-Atsugewi #language-Dyirbal #language-Kala Lagaw Ya #language-Kaytetye #language-Lower Southern Aranda #language-Alyawarr #language-Andegerebinha #language-Anmatyerre #language-Eastern Arrernte #language-Western Arrarnta #language-Ayerrerenge #language-Wirangu #language-Banggarla #language-Guyani #language-Narungga #language-Nauo #language-Ngadjuri #language-Nugunu (Australia) #language-Warumungu #language-Mangala #language-Nyangumarta #language-Warlpiri #language-Warlmanpa #language-Walmajarri #language-Gurindji #language-Mudburra #language-Jaru #language-Ngardi #language-Martu Wangka #language-Kukatja #language-Pintupi-Luritja #language-Ngaanyatjarra #language-Pitjantjatjara #language-Yankunytjatjara #language-Antakarinya #language-Kokata #language-Jandai #language-Yagara #language-Bigambal #language-Yugambal #language-Kalkutung #language-Yalarnnga #language-Yanda #language-Biri #language-Gangulu #language-Gugu Badhun #language-Gungabula #language-Guwamu #language-Kunggari #language-Mandandanyi #language-Wadjigu #language-Yandjibara #language-Gunya #language-Margany #language-Punthamara #language-Wangkumara #language-Pirlatapa #language-Dieri #language-Ngamini #language-Yarluyandi #language-Yandruwandha #language-Yawarawarga #language-Nhirrpi #language-Arabana #language-Pitta Pitta #language-Pirriya #language-Dyangadi #language-Nganyaywana #language-Yanyuwa #language-Thawa #language-Wagaya #language-Yindjilandji #language-Nyawaygi #language-Yuru #language-Gugadj #language-Ikaranggal #language-Tagalaka #language-Thaypan #language-Pakanha #language-Wikngenchera #language-Kanju #language-Kuuku-Ya'u #language-Umbindhamu #language-Flinders Island #language-Wik-Epa #language-Wik-Me'anha #language-Wik-Iiyanh #language-Wik-Mungkan #language-Kuku-Uwanh #language-Kuku-Ugbanh #language-Kuku-Mu'inh #language-Wikalkan #language-Lamalama #language-Mayaguduna #language-Ngawun #language-Mayi-Thakurti #language-Mayi-Yapi #language-Mayi-Kulan #language-Wunumara #language-Mbara (Australia) #language-Walangama #language-Kuthant #language-Areba #language-Yinwum #language-Anguthimri #language-Awngthim #language-Ndra'ngith #language-Gudang #language-Atampaya #language-Angkamuthi #language-Alngith #language-Mpalitjanh #language-Gugubera #language-Kuuk-Yak #language-Bayali #language-Dharumbal #language-Mirning #language-Yinggarda #language-Nhanda #language-Badimaya #language-Malgana #language-Wajarri #language-Kalaamaya #language-Ngadjunmaya #language-Kalarko #language-Bibbulman #language-Goreng #language-Pinjarup #language-Wajuk #language-Wardandi #language-Bayungu #language-Pinigura #language-Burduna #language-Dhalandji #language-Djiwarli #language-Thiin #language-Dhargari #language-Wariyangga #language-Nhuwala #language-Tjurruru #language-Kariyarra #language-Ngarluma #language-Yinhawangka #language-Kurrama #language-Yindjibarndi #language-Ngarla #language-Nyamal #language-Bandjalang #language-Muruwari #language-Kuri #language-Awabakal #language-Worimi #language-Birrpayi #language-Gundungurra #language-Ngunawal #language-Dhurga #language-Jaitmatang #language-Ngarigu #language-Kumbainggar #language-Yaygir #language-Gureng Gureng #language-Dhungaloo #language-Wakawaka #language-Wuliwuli #language-Dhudhuroa #language-Pallanganmiddang #language-Yabula Yabula #language-Wathawurrung #language-Ladji Ladji #language-Madhi Madhi #language-Nari Nari #language-Wadi Wadi #language-Wotjobaluk #language-Wergaia #language-Daungwurrung #language-Woiwurrung #language-Bunganditj #language-Dadi Dadi #language-Yitha Yitha #language-Malyangapa #language-Wadikali #language-Yardliyawarra #language-Guugu Yimidhirr #language-Djangun #language-Kuku-Yalanji #language-Muluridyi #language-Dayi #language-Dhangu-Djangu #language-Djambarrpuyngu #language-Gupapuyngu #language-Dhuwal #language-Gumatj #language-Dhuwaya #language-Djinba #language-Djinang #language-Golpa #language-Yan-nhangu #language-Cashibo-Cacataibo #language-Kaxararí #language-Tuxináwa #language-Chácobo #language-Karipuna #language-Pacahuara #language-Panobo #language-Sensi #language-Capanahua #language-Shipibo-Conibo #language-Amahuaca #language-Cashinahua #language-Shanenawa #language-Sharanahua #language-Yaminahua #language-Yawanawa #language-Yora #language-Atsahuaca #language-Marúbo #language-Panoan Katukína #language-Isconahua #language-Nukuini #language-Poyanáwa #language-Matís #language-Korubo #language-Kulina Pano #language-Cavineña #language-Tacana #language-Araona #language-Toromono #language-Emumu #language-Karkar-Yuri #language-Yafi #language-Dubu #language-Towei #language-Pinai-Hagahai #language-Nefamese #language-Mobilian #language-Pidgin Delaware #language-Chinese Pidgin English #language-Tay Boi #language-Barikanchi #language-Gibanawa #language-Broome Pearling Lugger Pidgin #language-Hiri Motu #language-Ndyuka-Trio Pidgin #language-Fanagalo #language-Southeastern Pomo #language-Central Pomo #language-Northern Pomo #language-Southern Pomo #language-Puri #language-Pacaraos Quechua #language-Cajatambo North Lima Quechua #language-Chiquián Ancash Quechua #language-Huallaga Huánuco Quechua #language-Margos-Yarowilca-Lauricocha Quechua #language-Panao Huánuco Quechua #language-Huamalíes-Dos de Mayo Huánuco Quechua #language-Huaylas Ancash Quechua #language-Northern Conchucos Ancash Quechua #language-Southern Conchucos Ancash Quechua #language-Corongo Ancash Quechua #language-Sihuas Ancash Quechua #language-Huaylla Wanca Quechua #language-Jauja Wanca Quechua #language-Ambo-Pasco Quechua #language-North Junín Quechua #language-Santa Ana de Tusi Pasco Quechua #language-Cajamarca Quechua #language-Lambayeque Quechua #language-Classical Quechua #language-Chachapoyas Quechua #language-San Martín Quechua #language-Arequipa-La Unión Quechua #language-Ayacucho Quechua #language-North Bolivian Quechua #language-Santiago del Estero Quichua #language-South Bolivian Quechua #language-Calderón Highland Quichua #language-Salasaca Highland Quichua #language-Loja Highland Quichua #language-Cañar Highland Quichua #language-Imbabura Highland Quichua #language-Napo Lowland Quechua #language-Tena Lowland Quichua #language-Northern Pastaza Quichua #language-Southern Pastaza Quechua #language-Cusco Quechua #language-Eastern Apurímac Quechua #language-Puno Quechua #language-Chincha Quechua #language-Yauyos Quechua #language-Tegali #language-Tenino #language-Umatilla #language-Berti #language-Kube #language-Kanembu #language-Tarjumo #language-Tumari Kanuri #language-Central Kanuri #language-Bilma Kanuri #language-Manga Kanuri #language-Dazaga #language-Tedaga #language-Bella Coola #language-Halkomelem #language-Sechelt #language-Straits Salish #language-Southern Puget Sound Salish #language-Skagit #language-Snohomish #language-Clallam #language-Cowlitz #language-Columbia-Wenatchi #language-Kalispel-Pend d'Oreille #language-Spokane #language-Sáliba #language-Maco #language-Dera (Indonesia) #language-Nafri #language-Sentani #language-Abau #language-Amal #language-Iwam #language-Chenapian #language-Wogamusin #language-Kwoma #language-Kwanga #language-Mende (Papua New Guinea) #language-Awtuw #language-Karawa #language-Pouye #language-Ayi (Papua New Guinea) #language-Pasi #language-Mehek #language-Bahinemo #language-Bisis #language-Mari (East Sepik Province) #language-Sumariup #language-Kapriman #language-Alamblak #language-Kaningra #language-Saniyo-Hiyewe #language-Hewa #language-Niksek #language-Piame #language-Ak #language-Namia #language-Shasta #language-Armenian Sign Language #language-Australian Aborigines Sign Language #language-Monastic Sign Language #language-Plains Indian Sign Language #language-Afghan Sign Language #language-Albanian Sign Language #language-Argentine Sign Language #language-Cambodian Sign Language #language-Guatemalan Sign Language #language-Hausa Sign Language #language-Maltese Sign Language #language-Mauritian Sign Language #language-Mozambican Sign Language #language-Nicaraguan Sign Language #language-Penang Sign Language #language-Sri Lankan Sign Language #language-Tanzanian Sign Language #language-Tibetan Sign Language #language-Turkish Sign Language #language-Zambian Sign Language #language-Zimbabwe Sign Language #language-Egypt Sign Language #language-Libyan Sign Language #language-Saudi Arabian Sign Language #language-Maritime Sign Language #language-British Sign Language #language-New Zealand Sign Language #language-Auslan #language-Papua New Guinean Sign Language #language-Namibian Sign Language #language-South African Sign Language #language-Chilean Sign Language #language-Paraguayan Sign Language #language-Uruguayan Sign Language #language-Hanoi Sign Language #language-Ho Chi Minh City Sign Language #language-Chinese Sign Language #language-German Sign Language #language-Israeli Sign Language #language-Polish Sign Language #language-Swiss-German Sign Language #language-Nepalese Sign Language #language-Indian Sign Language #language-Pakistan Sign Language #language-Japanese Sign Language #language-Korean Sign Language #language-Taiwan Sign Language #language-Algerian Sign Language #language-Austrian Sign Language #language-Brazilian Sign Language #language-Estonian Sign Language #language-French Sign Language #language-Greek Sign Language #language-Irish Sign Language #language-Latvian Sign Language #language-Mexican Sign Language #language-Philippine Sign Language #language-Swiss-French Sign Language #language-Dominican Sign Language #language-Ethiopian Sign Language #language-Ghanaian Sign Language #language-Guinean Sign Language #language-Moroccan Sign Language #language-Puerto Rican Sign Language #language-Quebec Sign Language #language-Salvadoran Sign Language #language-Sierra Leone Sign Language #language-Thai Sign Language #language-Trinidad and Tobago Sign Language #language-American Sign Language #language-Jamaican Sign Language #language-Costa Rican Sign Language #language-Honduras Sign Language #language-Panamanian Sign Language #language-Malaysian Sign Language #language-Selangor Sign Language #language-Chadian Sign Language #language-Nigerian Sign Language #language-Rwandan Sign Language #language-Ugandan Sign Language #language-Bolivian Sign Language #language-Colombian Sign Language #language-Ecuadorian Sign Language #language-Peruvian Sign Language #language-Catalan Sign Language #language-Valencian Sign Language #language-Bulgarian Sign Language #language-Czech Sign Language #language-Hungarian Sign Language #language-Romanian Sign Language #language-Slovakian Sign Language #language-Dutch Sign Language #language-Langue des signes de Belgique Francophone #language-Vlaamse Gebarentaal #language-Italian Sign Language #language-Swiss-Italian Sign Language #language-Tunisian Sign Language #language-Danish Sign Language #language-Icelandic Sign Language #language-Madagascar Sign Language #language-Norwegian Sign Language #language-Yugoslavian Sign Language #language-Haiphong Sign Language #language-Chiangmai Sign Language #language-Lithuanian Sign Language #language-Moldova Sign Language #language-Mongolian Sign Language #language-Ukrainian Sign Language #language-Russian Sign Language #language-Spanish Sign Language #language-Venezuelan Sign Language #language-Portuguese Sign Language #language-Swedish Sign Language #language-Finland-Swedish Sign Language #language-Finnish Sign Language #language-Cuba Sign Language #language-International Sign #language-Adamorobe Sign Language #language-Albarradas Sign Language #language-Al-Sayyid Bedouin Sign Language #language-Ban Khor Sign Language #language-Bribri Sign Language #language-Brunca Sign Language #language-Ghandruk Sign Language #language-Inuit Sign Language #language-Jamaican Country Sign Language #language-Jhankot Sign Language #language-Jumla Sign Language #language-Mardin Sign Language #language-Martha's Vineyard Sign Language #language-Miriwoong Sign Language #language-Miyakubo Sign Language #language-Old Kentish Sign Language #language-Seychelles Sign Language #language-Sivia Sign Language #language-Solomon Islands Sign Language #language-Tebul Sign Language #language-Urubú-Kaapor Sign Language #language-Yucatec Maya Sign Language #language-Providencia Sign Language #language-Olekha #language-Dakpakha #language-Dzalakha #language-Chalikha #language-Bumthangkha #language-Khengkha #language-Kurtokha #language-Classical Tibetan #language-Zangskari #language-Purik #language-Tibetan #language-Humla #language-Lhomi #language-Walungge #language-Dolpo #language-Tichurong #language-Tsum #language-Kyerung #language-Mugom #language-Jirel #language-Naaba #language-Khams Tibetan #language-Tseku #language-Bhoti Kinnauri #language-Stod Bhoti #language-Jad #language-Spiti Bhoti #language-Brokpake #language-Chocangacakha #language-Groma #language-Dzongkha #language-Layakha #language-Lunanakha #language-Khamba #language-Amdo Tibetan #language-Kaike #language-Northern Ghale #language-Southern Ghale #language-Eastern Gorkha Tamang #language-Seke (Nepal) #language-Gurung #language-Nar Phu #language-Chantyal #language-Eastern Tamang #language-Western Tamang #language-Rongpo #language-Rangkas #language-Chaudangsi #language-Byangsi #language-Kanashi #language-Tukpa #language-Jangshung #language-Shumcho #language-Pattani #language-Kalaktang Monpa #language-Tshangla #language-Kok Borok #language-Riang (India) #language-Tippera #language-Usui #language-Kachari #language-Atong (India) #language-Koch #language-Ruga #language-Chak #language-Kadu #language-Taman (Myanmar) #language-Chang Naga #language-Konyak Naga #language-Phom Naga #language-Wancho Naga #language-Khiamniungan Naga #language-Leinong Naga #language-Makyan Naga #language-Nocte Naga #language-Tutsa Naga #language-Ugong #language-Hpon #language-Maru #language-Pela #language-Taungyo #language-Danu #language-Intha #language-Old Burmese #language-Tavoyan #language-Marma #language-Pholo #language-Phana' #language-Bisu #language-Laomian #language-Pyen #language-Côông #language-Honi #language-Biyo #language-Enu #language-Kaduo #language-Akeu #language-Akha #language-Chepya #language-Muda #language-Sila #language-Buyuan Jinuo #language-Youle Jinuo #language-Kucong #language-Lahu Shi #language-Katso #language-Samatao #language-Lawu #language-Miqie #language-Limi #language-Mili #language-Sonaga #language-Kuamasi #language-Kua-nsi #language-Dongshanba Lalo #language-Western Lalu #language-Xishanba Lalo #language-Eastern Lalu #language-Lamu #language-Naluo Yi #language-Laghuu #language-Thopho #language-Qila Muji #language-Bokha #language-Phuma #language-Northern Muji #language-Southern Muji #language-Ani Phowa #language-Labo Phowa #language-Hlepho Phowa #language-Khlula #language-Zokhuo #language-Southern Nisu #language-Eastern Nisu #language-Northern Nisu #language-Sichuan Yi #language-Gepo #language-Samei #language-Sanie #language-Wuding-Luquan Yi #language-Ayizi #language-Chesu #language-Wumeng Nasu #language-Wusa Nasu #language-Aluo #language-Ache #language-Alugu #language-Phupa #language-Phuza #language-Phala #language-Alo Phola #language-Azha #language-Axi Yi #language-Azhe #language-Nisi (China) #language-Nusu #language-Zauzou #language-Ersu #language-Narua #language-Queyu #language-Northern Pumi #language-Southern Pumi #language-Southern Qiang #language-Northern Tujia #language-Southern Tujia #language-Toto #language-Lepcha #language-Lhokpu #language-Dura #language-Gamale Kham #language-Sheshi Kham #language-Eastern Parbate Kham #language-Western Parbate Kham #language-Eastern Magar #language-Western Magar #language-Saam #language-Sampang #language-Chukwa #language-Kulung (Nepal) #language-Nachering #language-Camling #language-Dungmali #language-Waling #language-Chhulung #language-Athpariya #language-Belhariya #language-Lohorung #language-Southern Yamphu #language-Yamphu #language-Eastern Meohang #language-Western Meohang #language-Jerung #language-Bahing #language-Wayu #language-Dumi #language-Baraamu #language-Mobwa Karen #language-Geba Karen #language-Manumanaw Karen #language-Yintale Karen #language-Eastern Kayah #language-Western Kayah #language-Geko Karen #language-Yinbaw Karen #language-Pa'o Karen #language-Pwo Eastern Karen #language-Pwo Western Karen #language-Phrae Pwo Karen #language-Pwo Northern Karen #language-Paku Karen #language-Wewaw #language-Bugun #language-Manipuri #language-Khezha Naga #language-Angami Naga #language-Chokri Naga #language-Mao Naga #language-Poumei Naga #language-Northern Rengma Naga #language-Pochuri Naga #language-Southern Rengma Naga #language-Sumi Naga #language-Ao Naga #language-Lotha Naga #language-Sangtam Naga #language-Jejara Naga #language-Yimchungru Naga #language-Long Phuri Naga #language-Makuri Naga #language-Amri Karbi #language-Bawm Chin #language-Bualkhaw Chin #language-Falam Chin #language-Biete #language-Darlong #language-Hmar #language-Senthang Chin #language-Zotung Chin #language-Mara Chin #language-Shendu #language-Aimol #language-Anal #language-Kom (India) #language-Monsang Naga #language-Ranglong #language-Eastern Khumi Chin #language-Khumi Chin #language-Ngawn Chin #language-Zou #language-Gangte #language-Vaiphei #language-Kharam Naga #language-Paite Chin #language-Purum #language-Ralte #language-Tedim Chin #language-Thado Chin #language-Asho Chin #language-Sumtu Chin #language-Chinbon Chin #language-Daai Chin #language-Kaang Chin #language-Mün Chin #language-Maring Naga #language-Maram Naga #language-Rongmei Naga #language-Thangal Naga #language-Liangmai Naga #language-Mzieme Naga #language-Zeme Naga #language-Galo #language-Na #language-Tagin #language-Central Bai #language-Southern Bai #language-Mru #language-Drung #language-Raji #language-Raute #language-Rawat #language-Old Chinese #language-Waxianghua #language-Literary Chinese #language-Gan Chinese #language-Hakka Chinese #language-Xiang Chinese #language-Jinyu Chinese #language-Mandarin Chinese #language-Wutunhua #language-Wu Chinese #language-Yue Chinese #language-Min Dong Chinese #language-Pu-Xian Chinese #language-Min Bei Chinese #language-Min Zhong Chinese #language-Omaha-Ponca #language-Iowa-Oto #language-Ofo #language-Uni #language-Bouni #language-Puare #language-Rawo #language-Womo #language-Vanimo #language-Momina #language-Momuna #language-Humburi Senni Songhay #language-Koyraboro Senni Songhai #language-Tondi Songway Kiini #language-Dendi (Benin) #language-Koyra Chiini Songhay #language-Tadaksahak #language-Kaburi #language-Kokoda #language-Kemberano #language-Arandai #language-Dime #language-Aari #language-Gayil #language-Hamer-Banna #language-Karo (Ethiopia) #language-Uisai #language-Simeku #language-Naasioi #language-Daantanai' #language-Koromira #language-La'bi #language-Lomavren #language-Ngatik Men's Creole #language-Traveller Danish #language-Tavringer Romani #language-Traveller Norwegian #language-Shelta #language-Callawalla #language-Camtho #language-Suki #language-Gogodala #language-Ari #language-Waruna #language-Kwegu #language-Me'en #language-Mursi #language-Murle #language-Tennet #language-Didinga #language-Laarim #language-Cun #language-Hlai #language-E'ma Buyang #language-En #language-Langnian Buyang #language-Baha Buyang #language-Laha (Viet Nam) #language-A'ou #language-Red Gelao #language-Qau #language-Lachi #language-White Lachi #language-Lingao #language-Minz Zhuang #language-Nung (Viet Nam) #language-Tày Sa Pa #language-Lü #language-Tày Tac #language-Tai Pao #language-Nyaw #language-Tai Do #language-Tai Long #language-Khamyang #language-Turung #language-Tai Nüa #language-Tai Hongjin #language-Pa Di #language-Tai Thanh #language-Northeastern Thai #language-Yoy #language-Zuojiang Zhuang #language-Central Hongshuihe Zhuang #language-Eastern Hongshuihe Zhuang #language-Guibian Zhuang #language-Guibei Zhuang #language-Lianshan Zhuang #language-Liujiang Zhuang #language-Liuqian Zhuang #language-Qiubei Zhuang #language-Tay Khang #language-Ts'ün-Lao #language-Youjiang Zhuang #language-Yongnan Zhuang #language-Yongbei Zhuang #language-Mulam #language-Southern Dong #language-Cao Miao #language-Northern Dong #language-T'en #language-Ai-Cham #language-Mak (China) #language-Chadong #language-Maonan #language-Lakkia #language-Mararit #language-Assangori #language-Tama (Chad) #language-Ganggalida #language-Kayardild #language-Purepecha #language-Western Highland Purepecha #language-Taulil #language-Dadibi #language-Folopa #language-Highland Oaxaca Chontal #language-Lowland Oaxaca Chontal #language-Bunak #language-Sawila #language-Kui (Indonesia) #language-Kamang #language-Adang #language-Hamap #language-Kabola #language-Kaera #language-Tereweng #language-Nedebang #language-Fataluku #language-Oirata #language-Orya #language-Berik #language-Itik #language-Kwesten #language-Mander #language-Maremgi #language-Bonerif #language-Dabe #language-Jofotek-Bromnya #language-Keder #language-Vitou #language-Huehuetla Tepehua #language-Pisaflores Tepehua #language-Tlachichilco Tepehua #language-Yecuatla Totonac #language-Papantla Totonac #language-Coyutla Totonac #language-Highland Totonac #language-Xicotepec De Juárez Totonac #language-Tecpatlán Totonac #language-Upper Necaxa Totonac #language-Waimaha #language-Yurutí #language-Arapaso #language-Yahuna #language-Tama (Colombia) #language-Macaguaje #language-Udihe #language-Orok #language-Jurchen #language-Sibe #language-Oroqen #language-Kepkiriwát #language-Arikem #language-Karitiâna #language-Sateré-Mawé #language-Awetí #language-Kamayurá #language-Xetá #language-Chiripá #language-Paraguayan Guaraní #language-Western Bolivian Guaraní #language-Tapieté #language-Jorá #language-Yuqui #language-Nhengatu #language-Tupinambá #language-Cocama-Cocamilla #language-Omagua #language-Potiguára #language-Tupinikin #language-Xingú Asuriní #language-Amanayé #language-Anambé #language-Araweté #language-Tapirapé #language-Parakanã #language-Suruí Do Pará #language-Tocantins Asurini #language-Turiwára #language-Guajajára #language-Júma #language-Paranawát #language-Wiraféd #language-Tenharim #language-Apiaká #language-kgm #language-Kayabí #language-Amundava #language-Uru-Eu-Wau-Wau #language-Urubú-Kaapor #language-Wayampi #language-Suruí #language-Cinta Larga #language-Gavião Do Jiparaná #language-Kuruáya #language-Mundurukú #language-Puruborá #language-Karo (Brazil) #language-Urumi #language-Makuráp #language-Akuntsu #language-Tuparí #language-Jurúna #language-Xipaya #language-Maritsauá #language-Barikewa #language-Mouwase #language-Bolgarian #language-Tuvinian #language-Ainu (China) #language-West Yugur #language-Uighur #language-Northern Uzbek #language-Kirghiz #language-Kara-Kalpak #language-Pecheneg #language-Karachay-Balkar #language-Qashqa'i #language-slq #language-North Azerbaijani #language-South Azerbaijani #language-Giyug #language-Mawa (Nigeria) #language-Moksela #language-Pankararé #language-Rer Bare #language-Sentinel #language-Tremembé #language-Truká #language-Wakoná #language-Wasu #language-Weyto #language-Agavotaguerra #language-Aguano #language-Himarimã #language-Dek #language-Dungu #language-Esuma #language-Kaivi #language-Mala (Nigeria) #language-Nshi #language-ksa #language-Tumi #language-Vono #language-Sorsogon Ayta #language-Villa Viciosa Agta #language-Agariya #language-Nagarchal #language-Pardhan #language-Badeshi #language-Manangkari #language-Yugul #language-Alapmunte #language-Yalakalore #language-Wik-Keyangan #language-Pisabo #language-Wares #language-Morerebi #language-Tukumanféd #language-Ngurmbur #language-Bazigar #language-Camunic #language-Elymian #language-Eteocretan #language-Eteocypriot #language-Gail #language-Haitian Vodoun Culture Language #language-Illyrian #language-Kaimbé #language-Kapinawá #language-Karirí-Xocó #language-Katabaga #language-Koguryo #language-Lemnian #language-Minoan #language-North Picene #language-Numidian #language-Paekche #language-Pictish #language-Pijao #language-Polari #language-Quinqui #language-Raetic #language-Tartessian #language-Traveller Scottish #language-Uamué #language-Uru-Pa-In #language-Wakabunga #language-Liv #language-Livvi #language-Ludian #language-Kven Finnish #language-Mulgi #language-Eastern Mari #language-Western Mari #language-Komi-Zyrian #language-Komi-Permyak #language-Nenets #language-Forest Enets #language-Tundra Enets #language-Selkup #language-Panamint #language-Ute-Southern Paiute #language-Mono (USA) #language-Northern Paiute #language-Tubar #language-Mayo #language-Highland Puebla Nahuatl #language-Huaxcaleca Nahuatl #language-Northern Oaxaca Nahuatl #language-Ometepec Nahuatl #language-Pipil #language-Central Huasteca Nahuatl #language-Eastern Huasteca Nahuatl #language-Western Huasteca Nahuatl #language-Isthmus-Cosoleacaque Nahuatl #language-Isthmus-Pajapan Nahuatl #language-Isthmus-Mecayapan Nahuatl #language-Tabasco Nahuatl #language-Orizaba Nahuatl #language-Central Puebla Nahuatl #language-Santa María La Alta Nahuatl #language-Sierra Negra Nahuatl #language-Zacatlán-Ahuacatlán-Tepetzintla Nahuatl #language-Central Nahuatl #language-Classical Nahuatl #language-Morelos Nahuatl #language-Northern Puebla Nahuatl #language-Tetelcingo Nahuatl #language-Pochutec #language-Temascaltepec Nahuatl #language-Coatepec Nahuatl #language-Tlamacazapa Nahuatl #language-Michoacán Nahuatl #language-Eastern Durango Nahuatl #language-Western Durango Nahuatl #language-El Nayar Cora #language-Santa Teresa Cora #language-Central Tarahumara #language-Lowland Tarahumara #language-Northern Tarahumara #language-Southwestern Tarahumara #language-Southeastern Tarahumara #language-Tohono O'odham #language-Northern Tepehuan #language-Southeastern Tepehuan #language-Southwestern Tepehuan #language-Tepecano #language-Heiltsuk #language-Tuwari #language-Yawiyo #language-Walio #language-Pei #language-Moi (Indonesia) #language-Seget #language-Kalabra #language-Moraid #language-Marimanindji #language-Maringarr #language-Marti Ke #language-Maridjabin #language-Maridan #language-Mariyedi #language-Marriammu #language-Maranunggu #language-Ami #language-Manda (Australia) #language-Wilawila #language-Wunambal #language-Gambera #language-Kwini #language-Miwa #language-Unggumi #language-Worrorra #language-Umiida #language-Unggaranggu #language-Yawijibaya #language-Dagoman #language-Wardaman #language-Yangman #language-Bariji #language-Yareba #language-Yawa #language-Arin #language-Pumpokol #language-Changriwa #language-Mekmek #language-Biwat #language-Bun #language-Northern Yukaghir #language-Chuvantsy #language-Wappo #language-Ayoreo #language-Andoa #language-Cahuarano #language-Iquito #language-Aushiri #language-Záparo #language-Alumu-Tesu #language-Eastern Abnaki #language-Aasáx #language-Manide #language-Western Abnaki #language-Abkhazian #language-Abellen Ayta #language-Achinese #language-Mesopotamian Arabic #language-Atauran #language-Lidzonka #language-Adi #language-Northeast Pashai #language-Putukwam #language-Nanubae #language-Remontado Dumagat #language-Ainu (Japan) #language-Andajin #language-Algerian Jewish Sign Language #language-Tosk Albanian #language-Alaba-K’abeena #language-Amol #language-Anu-Hkongso Chin #language-Alor #language-Pahanan Agta #language-Ambul #language-Official Aramaic (700-300 BCE) #language-Aruá (Rodonia State) #language-Cishingini #language-Abishira #language-Atemble #language-Atong (Cameroon) #language-Avaric #language-Jair Awyu #language-Awun #language-Xârâgurè #language-Ayabadhu #language-Magbukun Ayta #language-Mai Brat #language-Bainouk-Gunyuño #language-Baluchi #language-Baga Pokur #language-Bunuba #language-Central Bikol #language-Babine #language-Bainouk-Gunyaamolo #language-Bai (South Sudan) #language-Belait #language-Bekati' #language-Panyi Bai #language-Gahri #language-Bangandu #language-Bo (Laos) #language-Balkan Gagauz Turkish #language-Bohtan Neo-Aramaic #language-Baloi #language-Bidyogo #language-Bedjond #language-Binukid #language-Northern Sorsoganon #language-Bekwel #language-Bote-Majhi #language-Somba-Siawari #language-Butmas-Tur #language-Bamako Sign Language #language-Bonjo #language-Borôro #language-Daakaka #language-Kaure #language-Bishnupriya #language-Bilakura #language-Wumboko #language-Bengkala Sign Language #language-Bodo (India) #language-Bilbil #language-Kati #language-Brem #language-Barein #language-Baniva #language-Baniwa #language-Tairaha #language-Birale #language-Binahari #language-Biao #language-Bidjara #language-Naami #language-Kɛlɛngaxo Bozo #language-Tsimané #language-Chachi #language-Tsucuba #language-Cacua #language-Cafundo Creole #language-Cinda-Regi-Tiyal #language-Centúúm #language-Chinook #language-Mari (Russia) #language-Chinook jargon #language-Chakavian #language-Chukot #language-Cakfem-Mushere #language-Chilcotin #language-Idu-Mishmi #language-Lautu Chin #language-Classical Mongolian #language-Michigamea #language-Mro-Khimi Chin #language-Northern Ping Chinese #language-Chenoua #language-Middle Cornish #language-Colorado #language-Cori #language-Jola-Kasa #language-Southern Ping Chinese #language-Croatia Sign Language #language-Southern Ohlone #language-Northern Ohlone #language-Siyin Chin #language-Coos #language-Thaiphum Chin #language-Chhintange #language-Northern Catanduanes Bikol #language-Moundadan Chetty #language-Chug #language-Huizhou Chinese #language-Knaanic #language-Bondum Dom Dogon #language-Deccan #language-West Goodenough #language-Dido #language-Delaware #language-Slave (Athapascan) #language-Southern Dagaare #language-Casiguran Dumagat Agta #language-Andaandi #language-Dogri (individual language) #language-Dhodia #language-Dhanwar (Nepal) #language-Kumiai #language-Dimli (individual language) #language-Diriku #language-Djadjawurrung #language-Djamindjung #language-Eastern Maroon Creole #language-Medefaidrin #language-Dama #language-Kemedzung #language-Dení #language-Dogri (macrolanguage) #language-C'Lela #language-Disa #language-Daur #language-Adithinngithigh #language-Tene Kan Dogon #language-Daatsʼíin #language-Uyajitaya #language-Middle Dutch (ca. 1050-1350) #language-Duli-Gey #language-Djabugay #language-Karenggapa #language-Teke-Ebo #language-Emilian #language-Standard Estonian #language-Modern Greek (1453-) #language-Emerillon #language-Eastern Minyag #language-Middle English (1100-1500) #language-Northwest Alaska Inupiatun #language-Central Yupik #language-Etchemin #language-Eton (Cameroon) #language-Fa d'Ambu #language-Faita #language-Paloor #language-Fanti #language-Southwestern Fars #language-West Albay Bikol #language-Tornedalen Finnish #language-Foau #language-Flaaitaal #language-Fanbak #language-Fernando Po Creole English #language-Middle French (ca. 1400-1600) #language-Eastern Frisian #language-Fortsenal #language-Fulah #language-Nigerian Fulfulde #language-Guarequena #language-Galolen #language-Gbaya (Central African Republic) #language-Karajarri #language-Gbanziri #language-Gagadu #language-Gabi-Gabi #language-Gadjerawang #language-Ghodoberi #language-Kungardutyi #language-Ywom #language-ut-Ma'in #language-Eviya #language-Gurr-goni #language-Gagu #language-Ghadamès #language-Ghulfan #language-Kuke #language-Kija #language-Gaɓogbo #language-Githabul #language-Hinukh #language-Green Gelao #language-Mulao #language-White Gelao #language-Gunditjmara #language-Magɨ (Madang Province) #language-ǂUngkue #language-Belning #language-Northwest Pashai #language-Garlali #language-Magɨyi #language-Middle High German (ca. 1050-1500) #language-Mgbolizhia #language-ǁGana #language-Gozarkhani #language-Guana (Brazil) #language-Ancient Greek (to 1453) #language-Taznatit #language-Nema #language-Swiss German #language-Aghu-Tharnggala #language-Gunwinggu #language-Guana (Paraguay) #language-Guanano #language-Pará Gavião #language-Gawwada #language-ǀGwi #language-Hamba #language-Serbo-Croatian #language-Herdé #language-Hemba #language-Haiǁom #language-Kerak #language-Hoyahoya #language-Tsoa #language-Hong Kong Sign Language #language-Matu Chin #language-Large Flowery Miao #language-Maek #language-Hmong Shua #language-ǁAni #language-Hovongan #language-Hawai'i Sign Language (HSL) #language-Hértevin #language-Middle Hittite #language-San Francisco Del Mar Huave #language-Hungana #language-San Mateo Del Mar Huave #language-San Dionisio Del Mar Huave #language-Sabu #language-Santa María Del Mar Huave #language-Islander Creole English #language-Indo-Portuguese #language-Keley-I Kallahan #language-Iha Based Pidgin #language-Bidhawal #language-Inuktitut #language-Iranun (Malaysia) #language-Iranun (Philippines) #language-Inga #language-Jungle Inga #language-Indonesian Sign Language #language-Inupiaq #language-Iresim #language-Izii #language-Jamamadí #language-Jakati #language-Badjiri #language-Jabutí #language-Jeri Kuo #language-Gwak #language-Bu (Kaduna State) #language-sTodsde #language-Guanyinqiao #language-Koro (India) #language-Amami Koniya Sign Language #language-Jogi #language-Jordanian Sign Language #language-Judeo-Arabic #language-Hupdë #language-Kachin #language-Kabiyè #language-Ngkâlmpw Kanum #language-Kachama-Ganjule #language-Kannada Kurumba #language-Kachhi #language-Karingani #language-Bädi Kanum #language-Khvarshi #language-Kele (Democratic Republic of Congo) #language-Karagas #language-Agob #language-Kirmanjki (individual language) #language-Khinalugh #language-Harijan Kinnauri #language-Kaikavian Literary Language #language-Kaeku #language-Gamilaraay #language-Tagakaulo #language-Migum #language-Majukayang Kalinga #language-Kwama #language-Karipúna Creole French #language-Khorasani Turkish #language-Konda #language-Koongo #language-Western Kanjobal #language-Kanamarí #language-Konkani (individual language) #language-Kung-Ekoka #language-Kodi #language-Kacipo-Bale Suri #language-Konkani (macrolanguage) #language-Kugama #language-Koy Sanjaq Surat #language-Eastern Krahn #language-Kinaray-A #language-Gbaya (Sudan) #language-Southern Kalinga #language-Krisa #language-Juǀʼhoan #language-Kuman (Papua New Guinea) #language-Tsakwambo #language-Kwa #language-Kwakiutl #language-Kofyar #language-Zayein Karen #language-Kanoé #language-Koro (Papua New Guinea) #language-Kalapuya #language-Kelon #language-Southern Subanen #language-Linear A #language-Lama Bai #language-Libon Bikol #language-Rmeet #language-Dũya #language-Lamma #language-Lezghian #language-Lingarak #language-T'apo #language-Mlahsö #language-Likila #language-Lika #language-Lingala #language-Liberian English #language-Yirandali #language-Kungkari #language-Pévé #language-South Lembata #language-Langobardic #language-Leningitij #language-Langam #language-Lorediakarkar #language-Lanima #language-Louisiana Creole #language-Loke #language-Laro #language-Burundian Sign Language #language-Lish #language-Late Middle Chinese #language-Thur #language-Luxembourgish #language-Luiseno #language-Lushai #language-Lushootseed #language-Lavi #language-Levuka #language-Lakurumau #language-Lyngngam #language-Mandingo #language-Ombamba #language-Maquiritari #language-Malaccan Creole Portuguese #language-Cameroon Mambila #language-Minanibai #language-Maguindanaon #language-Miriwoong #language-Mano #language-Mogofin #language-Middle Irish (900-1200) #language-Manda (Tanzania) #language-Mongol #language-Mócheno #language-Digaro-Mishmi #language-Uncoded languages #language-Makalero #language-Tu #language-Mahican #language-Malas #language-Kinamiging Manobo #language-Makasae #language-Malagasy #language-Motlav #language-Malfaxal #language-Malaynon #language-Mundat #language-Musar #language-Musak #language-Manikion #language-Innu #language-Malak Malak #language-Mapidian #language-Misima-Panaeati #language-Pano #language-Marino #language-Malay (macrolanguage) #language-Mono (Solomon Islands) #language-Mator #language-Multiple languages #language-Murrinh-Patha #language-Labo #language-Marwari #language-Miju-Mishmi #language-Nigeria Mambila #language-Inapang #language-Ngan'gityemerri #language-Ca̱hungwa̱rya̱ #language-Ngarrindjeri #language-Ngbinda #language-Ngarinyman #language-South Ndebele #language-Na-kara #language-Chothe Naga #language-North Ndebele #language-Nadruvian #language-Nyenkha #language-Neo-Hittite #language-Nepali (macrolanguage) #language-Newari #language-Ayiwo #language-Nafaanra #language-Mfumte #language-Ngbaka #language-Dalabon #language-Ngurimi #language-Engdewu #language-Kriang #language-Guerrero Nahuatl #language-Nakame #language-Gilyak #language-Nisa #language-Nyishi #language-Khoibu Naga #language-Ngul #language-Nahali #language-Tangkhul Naga (India) #language-Manangba #language-ǃXóõ #language-Moyon Naga #language-Nyangga #language-Nepali (individual language) #language-Noipx #language-Southern Nago #language-Kyan-Karyaw Naga #language-Jèrriais #language-Northern Kalapuya #language-Lower Nossob #language-Northwestern Nisu #language-Tase Naga #language-Ngantangarra #language-Ikoma-Nata-Isenye #language-Tangkhul Naga (Myanmar) #language-Yuanga #language-Anong #language-Classical Newari #language-Ngayawung #language-Middle Newar #language-Nottoway-Meherrin #language-Koki Naga #language-Nyikina #language-Nyungar #language-Nanga Dama Dogon #language-Old Avar #language-Occitan (post 1500) #language-Old Cham #language-Old Hittite #language-Old Hungarian #language-Ontong Java #language-Kobo #language-Koresh-e Rostam #language-Middle Korean (10th-16th cent.) #language-Old Korean (3rd-9th cent.) #language-Omok #language-Old Manipuri #language-Onin Based Pidgin #language-Ong #language-Opata #language-Oriya (macrolanguage) #language-Adivasi Oriya #language-Old Sundanese #language-Ottoman Turkish (1500-1928) #language-Old Tibetan #language-Tagargrent #language-Oune #language-Old Uighur #language-Paumarí #language-Panjabi #language-Pakaásnovos #language-E'ñapa Woromaipu #language-Puebla Mazatec #language-Pyu (Papua New Guinea) #language-Parenga #language-Kayan #language-Northeastern Pomo #language-Kunja #language-Iranian Persian #language-Pere #language-Pfaelzisch #language-Sudanese Creole Arabic #language-Gāndhārī #language-Primitive Irish #language-Phalura #language-Pahari-Potwari #language-Piratapuyo #language-Pileni #language-Ardhamāgadhī Prākrit #language-Pankhu #language-plj #language-San Marcos Tlacoyalco Popoloca #language-Māhārāṣṭri Prākrit #language-Pamlico #language-Lingua Franca #language-Paynamar #language-Pangu #language-Banyjima #language-Pwapwâ #language-Prussian #language-Parauk #language-Prasuni #language-Old Provençal (to 1500) #language-Phai #language-Iranian Sign Language #language-Southwest Pashai #language-Southeast Pashai #language-Pauserna #language-Sauraseni Prākrit #language-Pindiini #language-Puoc #language-Pushto #language-Pyu (Myanmar) #language-Quechua #language-Chimborazo Highland Quichua #language-Yanahuanca Pasco Quechua #language-Kuman (Russia) #language-Kwalhioqua-Tlatskanai #language-Quiripi #language-Canela #language-Rarotongan #language-Rapa #language-Northern Bontok #language-Miraya Bikol #language-Remo #language-Retta #language-Roria #language-Tarifit #language-Riang Lang #language-Ritharrngu #language-Carpathian Romani #language-Sinte Romani #language-Romany #language-Arritinngithigh #language-Romano-Serbian #language-Yurats #language-Macedo-Romanian #language-Karuwali #language-Rāziḥī #language-Chabu #language-Sileibi #language-Sri Lankan Creole Malay #language-Hyolmo #language-Sha #language-Sicel #language-Shabak #language-Surubu #language-Cebaara Senoufo #language-Suarmin #language-Senara Sénoufo #language-Small Flowery Miao #language-Old Irish (to 900) #language-Mag-antsi Ayta #language-Suga #language-Singpho #language-Shahrudi #language-Shehri #language-Tachawit #language-Akkala Sami #language-Sajau Basap #language-Kildin Sami #language-Pite Sami #language-Kemi Sami #language-Sajalong #language-Ter Sami #language-Ume Sami #language-Sakirabiá #language-Sakalava Malagasy #language-Kutong #language-Sissala #language-Ma'ya #language-Southern Sami #language-Northern Sami #language-Lule Sami #language-Inari Sami #language-Skolt Sami #language-Somray #language-Bau Bidayuh #language-South West Bay #language-Songomeno #language-Songo #language-Swo #language-Sian #language-Loreto-Ucayali Spanish #language-Siculo Arabic #language-Kufr Qassem Sign Language (KQSL) #language-Sara #language-Southern Sorsoganon #language-So'a #language-Shark Bay #language-Settla #language-Saterfriesisch #language-Tirmaga-Chai Suri #language-Skalvian #language-Swahili (macrolanguage) #language-Swahili (individual language) #language-Sawknah #language-Sicanian #language-Shuhi #language-Southern Kalapuya #language-Selian #language-Samre #language-Sorothaptic #language-Tabassaran #language-Dharawal #language-Datooga #language-Tawr Chin #language-Tandroy-Mahafaly Malagasy #language-Teke-Tege #language-Tereno #language-Tewa (USA) #language-Tanaina #language-Kuuk Thaayorre #language-Aheu #language-Tidikelt Tamazight #language-Tiéfo #language-Tjungundji #language-Temacine Tamazight #language-Tjupany #language-Talodi #language-Filomena Mata-Coahuitlán Totonac #language-Sou Nama #language-Katbol #language-Tamashek #language-Tembo (Motembo) #language-Ménik #language-Ten'edn #language-tpw #language-Tembé #language-Western Totonac #language-Tarao Naga #language-Sediq #language-Tsishingini #language-Long Wat #language-Tewa (Indonesia) #language-Northern Tiwa #language-Kyanga #language-Central Atlas Tamazight #language-Buhi'non Bikol #language-Tanjijili #language-Muak Sa-aak #language-Meriam Mir #language-Morrobalama #language-Undetermined #language-Kurnai #language-Urali #language-us-Saare #language-ut-Hun #language-Sekele #language-Valman #language-Southwestern Bontok #language-Korlai Creole Portuguese #language-Vlaams #language-Martuyhunira #language-Barbaram #language-Mainfränkisch #language-Vano #language-Vinmavis #language-Awa (China) #language-Walla Walla #language-Wagiman #language-Wara #language-Waigali #language-West Bengal Sign Language #language-Warnman #language-Yanomámi #language-Wadjabangayi #language-Kiunum #language-Westphalien #language-Rawngtu Chin #language-Wejewa #language-Wangkangurru #language-Sou Upaa #language-Wahau Kenyah #language-Wik Ngathan #language-Keerray-Woorroong #language-Wangkayutyuru #language-Wailapa #language-Western Minyag #language-Mokati #language-Kuwema #language-Wè Northern #language-Waluwarra #language-Warungu #language-Gugu Warra #language-Wae Rana #language-Waray (Australia) #language-Wusi #language-Owenia #language-Wetamut #language-Wangaaybuwan-Ngiyambaa #language-Ararandewára #language-ǀXam #language-Aquitanian #language-Kamas #language-Lower Burdekin #language-Bindal #language-Batjala #language-Cumbric #language-Chorasmian #language-Curonian #language-Darkinyung #language-Dharuk #language-Eblan #language-ǁXegwi #language-Epi-Olmec #language-Gabrielino-Fernandeño #language-Garingbal #language-Galindan #language-Harami #language-Hunnic #language-Middle Khmer (1400 to 1850 CE) #language-Indus Valley Language #language-Minjungbal #language-Northern Nago #language-Kenyan Sign Language #language-Kachok #language-Loup B #language-Ligurian (Ancient) #language-Liburnian #language-Alanic #language-Median #language-Kugu-Muminh #language-Ancient Macedonian #language-Manichaean Middle Persian #language-Kanakanabu #language-Middle Mongolian #language-Ngoni (Tanzania) #language-Nganakarti #language-Ngoni (Mozambique) #language-Narragansett #language-Nukunul #language-Nyiyaparli #language-Komo (Sudan) #language-Northeastern Tasmanian #language-Oyster Bay Tasmanian #language-Southeast Tasmanian #language-North Midlands Tasmanian #language-Port Sorell Tasmanian #language-Puyo-Paekche #language-Northern Tasmanian #language-Northwestern Tasmanian #language-Southwestern Tasmanian #language-Puyo #language-Bruny Island Tasmanian #language-Kreye #language-Minang #language-Krikati-Timbira #language-Armazic #language-Aranama-Tamique #language-Sabaean #language-Sambal #language-Scythian #language-Sudovian #language-Early Tripuri #language-Tacahua Mixtec #language-Vandalic #language-Written Oirat #language-Boro (Ghana) #language-Ke'o #language-Zemgalian #language-Ancient Zapotec #language-Yaka (Democratic Republic of Congo) #language-Yakama #language-Yuwana #language-Yakha #language-Yabaâna #language-Yela #language-Yiningayi #language-Yolŋu Sign Language #language-Yan-nhaŋu Sign Language #language-Yidiny #language-Riang Lai #language-Kathu #language-Nyâlayu #language-Yokuts #language-Yongkom #language-Yirrk-Mel #language-Yerong #language-Yaroamë #language-Yassic #language-Myanmar Sign Language #language-Sirenik Yupik #language-Talu #language-Tanglang #language-Yatay #language-Yucateco #language-Yug #language-Yuracare #language-Mayawali #language-Yir Yoront #language-Miahuatlán Zapotec #language-Balaibalan #language-Bu (Bauchi State) #language-Zhuang #language-zkb #language-Khorezmian #language-Kanan #language-Kott #language-Krevinian #language-Khazar #language-Matngala #language-Zande (individual language) #language-Kara (Korea) #language-Zerenkel #language-Kaskean #language-Quioquitani-Quierí Zapotec #language-No linguistic content #language-Zyphe Chin #license-cc-by-4.0 #region-us
|
# Description
Dataset listing 27,328 languages and dialects (also includes macrolanguage names).
For each language, either the ISO 639 code, the Glottolog code or both are provided.
# Columns
- 'English_Name': Language name in English (e.g. '"French"').
- 'Native_Name': If value is not '0', corresponds to the name of the language by native speakers (e.g. '"Français"') which may have been found in Wikipedia's 'nativename' field.
- 'Glottocode': The language tag in the Glottolog convention (e.g. 'stan1290').
- 'near_ISO6393': the ISO 639-3 code closest to the Glottolog convention (e.g. 'fra') This information comes from Glottolog and may therefore be incomplete compared with column '639-3' from ISO.
- '639-3': The language tag in the ISO 639-3 convention (e.g. 'fra').
- '639-2_B': The language tag in the ISO 639-2_B (B for bibliographic) convention (e.g. 'fre').
- '639-2_T': The language tag in the ISO 639-2_T (T for terminological) convention (e.g. 'fra').
- '639-1': The language tag in the ISO 639-1 convention (e.g. 'fr').
- 'Scope': If value is not '0', 'I' for an individual language (e.g. "French"), 'M' for a macrolanguage, 'S' for special i.e non-language codes (e.g. "und" for Undetermined)).
- 'Language_Type': If value is not '0', 'A' for ancient language that went extinct long ago (e.g. 'got' for Gothic), 'C' for constructed i.e artificial languages, excluding programming languages (e.g. 'epo' for Esperanto), 'E' for extinct i.e. language that went extinct recently (e.g. 'rbp' for Barababaraba), 'H' for historical i.e. extinct language distinct from modern languages that descended from it (e.g. 'ofs' for Old Frisian), 'L' for living i.e. currently spoken language (e.g. 'fra' for French), 'S' for special i.e. non-language codes (e.g. 'und' for Undetermined).
- '#L1_Speakers': Indicates a (rounded) estimate of the number of speakers (L1) per language; the estimate comes from Writing System and Speaker Metadata for 2,800+ Language Varieties. | [
"# Description\nDataset listing 27,328 languages and dialects (also includes macrolanguage names). \nFor each language, either the ISO 639 code, the Glottolog code or both are provided.",
"# Columns\n- 'English_Name': Language name in English (e.g. '\"French\"').\n- 'Native_Name': If value is not '0', corresponds to the name of the language by native speakers (e.g. '\"Français\"') which may have been found in Wikipedia's 'nativename' field.\n- 'Glottocode': The language tag in the Glottolog convention (e.g. 'stan1290').\n- 'near_ISO6393': the ISO 639-3 code closest to the Glottolog convention (e.g. 'fra') This information comes from Glottolog and may therefore be incomplete compared with column '639-3' from ISO.\n- '639-3': The language tag in the ISO 639-3 convention (e.g. 'fra').\n- '639-2_B': The language tag in the ISO 639-2_B (B for bibliographic) convention (e.g. 'fre').\n- '639-2_T': The language tag in the ISO 639-2_T (T for terminological) convention (e.g. 'fra').\n- '639-1': The language tag in the ISO 639-1 convention (e.g. 'fr').\n- 'Scope': If value is not '0', 'I' for an individual language (e.g. \"French\"), 'M' for a macrolanguage, 'S' for special i.e non-language codes (e.g. \"und\" for Undetermined)).\n- 'Language_Type': If value is not '0', 'A' for ancient language that went extinct long ago (e.g. 'got' for Gothic), 'C' for constructed i.e artificial languages, excluding programming languages (e.g. 'epo' for Esperanto), 'E' for extinct i.e. language that went extinct recently (e.g. 'rbp' for Barababaraba), 'H' for historical i.e. extinct language distinct from modern languages that descended from it (e.g. 'ofs' for Old Frisian), 'L' for living i.e. currently spoken language (e.g. 'fra' for French), 'S' for special i.e. non-language codes (e.g. 'und' for Undetermined).\n- '#L1_Speakers': Indicates a (rounded) estimate of the number of speakers (L1) per language; the estimate comes from Writing System and Speaker Metadata for 2,800+ Language Varieties."
] | [
"TAGS\n#size_categories-1K<n<10K #language-Afade #language-Pará Arára #language-Afar #language-Aka-Bea #language-Abon #language-Abaza #language-Pal #language-Aneme Wake #language-Abui #language-Aka-Cari #language-Aka-Kora #language-Akar-Bale #language-Achang #language-Achi #language-Achumawi #language-Adele #language-Adonara #language-Adnyamathanha #language-Adyghe #language-Haeke #language-Aer #language-Ambakich #language-Amele #language-Andai #language-Akrukay #language-Defaka #language-Eloyi #language-Obokuitai #language-Agatu #language-Angal #language-Angor #language-Ngelima #language-Fembe #language-Tainae #language-Aghem #language-Aguaruna #language-Kahua #language-Aghul #language-Qimant #language-Ahom #language-Ake #language-Aimele #language-Aiton #language-Aka-Jeru #language-Akkadian #language-Aklanon #language-Aka-Bo #language-Siwu #language-Akhvakh #language-Aka-Kede #language-Aka-Kol #language-Alabama #language-Alago #language-Aleut #language-Alege #language-Algonquin #language-Southern Altai #language-Alur #language-Yanesha' #language-Amis #language-Amdang #language-Guerrero Amuzgo #language-Ambelau #language-Andaqui #language-Nend #language-Andi #language-Obolo #language-Andoque #language-Denya #language-Anyin #language-Pemon #language-Angoram #language-Anindilyakwa #language-Mufian #language-Taikat #language-Atorada #language-Uab Meto #language-Apinayé #language-A-Pucikwar #language-Apatani #language-Western Apache #language-Safeyoka #language-Archi #language-Atohwaim #language-Atakapa #language-Angaité #language-Aragonese #language-Arhuaco #language-Arikara #language-Arikapú #language-Arabela #language-Arapaho #language-Arawak #language-Assiniboine #language-Casuarina Coast Asmat #language-Assamese #language-Ipulo #language-Asturian #language-Muratayak #language-Zaiwa #language-Atikamekw #language-Aralle-Tabulahan #language-Reel #language-Northern Altai #language-Arutani #language-Waorani #language-Aguna #language-Aushi #language-Heyo #language-Makayam #language-Anus #language-Aurá #language-Awiyaana #language-Avatime #language-Avá-Canoeiro #language-Awadhi #language-Mato Grosso Arára #language-Ginyanga #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bambara #language-Balinese #language-Bantawa #language-Vengo #language-Barama #language-Babanki #language-Bats #language-Uneapa #language-Bamali #language-Girawa #language-Baba #language-Bannoni #language-Kaluli #language-Bench #language-Budukh #language-Baldemu #language-Bahnar #language-Bokoto #language-Oroko #language-Bodo Parja #language-Baham #language-Budong-Budong #language-Iceve-Maci #language-Beja #language-Belarusian #language-Bengali #language-Blagar #language-Betawi #language-Bari #language-Pauri Bareli #language-Betaf #language-Bofi #language-Blafe #language-Mmen #language-Badaga #language-Balti #language-Bantayanon #language-Bagheli #language-Gwamhi-Wuri #language-Haryanvi #language-Rathwi Bareli #language-Bagri #language-Bhatri #language-Bhili #language-Bhojpuri #language-Bima #language-Buwal #language-Biak #language-Bhele #language-Bissa #language-Bile #language-Nai #language-Bila #language-Berinomo #language-Southern Birifor #language-Budza #language-Burji #language-Binumarien #language-Baruga #language-Beeke #language-Pande #language-Buhid #language-Bekwarra #language-Bokyi #language-Bolango #language-Buol #language-Biloxi #language-Southern Catanduanes Bikol #language-Baluan-Pam #language-Blang #language-Tai Dam #language-Notre #language-Balantak #language-Lame #language-Kein #language-Bagirmi #language-Bomu #language-Muinane #language-Bookan #language-Masiwang #language-Benga #language-Bangi #language-Bunun #language-Bintulu #language-Bora #language-Boma #language-Anjam #language-Bole #language-Berom #language-Bosnian #language-Buamu #language-Bauni #language-Botlikh #language-Orowe #language-Dzao Min #language-Barrow Point #language-Palya Bareli #language-Bilba #language-Baima #language-Bandial #language-Biritai #language-Bamukumbit #language-Koro Wachi #language-Baangi #language-Breton #language-Bira #language-Brahui #language-Brokkat #language-Abinomn #language-Bassari #language-Wushi #language-Bashkardi #language-Bangwinji #language-Basa-Gumna #language-Barasana-Eduria #language-Bassa #language-Yangkam #language-Bata #language-Gamo-Ningi #language-Ratagnon #language-Rinconada Bikol #language-Batak Simalungun #language-Bete-Bendi #language-Batu #language-Bateri #language-Batak Karo #language-Bushi #language-Ntcham #language-Beothuk #language-Buginese #language-Bulgarian #language-Terei #language-Budu #language-Baeggu #language-Belanda Viri #language-Baan #language-Bolgo #language-Bwe Karen #language-Bafaw-Balong #language-Bwa #language-Cwi Bwamu #language-Bebil #language-Bhujel #language-Burak #language-Medumba #language-Qaqet #language-Andio #language-Bribri #language-Mapos Buang #language-Chuj #language-Caddo #language-Nivaclé #language-Kaqchikel #language-Carolinian #language-Chipaya #language-Catalan #language-Chiquitano #language-Cayuga #language-Carapana #language-Carijona #language-Chimila #language-Chayahuita #language-Candoshi-Shapra #language-Carabayo #language-Chamicuro #language-Chopi #language-Atsam #language-Chakma #language-Choni #language-Chenchu #language-Chiru #language-Chodri #language-Chepang #language-Lower Chehalis #language-Cebuano #language-Chamacoco #language-Czech #language-Cara #language-Chamorro #language-Chibcha #language-Catawba #language-Chechen #language-Chagatai #language-Chuukese #language-Cahuilla #language-Choctaw #language-Chipewyan #language-Cherokee #language-Cholón #language-Chuvash #language-Chuwabu #language-Cheyenne #language-Cia-Cia #language-Chickasaw #language-Chinali #language-Chitkuli Kinnauri #language-Cimbrian #language-Upper Chehalis #language-Chamalal #language-Chokwe #language-Shor #language-Cibak #language-Koasati #language-Kavalan #language-Chulym #language-Cerma #language-Changthang #language-Northern Qiang #language-Hakha Chin #language-Asháninka #language-Chung #language-Montenegrin #language-Chicomuceltec #language-Koreguaje #language-Chong #language-Comanche #language-Cofán #language-Comox #language-Coptic #language-Cornish #language-Corsican #language-Caquinte #language-Wamey #language-Nanti #language-Capiznon #language-Lonwolwol #language-Coeur d'Alene #language-Cree #language-Crimean Tatar #language-Plains Cree #language-Moose Cree #language-Crow #language-Carolina Algonquian #language-Chaura #language-Carrier #language-Cruzeño #language-Kashubian #language-Swampy Cree #language-Chittagonian #language-Chitimacha #language-Cubeo #language-Mashco Piro #language-Cumanagoto #language-Cupeño #language-Tai Ya #language-Kwere #language-Welsh #language-Dangaléat #language-Dagbani #language-Gwahatike #language-Dakota #language-Danish #language-Dargwa #language-Bangime #language-Dadiya #language-Dibiyaso #language-Dongotono #language-Dagik #language-Dehwari #language-Dem #language-Deori #language-Desano #language-German #language-Domung #language-Dogrib #language-Dogoso #language-Dhundari #language-Dhimal #language-Zemba #language-Dia #language-Digo #language-Dilling #language-Dinka #language-Dibo #language-Dimasa #language-Ding #language-Zarma #language-Jawoyn #language-Jangkang #language-Dolgan #language-Dahalik #language-Dalmatian #language-Gavak #language-Dameli #language-East Damar #language-Demta #language-Dungan #language-Dan #language-Dengka #language-Danau #language-Western Dani #language-Dom #language-Domu #language-Bussa #language-Minderico #language-Darmiya #language-Paakantyi #language-West Damar #language-Rukai #language-Lower Sorbian #language-Ditidaht #language-Dumun #language-Jola-Fonyi #language-Dyula #language-Tunzu #language-Eastern Bontok #language-Ebrié #language-Embu #language-E #language-Efik #language-Eggon #language-Askopan #language-Ekari #language-Koti #language-Yace #language-Elepi #language-Nding #language-Mamulique #language-Erromintxela #language-Apali #language-Enlhet #language-Engenni #language-Enxet #language-Eravallan #language-Ogea #language-Horpa #language-Eritai #language-Ese Ejja #language-Esselen #language-Central Siberian Yupik #language-Estonian #language-Eskayan #language-Eten #language-Basque #language-Even #language-Uvbie #language-Evenki #language-Ewe #language-Extremaduran #language-Keiyo #language-Fasu #language-Wagi #language-Faroese #language-Persian #language-Foia Foia #language-Fongoro #language-Nobiin #language-Faifi #language-Fijian #language-Filipino #language-Finnish #language-Fipa #language-Firan #language-Kirya-Konzəl #language-Fania #language-Fon #language-Fas #language-French #language-Fordata #language-Frankish #language-Pulaar #language-Friulian #language-Furu #language-Fur #language-Fwe #language-Ga #language-Gagauz #language-Alekano #language-Gamkonora #language-Gants #language-Nobonob #language-Gayo #language-Gaddi #language-Garhwali #language-Zoroastrian Dari #language-Mali #language-Galice #language-Gurdjar #language-Dirasha #language-Laal #language-Umanakaina #language-Wipi #language-Geruma #language-Kire #language-Gebe #language-Gen #language-Gera #language-Garre #language-Enya #language-Patpatar #language-Kungarakany #language-Ghanongga #language-Gidar #language-Gilbertese #language-Gitxsan #language-Gujari #language-Kok-Nar #language-Nanai #language-Irish #language-Galician #language-Gilaki #language-Manx #language-Glavda #language-Gula'alaa #language-Kaansa #language-Ngangam #language-Guntai #language-Gongduk #language-Gogo #language-Gobasi #language-Gondi #language-Gorontalo #language-Goo #language-Guiqiong #language-Grebo #language-Gbiri-Niragu #language-Guarani #language-Garo #language-Shiki #language-Wayuu #language-Guahibo #language-Eastern Bolivian Guaraní #language-Gujarati #language-Mbyá Guaraní #language-Guayabero #language-Aché #language-Farefare #language-Yanomamö #language-Gun #language-Gusii #language-Duwet #language-Guajá #language-Gulay #language-Gawri #language-Gweno #language-Gwichʼin #language-Gwere #language-Gyalsumdo #language-Guarayu #language-Ganza #language-Haida #language-Hajong #language-Hangaza #language-Ha #language-Harari #language-Haisla #language-Hausa #language-Havu #language-Hawaiian #language-Haya #language-Huba #language-Heiban #language-Huichol #language-Hebrew #language-Hehe #language-Herero #language-Hoia Hoia #language-Hidatsa #language-Pamosu #language-Hinduri #language-Hiligaynon #language-Hittite #language-Hunde #language-Halbi #language-Hlersu #language-Hmong #language-Hamtai #language-Chhattisgarhi #language-Hani #language-Hanunoo #language-Ho #language-Horom #language-Holikachuk #language-Holu #language-Holoholo #language-Hopi #language-Hote #language-Hrangkhol #language-Hruso #language-Croatian #language-Upper Sorbian #language-Minica Huitoto #language-Hadza #language-Huilliche #language-Hungarian #language-Hupa #language-Huastec #language-Hukumina #language-Nüpode Huitoto #language-Hunzib #language-Armenian #language-Iaai #language-Iatmul #language-Iban #language-Ibibio #language-Ibaloi #language-Agoi #language-Igbo #language-Idon #language-Idoma #language-Kanggape #language-Iha #language-Izon #language-Kalabari #language-Ik #language-Ikizu #language-Ila #language-Ili Turki #language-Anamgura #language-Miluk #language-Milyan #language-Indonesian #language-Ingush #language-Inor #language-Irarutu #language-Rigwe #language-Iraqw #language-Irula #language-Kamberau #language-Esan #language-Nkem-Nkum #language-Ishkashimi #language-Icelandic #language-Isanzu #language-Istriot #language-Italian #language-Itelmen #language-Itonama #language-Iteri #language-Iu Mien #language-Ivatan #language-Iwur #language-Sepik Iwam #language-Ixcatec #language-Mesaka #language-Ingrian #language-Izere #language-Hyam #language-Yabem #language-Yalahatan #language-Javanese #language-Nafusi #language-Jukun Takum #language-Krymchak #language-Jadgali #language-Jebero #language-Yelmek #language-Manem #language-Ngbee #language-Ngomba #language-Tol #language-Jingulu #language-Jiamao #language-Jita #language-Shuar #language-Labir #language-Ngile #language-Dima #language-Zumbun #language-Jumli #language-Janji #language-Jowulu #language-Japanese #language-Jaqaru #language-Jarai #language-Wapan #language-Juang #language-Jiba #language-Jwira-Pepesa #language-Kabyle #language-Adara #language-Jju #language-Bezhta #language-Kashmiri #language-Georgian #language-Kanuri #language-Kazakh #language-Kabardian #language-Kari #language-Kafa #language-Kabutra #language-Duhwa #language-Khanty #language-Tyap #language-Kalanga #language-Nubi #language-Kamo #language-Katla #language-Kaian #language-Kabwari #language-Korandje #language-Makonde #language-Tem #language-Numèè #language-Kunda #language-Karaim #language-Kuy #language-Kam #language-Kerewe #language-Tese #language-Keak #language-Kenyang #language-Ket #language-Kanikkaran #language-Koya #language-Kinnauri #language-Khunsari #language-Korwa #language-Korku #language-Kanjari #language-Kumaoni #language-Komering #language-Kusunda #language-Kaiwá #language-Kaingang #language-Somyev #language-Kobol #language-Karas #language-Khasi #language-Korowai #language-Lusi #language-Khmer #language-Kharia #language-Khamti #language-Koalib #language-Kikuyu #language-Kariya #language-Kiowa #language-Kimbu #language-Kirikiri #language-Khmu #language-Khakas #language-Highland Konjo #language-Kháng #language-Kunjen #language-Kashaya #language-Ramopa #language-Kinuku #language-Khün #language-Kokota #language-Kiong #language-Giiwo #language-Koi #language-Kangean #language-Kaska #language-Kiliwa #language-Kendeje #language-Khalaj #language-Rumu #language-Khaling #language-Kalasha #language-Klao #language-Kalao #language-Konni #language-Kanufi #language-Kwanja #language-Tabo #language-Kendayan #language-Kalamsé #language-Komi #language-Kongo #language-Waube #language-Korean #language-Lagwan #language-Koyukon #language-Kutto #language-Kpelle #language-Komba #language-Kapingamarangi #language-Karajá #language-Koho #language-Tehit #language-Kafoa #language-Koryak #language-Kupsabiny #language-Mum #language-Khe #language-Kyenele #language-Kaonde #language-Kimré #language-Seroa #language-Okolod #language-Panará #language-Kurama #language-Karelian #language-Kurukh #language-Kryts #language-Shambala #language-Kansa #language-Kumba #language-Kaba #language-Borong #language-S'gaw Karen #language-Nubri #language-Kurti #language-Kwinsu #language-Kuria #language-Kumyk #language-Kunama #language-Kusaal #language-Kutenai #language-Upper Kuskokwim #language-Kunza #language-Bagvalal #language-Kalabakan #language-Kabalai #language-Kayaw #language-Kerinci #language-Wersing #language-Kwerba #language-Kwara'ae #language-Kowiai #language-Kwangali #language-Kwese #language-Kwadi #language-Keningau Murut #language-Kuvi #language-Kayagar #language-Rapoisi #language-Kayeli #language-Kais #language-Karang #language-Lacandon #language-Lambya #language-Lamba #language-Laru #language-Lao #language-Qabiao #language-Latvian #language-Aribwatsa #language-Lak #language-Tinani #language-Ladakhi #language-Central Bontok #language-Wampar #language-Lardil #language-Loncong #language-Lisela #language-Luhu #language-Luri #language-Lemoro #language-Kaan #language-Loo #language-Tso #language-Lala-Bisa #language-Leco #language-Lendu #language-Lyélé #language-Lelemi #language-Lenje #language-Lengola #language-Lese #language-Lesing-Gelimi #language-Luang #language-Lemolang #language-Logba #language-Pahi #language-Lahu #language-Limbu #language-Lihir #language-Ligurian #language-Lillooet #language-Lisu #language-Lithuanian #language-Col #language-Laiyolo #language-Lakha #language-Laki #language-Remun #language-Khayo #language-Päri #language-Lakota #language-Lokoya #language-Ladin #language-Lole #language-Lilau #language-North Efate #language-Lau #language-Limilngan #language-Lumun #language-Lamkang #language-Lombard #language-Limbum #language-Lanoh #language-Longuda #language-Loloda #language-Lobi #language-Saluan #language-Logol #language-Loko #language-Mongo #language-Malawi Lomwe #language-Lopa #language-Otuho #language-Lozi #language-Lipo #language-Lopit #language-Marachi #language-Lashi #language-Aruop #language-Latgalian #language-Luba-Katanga #language-Lunda #language-Lumbu #language-Lwalu #language-Luyana #language-Litzlitz #language-Laz #language-Madurese #language-Magahi #language-Marshallese #language-Maithili #language-Mam #language-Marathi #language-Mampruli #language-Maxakalí #language-Macaguán #language-Mbula-Bwazza #language-Memoni #language-Bitur #language-Matsés #language-Mvanip #language-Mbunda #language-Moksha #language-Mangbetu #language-Mbole #language-Mbere #language-Ikobi #language-Megam #language-Meyah #language-Meru #language-Maaka #language-Menominee #language-Naki #language-Wandala #language-Mbe #language-Marrithiyel #language-Moru #language-Maklew #language-Mpumpong #language-Abureni #language-Malila #language-Mambwe-Lungu #language-Mailu #language-Matengo #language-Matumbi #language-Mbugu #language-Ma'di #language-Mauwake #language-Mandan #language-Mbukushu #language-Mi'kmaq #language-Mandaic #language-Minangkabau #language-Akoye #language-Muskum #language-Miship #language-Karbi #language-Mbre #language-Mal Paharia #language-Siliput #language-Macedonian #language-Dhatki #language-Mokilese #language-Byep #language-Mingang Doso #language-Moikodi #language-Bay Miwok #language-Cao Lan #language-Mal #language-Ilwana #language-Bargam #language-Vame #language-Masalit #language-Maltese #language-Moloko #language-Mangga Buang #language-Siawi #language-Malalamai #language-Miriti #language-Emae #language-Muna #language-Manchu #language-Mondé #language-Munji #language-Mansi #language-Mon #language-Mohawk #language-Mboi #language-Morori #language-Mangue #language-Moro #language-Barí #language-Molima #language-Mpoto #language-Majang #language-Marba #language-Maung #language-Mpi #language-Manipa #language-West Makian #language-Maricopa #language-Elseng #language-Mising #language-Mangareva #language-Mandaya #language-Mekwei #language-Mansaka #language-Caac #language-Aruamu #language-Mualang #language-Moskona #language-Montol #language-Muong #language-Mewari #language-Nabi #language-Mundang #language-Musgu #language-Nyong #language-Malvi #language-Muthuvan #language-Duri #language-Massep #language-Marfa #language-Juwal #language-Mirandese #language-Sar #language-Mentawai #language-Mele-Fila #language-Malgbe #language-Meramera #language-Mbowe #language-Burmese #language-Mbay #language-Myene #language-Bambassi #language-Manta #language-Makah #language-Pirahã #language-Erzya #language-Macuna #language-Mumuye #language-Mazanderani #language-Movima #language-Mintil #language-Deg #language-Nakanai #language-Neapolitan #language-Khoekhoe #language-Navajo #language-Ndoe #language-Nkukoli #language-Nnam #language-Iyo #language-Nisga'a #language-Natchez #language-Nde-Nsele-Nta #language-Ndengereko #language-Ndali #language-Ndo #language-Lutos #language-Negidal #language-Ná-Meo #language-Yahadian #language-Nyaheun #language-Nez Perce #language-Dhao #language-Ahwai #language-Nǁng #language-Lomwe #language-Ngwo #language-Ngulu #language-Nagumi #language-Tibea #language-Beng #language-Nias #language-Niellim #language-Ngalakgan #language-Nii #language-Southern Nicobarese #language-Ninzo #language-Nganasan #language-Nimboran #language-Niuean #language-Hema #language-Ngiti #language-Nkoya #language-Koireng #language-Nukuoro #language-North Asmat #language-Nalca #language-Dutch #language-Nyali #language-Big Nambas #language-Ngam #language-Kwasio #language-Namakura #language-Nambya #language-Nimbari #language-Namuyi #language-Nawdm #language-Nande #language-Ngiemboon #language-Ngindo #language-Dwang #language-Northern Thai #language-Nimadi #language-Nogai #language-Nonuya #language-Nooksack #language-Nomlaki #language-Norwegian #language-Nomatsiguenga #language-Nyambo #language-Noy #language-Nara #language-Narom #language-Norn #language-Nsenga #language-Naskapi #language-Nsongo #language-Nisenan #language-Natioro #language-Delo #language-Mantsi #language-Nuu-chah-nulth #language-Nuer #language-Nunggubuyu #language-Nyokon #language-Nawaru #language-Naxi #language-Ninggerum #language-Nyanga #language-Nyaneka #language-Nyoro #language-Nyang'i #language-Nyungwe #language-Njebi #language-Nzadi #language-Nzakambay #language-Oroch #language-Obispeño #language-Ocaina #language-Ogbia #language-Khana #language-Ogbronuagum #language-Okanagan #language-Okodia #language-Oko-Juwoi #language-Oku #language-Olrat #language-Mochica #language-Utarmbung #language-Omotik #language-Ona #language-Oneida #language-Onondaga #language-Sartang #language-Oksapmin #language-Orejón #language-Oromo #language-Odia #language-Osage #language-Ososo #language-Ossetian #language-Oti #language-Otoro #language-Pagibete #language-Pangasinan #language-Pe #language-Parya #language-Palauan #language-Pankararú #language-Páez #language-Paraujano #language-Parkwa #language-Badyara #language-Pangwa #language-Pnar #language-Pear #language-Bouyei #language-Picard #language-Paniya #language-Duruwa #language-Pardhi #language-Piti #language-Podena #language-Eastern Pomo #language-Bonan #language-Phudagi #language-Phuong #language-Phukha #language-Phake #language-Phunoi #language-Phu Thai #language-Phuan #language-Pahlavani #language-Pima Bajo #language-Yine #language-Pinji #language-Piaroa #language-Piapoco #language-Pero #language-Pimbwe #language-Pokomo #language-Maleng #language-Palu'e #language-Palikúr #language-Tuamotuan #language-Penrhyn #language-Paleni #language-Polish #language-Pohnpeian #language-Portuguese #language-Potawatomi #language-Polabian #language-Pogolo #language-Paipai #language-Uma #language-Pare #language-Puragi #language-Parawen #language-Panasuan #language-Pai Tavytera #language-Zo'é #language-Enrekang #language-Bambam #language-Port Vato #language-Pentlatch #language-Puelche #language-Puinave #language-Puma #language-Punu #language-Patwin #language-Paiwan #language-Quapaw #language-Quileute #language-Quinault #language-Logooli #language-Rabha #language-Riantana #language-Rao #language-Rawang #language-Barababaraba #language-Reli #language-Rejang #language-Rengao #language-Reshe #language-Reyesano #language-Ringgou #language-Rohingya #language-Yahang #language-Nungu #language-Rikbaktsa #language-Rakhine #language-Rangpuri #language-Rama #language-Rembarrnga #language-Angloromani #language-Domari #language-Welsh Romani #language-Vlax Romani #language-Ruund #language-Rungwa #language-Rombo #language-Romansh #language-Romblomanon #language-Romanian #language-Dela-Oenale #language-Ruthenian #language-Rotuman #language-Gungu #language-Ruuli #language-Rusyn #language-Luguru #language-Russian #language-Rutul #language-Ruma #language-Rawa #language-Yaeyama #language-Sandawe #language-Sango #language-Yakut #language-Sake #language-Samaritan Aramaic #language-Samburu #language-Santali #language-Saleman #language-Saya #language-Saurashtra #language-Safwa #language-Sabüm #language-Kimki #language-Soli #language-Sakachep #language-Sicilian #language-Scots #language-Sa'och #language-Suundi #language-Sherdukpen #language-Semai #language-Seneca #language-Seri #language-Sekani #language-Serrano #language-Secoya #language-Sehwi #language-Shughni #language-Sangkong #language-Singa #language-Samogitian #language-Sanglechi #language-Ninam #language-Sonde #language-Kundal Shahi #language-Shoshoni #language-Shatt #language-Shilluk #language-Shan #language-Shi #language-Shuswap #language-Shwai #language-She #language-Siamou #language-Paasaal #language-Zire #language-Sikiana #language-Sinhala #language-Sikkimese #language-Siuslaw #language-Sinagen #language-Siwai #language-Sumau #language-Sivandi #language-Siwi #language-Xibe #language-Surjapuri #language-Siar-Lak #language-Shawnee #language-Saek #language-Saraiki #language-Maia #language-Skou #language-Slovak #language-Salt-Yui #language-Salar #language-Salampasu #language-Selayar #language-Bolinao #language-Samoan #language-Simeulue #language-Simte #language-Sumbawa #language-Semnani #language-Shona #language-Sindhi #language-Noon #language-Soninke #language-Siona #language-Sam #language-Kou #language-Thai Song #language-Sogdian #language-Aka #language-Somali #language-Kanasi #language-Somrai #language-Southern Thai #language-Spanish #language-Sapé #language-Akukem #language-Sanapaná #language-Saposa #language-Sapuan #language-Sambalpuri #language-Sabaot #language-Shau #language-Albanian #language-Soqotri #language-Squamish #language-Sora #language-Sardinian #language-Sarikoli #language-Siriano #language-Saramaccan #language-Serbian #language-Sirionó #language-Serer #language-Sirmauri #language-Thao #language-Sansi #language-Sunam #language-Semnam #language-Owa #language-Stoney #language-Siberian Tatar #language-Suku #language-Sukuma #language-Sundanese #language-Susu #language-Puroik #language-Sumbwa #language-Sumerian #language-Suyá #language-Sunwar #language-Svan #language-Swedish #language-Sui #language-Saweru #language-Shekhawati #language-Sighu #language-Saaroa #language-Sukur #language-Sylheti #language-Suoy #language-Syriac #language-Sinyar #language-Kagate #language-Samay #language-Ngalum #language-Silesian #language-Sula #language-Suabo #language-Sawai #language-Lower Tanana #language-Tagoi #language-Tahitian #language-Tamil #language-Yami #language-Taabwa #language-Tamasheq #language-Tatar #language-Upper Tanana #language-Tatuyo #language-Tocho #language-Aikanã #language-Tanimbili #language-Gaam #language-Calamian Tagbanwa #language-Taworta #language-Tembo (Kitembo) #language-Ticuna #language-Tanacross #language-Tamagario #language-Tulu #language-Tagdal #language-Thulung #language-Toro #language-Terik #language-Teressa #language-Tehuelche #language-Torricelli #language-Telugu #language-Teso #language-Temein #language-Tetum #language-Soo #language-Tetserret #language-Teribe #language-Ternate #language-Tajik #language-Tagalog #language-Tangoa #language-Tagish #language-Thai #language-Thangmi #language-Thompson #language-Thakali #language-Tahltan #language-Tha #language-Tigre #language-Tiene #language-Tilung #language-Tillamook #language-Tindi #language-Tigrinya #language-Tinigua #language-Tiv #language-Tai Laing #language-Djabwurrung #language-Takelma #language-Tsakhur #language-Mur Pano #language-Klingon #language-Tlingit #language-Tetela #language-Tai Loi #language-Khehek #language-Talysh #language-Haruai #language-Toba-Maskoy #language-Samarokena #language-Tima #language-Iau #language-Temuan #language-Tanimuca-Retuarã #language-Tobanga #language-Kwamera #language-Lenakel #language-Tabla #language-Tanema #language-Tongwe #language-Tolowa #language-Tombulu #language-Toposa #language-Jemez #language-Tobian #language-Kula #language-Trumai #language-Tinputz #language-Lehali #language-Toaripi #language-Taushiro #language-Turoyo #language-Torwali #language-Tsaangi #language-Tsamai #language-Tswa #language-Tsakonian #language-Tausug #language-Tswana #language-Tsonga #language-Tsou #language-Tsogo #language-Mubami #language-Tutelo #language-Gaa #language-Tobati #language-Tooro #language-Totela #language-Titan #language-Wiarumus #language-Tübatulabal #language-Mutu #language-Tuyuca #language-Turkmen #language-Tumbuka #language-Tunica #language-Tucano #language-Turkish #language-Tuscarora #language-Tututni #language-Turkana #language-Tugen #language-Turka #language-Southeast Ambrym #language-Taivoan #language-Twana #language-Tai Dón #language-Twendi #language-Tasawaq #language-Termanu #language-Tsetsaut #language-Tangut #language-Ikpeng #language-Tii #language-Tatana #language-Tauya #language-Tai Daeng #language-Tày #language-Tzeltal #language-Tzotzil #language-Tabriak #language-Kuan #language-Tairuma #language-Ubykh #language-Udi #language-Udmurt #language-Kubachi #language-Ukrainian #language-Ukwuani-Aboh-Ndoni #language-Ulukwumi #language-Ulch #language-Lule #language-Usku #language-Ulithian #language-Ullatan #language-Umpila #language-Munsee #language-Uneme #language-Ngarinyin #language-Mundari #language-Urarina #language-Uru #language-Urak Lawoi' #language-Sop #language-Uya #language-Urum #language-U #language-West Uvean #language-Uri #language-Uzbek #language-Southern Uzbek #language-Vai #language-Huarijio #language-Vasavi #language-Vanuma #language-Varli #language-Venetian #language-Venda #language-Ventureño #language-Veps #language-Vietnamese #language-Vili #language-Kaur #language-Lungalunga #language-Makhuwa #language-Votic #language-Võro #language-Vumbu #language-Wan #language-Washo #language-Kaninuwa #language-Waritai #language-Wanda #language-Vwanji #language-Wakhi #language-Wa #language-Wadjiginy #language-Warrgamay #language-Wichita #language-Minidien #language-Ho-Chunk #language-Vitu #language-Waja #language-Wakde #language-Walloon #language-Wallisian #language-Wambule #language-Wamin #language-Mwani #language-Wantoat #language-Wanggamala #language-Wanap #language-Usan #language-Wintu #language-Wolof #language-Wongo #language-Wiradjuri #language-Warembori #language-Watiwa #language-Berta #language-Watakataui #language-Mewati #language-Silimo #language-Wurrugu #language-Wutung #language-Waama #language-Wymysorys #language-Wyandot #language-Wayoró #language-Adai #language-Xamtanga #language-Kawaiisu #language-Bactrian #language-Kambiwá #language-Chemakum #language-Kaitag #language-Hdi #language-Kembayan #language-Guwa #language-Xhosa #language-Kalkoti #language-Mainstream Kenyah #language-Kiorr #language-Kgalagadi #language-Kamula #language-Lycian #language-Mbudum #language-Mingrelian #language-Mengaka #language-Anglo-Norman #language-Kangri #language-Kenzi #language-Soga #language-Konkomba #language-Mohegan-Pequot #language-Parthian #language-Karakhanid #language-Solano #language-Sherpa #language-Sanumá #language-Saisiyat #language-Ketengban #language-Betta Kurumba #language-Kunigami #language-Kuo #language-Kwaza #language-Woccon #language-Kwerba Mamberamo #language-Wemba Wemba #language-Yorta Yorta #language-Zhang-Zhung #language-Yagua #language-Yao #language-Yapese #language-Yaqui #language-Yala #language-Yemba #language-Hasha #language-Yukuben #language-Lolopo #language-Yucuna #language-Yidgha #language-Yevanic #language-Tarok #language-Nyankpa #language-Yapunda #language-Yeyi #language-Awu #language-Yasa #language-Yaul #language-Yele #language-Yelogu #language-Yameo #language-Moji #language-Makwe #language-Yamna #language-Muzi #language-Naukan Yupik #language-Yong #language-Yansi #language-Yonaguni #language-Yoron #language-Phola #language-Phupha #language-Sani #language-Yessan-Mayo #language-Yuchi #language-Yuki #language-Yulu #language-Quechan #language-Yukpa #language-Yurok #language-Southern Yukaghir #language-Kalou #language-Yuyu #language-Zaghawa #language-Zenaga #language-Kinga #language-Zhaba #language-Dai Zhuang #language-Zhire #language-Nong Zhuang #language-Chinese #language-Zialo #language-Mesme #language-Zinza #language-Zigula #language-Zizilivakan #language-Karankawa #language-Zakhring #language-Kaurna #language-Zimba #language-Mfinu #language-Mbangwe #language-Mpuono #language-Mbariman-Gudhinma #language-Zarphatic #language-Zulu #language-Zuni #language-Zay #language-Yang Zhuang #language-Abun #language-Anem #language-Bilua #language-Bogaya #language-Burmeso #language-Burushaski #language-Camsá #language-Canichana #language-Cayuse #language-Cayubaba #language-Chimariko #language-Coahuilteco #language-Cotoname #language-Cuitlatec #language-Damal #language-Duna #language-Elamite #language-Etruscan #language-Fulniô #language-Fuyug #language-Guató #language-Gule #language-Gumuz #language-Guriaso #language-Hattic #language-Iberian #language-Kaki Ae #language-Kapori #language-Karami #language-Karok #language-Kehu #language-Kenaboi #language-Kibiri #language-Klamath-Modoc #language-Kol (Papua New Guinea) #language-Kujarge #language-Kuot #language-Lafofa #language-Laragia #language-Lavukaleve #language-Máku #language-Mawes #language-Meroitic #language-Minkin #language-Molale #language-Molof #language-Mor (Bomberai Peninsula) #language-Mpur #language-Muniche #language-Nihali #language-Odiai #language-Omurano #language-Papi #language-Pawaia #language-Pele-Ata #language-Pumé #language-Puquina #language-Purari #language-Salinan #language-Sause #language-Savosavo #language-Shom Peng #language-Sulka #language-Taiap #language-Tambora #language-Tanahmerah #language-Taruma #language-Tauade #language-Timucua #language-Tiwi #language-Tonkawa #language-Touo #language-Tsimshian #language-Tuxá #language-Umbugarla #language-Vilela #language-Warao #language-Wiru #language-Xukurú #language-Yale #language-Yámana #language-Yana #language-Yerakai #language-Yetfa #language-Hoti #language-Awjilah #language-Tumzabt #language-Sened #language-Tachelhit #language-Standard Moroccan Tamazight #language-Ghomara #language-Senhaja De Srair #language-Tahaggart Tamahaq #language-Tawallammat Tamajaq #language-Tayart Tamajeq #language-Guanche #language-Mbuko #language-Mbara (Chad) #language-Hya #language-Psikye #language-Bana #language-Kamwe #language-Buduma #language-Jina #language-Majera #language-Mser #language-Maslam #language-Mpade #language-Lamang #language-Vemgo-Mabas #language-Marghi Central #language-Marghi South #language-Bura-Pabir #language-Nggwahyi #language-Putai #language-Dghwede #language-Gvoko #language-Cineni #language-Guduf-Gava #language-Matal #language-Dugwor #language-Merey #language-Zulgo-Gemzek #language-Mofu-Gudur #language-North Mofu #language-Mada (Cameroon) #language-Muyang #language-Wuzlam #language-North Giziga #language-South Giziga #language-Bacama #language-Gudu #language-Ngwaba #language-Jimi (Cameroon) #language-Fali #language-Gude #language-Holma #language-Nzanyi #language-Sharwa #language-Tsuvan #language-Mina (Cameroon) #language-Gavar #language-Mazagway #language-Daba #language-Boga #language-Ga'anda #language-Hwana #language-Jara #language-Tera #language-Cuvok #language-Mafa #language-Mefele #language-Jilbe #language-Mukulu #language-Mabire #language-Birgit #language-Mogum #language-Toram #language-Bidiyo #language-Migaama #language-Jonkor Bourmataguil #language-Kajakse #language-Masmaje #language-Mubi #language-Mawa (Chad) #language-Ubi #language-Boor #language-Miltu #language-Saba #language-Sokoro #language-Tamki #language-Kera #language-Kwang #language-Lele (Chad) #language-Nancere #language-Gabri #language-Ndam #language-Tumak #language-Gadang #language-Sarua #language-Musey #language-Masana #language-Zumaya #language-Ngete #language-Fyer #language-Tambas #language-Kulere #language-Ron #language-Gwandara #language-Karekare #language-Galambu #language-Ngamo #language-Beele #language-Deno #language-Kubi #language-Bure #language-Kholok #language-Nyam #language-Dera (Nigeria) #language-Kushi #language-Piya-Kwonci #language-Tangale #language-Kwaami #language-Mwaghavul #language-Ngas #language-Goemai #language-Tal #language-Koenoem #language-Pyapun #language-Jakattoe #language-Nteng #language-Duwai #language-Ngizim #language-Bade #language-Auyokawa #language-Teshenawa #language-Ajawa #language-Ciwogai #language-Diri #language-Mburku #language-Pa'a #language-Siri #language-Miya #language-Warji #language-Boghom #language-Kir-Balar #language-Mangas #language-Guruntum-Mbaaru #language-Jimi (Nigeria) #language-Ju #language-Tala #language-Zangwal #language-Geji #language-Dass #language-Zeem #language-Zari #language-Awngi #language-Bilin #language-Dahalo #language-Hadiyya #language-Libido #language-Kambaata #language-Gedeo #language-Sidamo #language-Saho #language-Konso #language-West Central Oromo #language-Borana-Arsi-Guji Oromo #language-Orma #language-Eastern Oromo #language-Waata #language-Girirra #language-Maay #language-Rendille #language-Baiso #language-Jiiddu #language-Dabarre #language-Tunni #language-Aweer #language-Arbore #language-Daasanach #language-El Molo #language-Yaaku #language-Boon #language-Kw'adza #language-Burunge #language-Alagwa #language-Gorowa #language-Egyptian (Ancient) #language-Ancient North Arabian #language-Arabic #language-Standard Arabic #language-Hadrami Arabic #language-Hijazi Arabic #language-Judeo-Yemeni Arabic #language-Sanaani Arabic #language-Shihhi Arabic #language-Ta'izzi-Adeni Arabic #language-Baharna Arabic #language-Dhofari Arabic #language-Gulf Arabic #language-Najdi Arabic #language-Omani Arabic #language-Tajiki Arabic #language-Uzbeki Arabic #language-Judeo-Iraqi Arabic #language-North Mesopotamian Arabic #language-Eastern Egyptian Bedawi Arabic #language-Egyptian Arabic #language-Saidi Arabic #language-Chadian Arabic #language-Sudanese Arabic #language-Cypriot Arabic #language-Levantine Arabic #language-South Levantine Arabic #language-Algerian Arabic #language-Algerian Saharan Arabic #language-Hassaniyya #language-Judeo-Tripolitanian Arabic #language-Judeo-Moroccan Arabic #language-Libyan Arabic #language-Tunisian Arabic #language-Andalusian Arabic #language-Moroccan Arabic #language-Classical Syriac #language-Assyrian Neo-Aramaic #language-Chaldean Neo-Aramaic #language-Jewish Babylonian Aramaic (ca. 200-1200 CE) #language-Senaya #language-Barzani Jewish Neo-Aramaic #language-Lishana Deni #language-Hulaulá #language-Lishán Didán #language-Lishanid Noshan #language-Classical Mandaic #language-Western Neo-Aramaic #language-Jewish Palestinian Aramaic #language-Old Aramaic (up to 700 BCE) #language-Ancient Hebrew #language-Samaritan #language-Edomite #language-Moabite #language-Ugaritic #language-Phoenician #language-Punic #language-Hadrami #language-Minaean #language-Qatabanian #language-Geez #language-Amharic #language-Argobba #language-Silt'e #language-Wolane #language-Gafat #language-Kistane #language-Mesqan #language-Sebat Bet Gurage #language-Mesmes #language-Hobyót #language-Bathari #language-Harsusi #language-Mehri #language-Wiyot #language-Siksika #language-Nawathinehena #language-Gros Ventre #language-Northern East Cree #language-Southern East Cree #language-Woods Cree #language-Michif #language-Malecite-Passamaquoddy #language-Powhatan #language-Unami #language-Nanticoke #language-Piscataway #language-Loup A #language-Wampanoag #language-Miami #language-Kickapoo #language-Meskwaki #language-Ojibwa #language-Ottawa #language-Central Ojibwa #language-Chippewa #language-Eastern Ojibwa #language-Northwestern Ojibwa #language-Western Ojibwa #language-Severn Ojibwa #language-Alsea #language-Amto #language-Angaataha #language-Yagwoia #language-Baruya #language-Simbari #language-Menya #language-Kawacha #language-Kamasa #language-Susuami #language-Ankave #language-Ipiko #language-Kuni-Boazi #language-Zimakani #language-Bian Marind #language-Marind #language-Warkay-Bipim #language-Yaqay #language-Abom #language-Baramu #language-Tapei #language-Mapudungun #language-Yavitero #language-Baré #language-Taino #language-Garifuna #language-Island Carib #language-Enawené-Nawé #language-Parecís #language-Saraveca #language-Yawalapití #language-Mehináku #language-Waurá #language-Cabiyarí #language-Tariana #language-Curripaco #language-Achagua #language-Mandahuaca #language-Resígaro #language-Xiriâna #language-Wapishana #language-Baure #language-Paunaka #language-Ignaciano #language-Trinitario #language-Chané #language-Ajyíninka Apurucayali #language-Ashéninka Perené #language-Pichis Ashéninka #language-Ucayali-Yurúa Ashéninka #language-Ashéninka Pajonal #language-South Ucayali Ashéninka #language-Machiguenga #language-Apurinã #language-Iñapari #language-Machinere #language-Aruá (Amazonas State) #language-Suruahá #language-Madi #language-Culina #language-Afrihili #language-Blissymbols #language-Brithenig #language-Dutton World Speedwords #language-Interlingua (International Auxiliary Language Association) #language-Interglossa #language-Interlingue #language-Kotava #language-Láadan #language-Lingua Franca Nova #language-Lojban #language-Malawian Sign Language #language-N'Ko #language-Novial #language-Quenya #language-Romanova #language-Sindarin #language-Talossan #language-Toki Pona #language-Volapük #language-Esperanto #language-Ido #language-Eyak #language-Sarsi #language-Kiowa Apache #language-Jicarilla Apache #language-Lipan Apache #language-Mescalero-Chiricahua Apache #language-Southern Carrier #language-Han #language-Degexit'an #language-Northern Tutchone #language-Southern Tutchone #language-Beaver #language-North Slavey #language-South Slavey #language-Kato #language-Mattole #language-Wailaki #language-Upper Umpqua #language-Coquille #language-Ahtena #language-Gola #language-Mansoanka #language-East Limba #language-West-Central Limba #language-Sherbro #language-Bom-Kim #language-Bullom So #language-Northern Kissi #language-Southern Kisi #language-Baga Manduri #language-Baga Sitemu #language-Baga Koga #language-Landoma #language-Timne #language-Ndut #language-Saafi-Saafi #language-Lehar #language-Balanta-Kentohe #language-Balanta-Ganja #language-Bayot #language-Ejamat #language-Kuwaataay #language-Karon #language-Mlomp #language-Gusilay #language-Mankanya #language-Mandjak #language-Papel #language-Biafada #language-Mbulungish #language-Nalu #language-Borgu Fulfulde #language-Maasina Fulfulde #language-Pular #language-Western Niger Fulfulde #language-Central-Eastern Niger Fulfulde #language-Adamawa Fulfulde #language-Bagirmi Fulfulde #language-Kasanga #language-Kobiana #language-Gambian Wolof #language-Ega #language-Gade #language-Oko-Eni-Osayen #language-Ukaan #language-Akpes #language-Epie #language-Degema #language-Ghotuo #language-Yekhee #language-Bini #language-Emai-Iuleha-Ora #language-Enwan (Edo State) #language-Ikpeshi #language-Ivbie North-Okpela-Arhe #language-Igwe #language-Sasaru #language-Iyayu #language-Uhami #language-Ehueun #language-Ukue #language-Okpamheri #language-Oloma #language-Akuku #language-Okpe (Northwestern Edo) #language-Eruwa #language-Isoko #language-Okpe (Southwestern Edo) #language-Urhobo #language-Tikar #language-Samba Daka #language-Dirim #language-Lamja-Dengsa-Tola #language-Dong #language-Ndoola #language-Bung #language-Luo (Cameroon) #language-Njerep #language-Yeni #language-Mbongno #language-Ndunda #language-Vute #language-Wawa #language-Bishuo #language-Busuu #language-Bikya #language-Bukwen #language-Mashi (Nigeria) #language-Noone #language-Mbuk #language-Ncane #language-Bumaji #language-Obanliku #language-Bete #language-Ubang #language-Ukpe-Bayobiri #language-Buru (Nigeria) #language-Ejagham #language-Efutop #language-Abanyom #language-Ekajuk #language-Kendem #language-Seki #language-Kande #language-Simba #language-Bubi #language-Dimbong #language-Bafia #language-Lefa #language-Bankon #language-Barombi #language-Bakoko #language-Basa (Cameroon) #language-Hijuk #language-Bulu (Cameroon) #language-Fang (Equatorial Guinea) #language-Mengisa #language-Bebele #language-Ewondo #language-Kota (Gabon) #language-Mahongwe #language-Ndasa #language-Wumbvu #language-Kélé #language-Ngom #language-Ndambomo #language-Bonkeng #language-Nkongho #language-Mokpwe #language-Bassossi #language-Mbo (Cameroon) #language-Akoose #language-Bakaka #language-Kako #language-Kwakum #language-Bomwali #language-Mpiemo #language-Ukhwejo #language-Koonzime #language-Njyem #language-Makaa #language-Kol (Cameroon) #language-Gyele #language-Pomo #language-Batanga #language-Molengue #language-Ngumbi #language-Duala #language-Malimba #language-Bakole #language-Isu (Fako Division) #language-Mashi (Zambia) #language-Nyengo #language-Simaa #language-Sanga (Democratic Republic of Congo) #language-Kanyok #language-Bangubangu #language-Luba-Lulua #language-Binji #language-Luna #language-Songe #language-Zula #language-Mbangala #language-Phende #language-Mbala #language-Kibala #language-Kimbundu #language-Mpinda #language-Luvale #language-Luchazi #language-Nkangala #language-Nyemba #language-Luimbi #language-Mbwela #language-Kete #language-Umbundu #language-Kuvale #language-Kwandu #language-Ngendelengo #language-Kuanyama #language-Kwambi #language-Ndonga #language-Mbalanhu #language-Ngandyera #language-Nkhumbi #language-Ndombe #language-Mbesa #language-Lombo #language-Poke #language-Moingi #language-So (Democratic Republic of Congo) #language-Mbo (Democratic Republic of Congo) #language-Ndaka #language-Sengele #language-Bolia #language-Ntomba #language-Lalia #language-Ngando (Democratic Republic of Congo) #language-Ombo #language-Bushoong #language-Lele (Democratic Republic of Congo) #language-Dengese #language-Nkutu #language-Kusu #language-Kela (Democratic Republic of Congo) #language-Akwa #language-Mboko #language-Koyo #language-Mbosi #language-Dibole #language-Mbati #language-Ngundi #language-Yaka (Central African Republic) #language-Bomitaba #language-Bongili #language-Ngando (Central African Republic) #language-Lusengo #language-Bamwe #language-Dzando #language-Ndolo #language-Bomboma #language-Bomboli #language-Bozaba #language-Bali (Democratic Republic of Congo) #language-Amba (Uganda) #language-Kango (Tshopo District) #language-Komo (Democratic Republic of Congo) #language-Kango (Bas-Uélé District) #language-Nyanga-li #language-Homa #language-Mayeka #language-Bodo (Central African Republic) #language-Boguru #language-Ligenza #language-Ngombe (Democratic Republic of Congo) #language-Bwela #language-Bolondo #language-Babango #language-Boko (Democratic Republic of Congo) #language-Lobala #language-Boloki #language-Moi (Congo) #language-Bangala #language-Likuba #language-Likwala #language-Mabaale #language-Ndobo #language-Libinza #language-Samba #language-Beembe #language-Kaamba #language-Kunyi #language-Doondo #language-Laari #language-Hungu #language-Kituba (Congo) #language-Kituba (Democratic Republic of Congo) #language-San Salvador Kongo #language-Yombe #language-Bwisi #language-Sangu (Gabon) #language-Sira #language-Lonzo #language-Pelende #language-Ngongo #language-Ibali Teke #language-Sakata #language-Teke-Fuumu #language-Teke-Tyee #language-Teke-Kukuya #language-Teke-Tsaayi #language-Tchitchege #language-Kaningi #language-Ndumu #language-Teke-Laali #language-Yaka (Congo) #language-Duma #language-Wandji #language-Ngungwel #language-Teke-Nzikou #language-Dombe #language-Sala #language-Tonga (Zambia) #language-Subiya #language-Bungu #language-Nyamwanga #language-Nyika (Tanzania) #language-Nyika (Malawi and Zambia) #language-Nyiha (Malawi) #language-Nyiha (Tanzania) #language-Nyakyusa-Ngonde #language-Rangi #language-Mbugwe #language-Dhaiso #language-Kamba (Kenya) #language-Chuka #language-Tharaka #language-Temi #language-Mwimbi-Muthambi #language-Suba #language-Suba-Simbiti #language-Kabwa #language-Zanaki #language-Kara (Tanzania) #language-Kwaya #language-Luyia #language-Idakho-Isukha-Tiriki #language-Bukusu #language-Kabras #language-Masaaba #language-East Nyala #language-Kisa #language-Marama #language-Nyore #language-Tachoni #language-Tsotso #language-Wanga #language-Saamia #language-Nyole #language-Ganda #language-Kenyi #language-Talinga-Bwisi #language-Chiga #language-Nyankole #language-Subi #language-Nyindu #language-Fuliiru #language-Joba #language-Kinyarwanda #language-Rundi #language-Vinza #language-Shubi #language-Konzo #language-Kahe #language-Mochi #language-Vunjo #language-Machame #language-Rwa #language-Sagalla #language-Taita #language-Mwali Comorian #language-Ngazidja Comorian #language-Maore Comorian #language-Ndzwani Comorian #language-Chonyi-Dzihana-Kauma #language-Duruma #language-Giryama #language-Segeju #language-Congo Swahili #language-Cutchi-Swahili #language-Taveta #language-Asu (Tanzania) #language-Kagulu #language-Doe #language-Kami (Tanzania) #language-Kutu #language-Zaramo #language-Bondei #language-Mushungulu #language-Sagala #language-Vidunda #language-Bena (Tanzania) #language-Benamanga #language-Magoma #language-Kisi #language-Sangu (Tanzania) #language-Nyamwezi #language-Konongo #language-Ruwila #language-Bende #language-Bembe #language-Songoora #language-Buyu #language-Lega-Mwenga #language-Kanu #language-Lega-Shabunda #language-Mituku #language-Kwami #language-Nilamba #language-Nyaturu #language-Ndamba #language-Mbunga #language-Ndwewe #language-Ndendeule #language-Nindi #language-Machinga #language-Mwera (Chimwera) #language-Bwile #language-Bemba (Zambia) #language-Seba #language-Ndau #language-Manyika #language-Tewe #language-Tawara #language-Dema #language-Gitonga #language-Swati #language-Ronga #language-Kokola #language-Maindo #language-Manyawa #language-Nathembo #language-Lolo #language-Marenje #language-Takwane #language-Makhuwa-Shirima #language-Makhuwa-Meetto #language-Makhuwa-Marrevone #language-Makhuwa-Moniga #language-Makhuwa-Saka #language-Birwa #language-Pedi #language-Tswapong #language-Southern Sotho #language-Koma #language-Mwera (Nyasa) #language-Nyanja #language-Barwe #language-Malawi Sena #language-Sena #language-Phimbi #language-Tonga (Nyasa) #language-Bube #language-Mbonga #language-Kulung (Nigeria) #language-Mama #language-Dulbu #language-Bada (Nigeria) #language-Duguri #language-Bankal #language-Gwa #language-Nubaca #language-Bati (Cameroon) #language-Mbule #language-Yangben #language-Mmaala #language-Elip #language-Nugunu (Cameroon) #language-Leti (Cameroon) #language-Tuki #language-Tuotomb #language-Yambeta #language-Nomaande #language-Tunen #language-Esimbi #language-Evant #language-Iyive #language-Otank #language-Caka #language-Eman #language-Ambo #language-Bitare #language-Ambele #language-Befang #language-Ndemli #language-Mbe' #language-Yamba #language-Kwaja #language-Fe'fe' #language-Ghomálá' #language-Kwa' #language-Nda'nda' #language-Ngombale #language-Ngwe #language-Bafanji #language-Bambalang #language-Bamun #language-Bangolan #language-Mungaka #language-Bamenyam #language-Awing #language-Beba #language-Pinyin #language-Bafut #language-Bambili-Bambui #language-Mendankwe-Nkwen #language-Ngemba #language-Kpati #language-Mundani #language-Njen #language-Ngie #language-Ngoshie #language-Meta' #language-Ngamambo #language-Lamnso' #language-Kung #language-Kom (Cameroon) #language-Mbessa #language-Bum #language-Kuk #language-Laimbue #language-Isu (Menchum Division) #language-Zhoa #language-Weh #language-Bamunka #language-Kenswei Nsei #language-Balo #language-Busam #language-Osatu #language-Menka #language-Viti #language-Fang (Cameroon) #language-Koshin #language-Ajumbu #language-Abar #language-Mundabli #language-Fam #language-Sambe #language-Lijili #language-Cen #language-Ganang #language-Shall-Zwall #language-Doka #language-Iku-Gora-Ankwa #language-Kuturmi #language-Bo-Rukul #language-Fyam #language-Sur #language-Tiyaa #language-Bijim #language-Kadung #language-Ikulu #language-Aninka #language-Ayu #language-Numana #language-Kaningdon-Nindem #language-Che #language-Mada (Nigeria) #language-Kagoma #language-Kamantan #language-Shamang #language-Ashe #language-Koro Nulu #language-Kapya #language-Akum #language-Beezen #language-Lufu #language-Arigidi #language-Àhàn #language-Ayere #language-Igala #language-Isekiri #language-Mokole #language-Ede Cabe #language-Ede Ije #language-Lucumi #language-Yoruba #language-Kura Ede Nago #language-Ede Idaca #language-Ede Ica #language-Ifè #language-Abua #language-Odual #language-Kugbo #language-Ogbogolo #language-Obulom #language-O'chi'chi' #language-Ebughu #language-Ibino #language-Iko #language-Ilue #language-Okobo #language-Oro #language-Usaghade #language-Efai #language-Anaang #language-Ukwa #language-Ekit #language-Etebi #language-Ibuoro #language-Ito #language-Itu Mbon Uzo #language-Nkari #language-Enwan (Akwa Ibom State) #language-Uda #language-Eki #language-Idere #language-Gokana #language-Tee #language-Eleme #language-Ukpet-Ehom #language-Bakpinka #language-Doko-Uyanga #language-Olulumo-Ikom #language-Lokaa #language-Lubila #language-Cross River Mbembe #language-Legbo #language-Lenyima #language-Leyigha #language-Oring #language-Kukele #language-Uzekwe #language-Ubaghara #language-Agwagwune #language-Kohumono #language-Umon #language-Durop #language-Ebira #language-Gbagyi #language-Gbari #language-Asu (Nigeria) #language-Nupe-Nupe-Tako #language-Kakanda #language-Kupa #language-Kami (Nigeria) #language-Gupa-Abawa #language-Koro Zuba #language-Igede #language-Etulo #language-Akpa #language-Ekpeye #language-Ika #language-Ikwere #language-Ogbah #language-Ezaa #language-Ikwo #language-Kutep #language-Tigon Mbembe #language-Wãpha #language-Jibu #language-Hõne #language-Wannu #language-Como Karim #language-Jiru #language-Shoo-Minda-Nye #language-Etkywan #language-Kpan #language-Basa (Nigeria) #language-Basa-Gurmana #language-Bassa-Kontagora #language-Amo #language-Bina (Nigeria) #language-Kono (Nigeria) #language-Lere #language-Gyem #language-Kudu-Camo #language-Iguta #language-Jere #language-Panawa #language-Izora #language-Sanga (Nigeria) #language-Sheni #language-Damakawa #language-Cicipu #language-Tsuvadi #language-Tsikimba #language-Rogo #language-Eastern Acipa #language-Shama-Sambuga #language-Bauchi #language-Fungwa #language-Gurmana #language-Baissa Fali #language-Tita #language-Adangme #language-Aja (Benin) #language-Eastern Xwla Gbe #language-Tofin Gbe #language-Ci Gbe #language-Defi Gbe #language-Maxi Gbe #language-Weme Gbe #language-Wudu #language-Ayizo Gbe #language-Gbesi Gbe #language-Kotafon Gbe #language-Saxwe Gbe #language-Western Xwla Gbe #language-Xwela Gbe #language-Adangbe #language-Kpessi #language-Waci Gbe #language-Nyangbo #language-Tafi #language-Akebu #language-Animere #language-Igo #language-Ikposo #language-Tuwuli #language-Anii #language-Sekpele #language-Selee #language-Attié #language-Abé #language-Abidji #language-Adioukrou #language-Alladian #language-Avikam #language-Mbato #language-Krobu #language-Abron #language-Akan #language-Wasa #language-Twi #language-Anufo #language-Baoulé #language-Anyin Morofo #language-Ahanta #language-Nzima #language-Dompo #language-Gonja #language-Nkami #language-Nkonya #language-Nawuri #language-Foodo #language-Gikyode #language-Kplang #language-Krache #language-Chumburung #language-Tchumbuli #language-Nchumbulu #language-Awutu #language-Larteh #language-Cherepon #language-Gua #language-Abure #language-Beti (Côte d'Ivoire) #language-Day #language-Tunia #language-Bua #language-Bon Gula #language-Zan Gula #language-Gula Iro #language-Koke #language-Besme #language-Goundo #language-Kim #language-Lala-Roba #language-Bena (Nigeria) #language-Voro #language-Mághdì #language-Mak (Nigeria) #language-Kyak #language-Leelau #language-Moo #language-Dza #language-Mbum #language-Kare (Central African Republic) #language-Pana (Central African Republic) #language-Ndai #language-Mambai #language-Tupuri #language-Mono (Cameroon) #language-To #language-Pangseng #language-Rang #language-Bali (Nigeria) #language-Kpasam #language-Yotti #language-Teme #language-Waka #language-Yendang #language-Doyayo #language-Gimme #language-Gimnime #language-Mom Jango #language-Longto #language-Dii #language-Dugun #language-Duupa #language-Kolbila #language-Samba Leko #language-Wom (Nigeria) #language-Mbandja #language-Ngbundu #language-West Central Banda #language-Banda-Yangere #language-Banda-Mbrès #language-Banda-Banda #language-Banda-Bambari #language-Banda-Ndélé #language-Togbo-Vara Banda #language-Gobu #language-Kpagua #language-Mid-Southern Banda #language-Mono (Democratic Republic of Congo) #language-Ngundu #language-Langbashe #language-South Central Banda #language-Ma (Democratic Republic of Congo) #language-Dongo #language-Mba #language-Ndunga #language-Gbayi #language-Dendi (Central African Republic) #language-Mbangi #language-Northern Ngbandi #language-Southern Ngbandi #language-Yakoma #language-Riverain Sango #language-Mündü #language-Bangba #language-Mayogo #language-Gundi #language-Limassa #language-Baka (Cameroon) #language-Ganzi #language-Gilima #language-Ngbaka Ma'bo #language-Monzombo #language-Kpala #language-Yango #language-Feroge #language-Mangayat #language-Indri #language-Togoyo #language-Ndogo #language-Sere #language-Tagbu #language-Barambu #language-Pambia #language-Geme #language-Nzakara #language-Oblo #language-Gbanu #language-Manza #language-Ali #language-Ngbaka Manza #language-Gbaya-Mbodomo #language-Northwest Gbaya #language-Gbaya-Bozoum #language-Gbaya-Bossangoa #language-Suma #language-Southwest Gbaya #language-Viemo #language-Koromfé #language-Láá Láá Bwamu #language-Buli (Ghana) #language-Gourmanchéma #language-Bimoba #language-Moba #language-Akaselem #language-Yom #language-Kantosi #language-Mossi #language-Safaliba #language-Dagaari Dioula #language-Wali (Ghana) #language-Northern Dagara #language-Malba Birifor #language-Hanga #language-Kamara #language-Biali #language-Nateni #language-Ditammari #language-Mbelime #language-Baatonum #language-Dogosé #language-Khisa #language-Lama (Togo) #language-Lukpa #language-Bago-Kusuntu #language-Chala #language-Phuie #language-Winyé #language-Vagla #language-Chakali #language-Tampulma #language-Tumulung Sisaala #language-Western Sisaala #language-Pana (Burkina Faso) #language-Kasem #language-Northern Nuni #language-Southern Nuni #language-Dyan #language-Dijim-Bwilim #language-Awak #language-Tula #language-Bondoukou Kulango #language-Bouna Kulango #language-Loma (Côte d'Ivoire) #language-Téén #language-Northern Toussian #language-Southern Toussian #language-Eastern Karaboro #language-Western Karaboro #language-Mamara Senoufo #language-Nanerigé Sénoufo #language-Sìcìté Sénoufo #language-Supyire Senoufo #language-Syenara Senoufo #language-Shempire Senoufo #language-Nyarafolo Senoufo #language-Palaka Senoufo #language-Djimini Senoufo #language-Tagwana Senoufo #language-Miyobe #language-Aproumu Aizi #language-North Fali #language-South Fali #language-Jah Hut #language-Chewong #language-Kensiu #language-Kintaq #language-Jehai #language-Minriq #language-Batek #language-Temiar #language-Besisi #language-Semaq Beri #language-Semelai #language-Temoq #language-Cua #language-Katua #language-Takua #language-Monom #language-Todrah #language-Hre #language-Sedang #language-Kayong #language-Halang #language-Jeh #language-Halang Doan #language-Romam #language-Alak #language-Brao #language-Oy #language-Kavet #language-Krung #language-Laven #language-Sou #language-Maa #language-Chrau #language-Eastern Mnong #language-Central Mnong #language-Kraol #language-Southern Mnong #language-Budeh Stieng #language-Bulo Stieng #language-Mel-Khaonh #language-Tampuan #language-Talieng #language-Trieng #language-Pacoh #language-Eastern Katu #language-Western Katu #language-Lower Ta'oih #language-Upper Ta'oih #language-Eastern Bru #language-Northern Katang #language-Southern Katang #language-Sô #language-Western Bru #language-Nyeu #language-War-Jaintia #language-Hu #language-Man Met #language-Mok #language-Bit #language-Samtao #language-Eastern Lawa #language-Western Lawa #language-Rumai Palaung #language-Ruching Palaung #language-Shwe Palaung #language-Northern Khmer #language-Old Khmer #language-Mlabri #language-Khuen #language-O'du #language-Phong-Kniang #language-Mang #language-Bolyu #language-Bugan #language-Nyahkur #language-Old Mon #language-Gata' #language-Bodo Gadaba #language-Bondo #language-Birhor #language-Koda #language-Majhwar #language-Turi #language-Asuri #language-Bijori #language-Kodaku #language-Kol (Bangladesh) #language-Mahali #language-Juray #language-Car Nicobarese #language-Central Nicobarese #language-Arem #language-Chut #language-Hung #language-Tho #language-Nguôn #language-Puyuma #language-Atayal #language-Sakizaya #language-Basay #language-Ketangalan #language-Siraya #language-Ati #language-Enggano #language-Nasal #language-Basap #language-Dusun Malang #language-Dusun Deyah #language-Ampanang #language-Tunjung #language-Lawangan #language-Tawoyan #language-Kohin #language-Ot Danum #language-Siang #language-Inabaknon #language-Yakan #language-Pangutaran Sama #language-Indonesian Bajau #language-Mapun #language-West Coast Bajau #language-Balangingi #language-Central Sama #language-Southern Sama #language-Dusun Witu #language-Ma'anyan #language-Paku #language-Plateau Malagasy #language-Southern Betsimisaraka Malagasy #language-Antankarana Malagasy #language-Northern Betsimisaraka Malagasy #language-Tsimihety Malagasy #language-Tesaka Malagasy #language-Bara Malagasy #language-Tanosy Malagasy #language-Masikoro Malagasy #language-Bakumpai #language-Ngaju #language-Ibatan #language-Giangan #language-Tiruray #language-Tboli #language-Koronadal Blaan #language-Sarangani Blaan #language-Banggai #language-Bobongko #language-Batui #language-Moronene #language-Bahonsuai #language-Bungku #language-Koroni #language-Kulisusu #language-Mori Bawah #language-Taloki #language-Wawonii #language-Mori Atas #language-Padoe #language-Tomadino #language-Kodeoha #language-Rahambuu #language-Tolaki #language-Waru #language-Kumbewaha #language-Lasalimu #language-Busoa #language-Kaimbulawa #language-Kioko #language-Liabuku #language-Pancana #language-Bonerate #language-Tukang Besi North #language-Tukang Besi South #language-Dondo #language-Lauje #language-Tomini #language-Balaesang #language-Dampelas #language-Pendau #language-Taje #language-Tajio #language-Topoiyo #language-Sedoa #language-Baras #language-Da'a Kaili #language-Ledo Kaili #language-Unde Kaili #language-Moma #language-Tado #language-Pamona #language-Tombelala #language-Sarudu #language-Wotu #language-Kamaru #language-Wolio #language-Pampanga #language-Ambala Ayta #language-Botolan Sambal #language-Mag-Indi Ayta #language-East Tarangan #language-West Tarangan #language-Batuley #language-Mariri #language-Lola #language-Lorang #language-Manombai #language-Dobel #language-Koba #language-Barakai #language-Karey #language-Ujir #language-Kola #language-Kompane #language-Kedang #language-Sika #language-Lamaholot #language-Lewotobi #language-Lamalera #language-Ile Ape #language-West Lembata #language-Lamatuka #language-Lewo Eleng #language-Kepo' #language-Komodo #language-Manggarai #language-Riung #language-Rembong #language-Rajong #language-Ende #language-Li'o #language-Nage #language-Ngad'a #language-Rongga #language-Eastern Ngad'a #language-Kambera #language-Mamboru #language-Anakalangu #language-Wanukaka #language-Lamboya #language-Laura #language-Banda (Indonesia) #language-Watubela #language-Bati (Indonesia) #language-Geser-Gorom #language-Bobot #language-Benggoi #language-Liana-Seti #language-Salas #language-Huaulu #language-North Nuaulu #language-South Nuaulu #language-Sepa (Indonesia) #language-Paulohi #language-Kaibobo #language-Laha (Indonesia) #language-Seit-Kaitetu #language-Hitu #language-Tulehu #language-Kamarian #language-Haruku #language-Amahai #language-Nusa Laut #language-Latu #language-Saparua #language-Asilulu #language-Boano (Maluku) #language-Larike-Wakasihu #language-Wemale #language-Hulung #language-Lisabata-Nuniali #language-Loun #language-Alune #language-Naka'ela #language-Kur #language-Teor #language-Buru (Indonesia) #language-Mangole #language-Kadai #language-Taliabu #language-Kei #language-Yamdena #language-Onin #language-Sekar #language-Uruangnirin #language-Helong #language-Idaté #language-Lakalei #language-Habu #language-Tetun Dili #language-Kairui-Midiki #language-Nauete #language-Waima'a #language-Amarasi #language-Baikeno #language-Maku'a #language-Dai #language-Dawera-Daweloor #language-North Babar #language-Central Masela #language-East Masela #language-Serili #language-Southeast Babar #language-West Masela #language-Emplawas #language-Imroing #language-Tela-Masbuar #language-Kisar #language-Roma #language-Leti (Indonesia) #language-Selaru #language-Seluwasan #language-Te'un #language-Nila #language-Serua #language-Ili'uun #language-Tugun #language-Aputai #language-Perai #language-Mambae #language-Welaun #language-Kemak #language-Tukudede #language-Pak-Tong #language-Andra-Hus #language-Leipon #language-Ponam #language-Lele (Papua New Guinea) #language-Nali #language-Ere #language-Kele (Papua New Guinea) #language-Elu #language-Loniu #language-Mokerang #language-Bipi #language-Hermit #language-Nyindrou #language-Sori-Harengan #language-Mondropolon #language-Tulu-Bohuai #language-Likum #language-Lenkau #language-Nauna #language-Penchal #language-Lou #language-Pam #language-Seimat #language-Wuvulu-Aua #language-Kaniet #language-Gone Dau #language-Lauan #language-Lomaiviti #language-Anuta #language-East Futuna #language-Rennell-Bellona #language-Tikopia #language-Niuafo'ou #language-Niuatoputapu #language-Tuvalu #language-Pukapuka #language-Tokelau #language-Sikaiana #language-Nukumanu #language-Nukuria #language-Takuu #language-Rapanui #language-North Marquesan #language-South Marquesan #language-Maori #language-Rakahanga-Manihiki #language-Austral #language-Futuna-Aniwa #language-Tonga (Tonga Islands) #language-Namosi-Naitasiri-Serua #language-Western Fijian #language-Pingelapese #language-Mapia #language-Woleaian #language-Mortlockese #language-Puluwatese #language-Satawalese #language-Namonuito #language-Pááfang #language-Tanapag #language-Sonsorol #language-Kosraean #language-Nauru #language-Paama #language-North Ambrym #language-Lelepa #language-Eton (Vanuatu) #language-South Efate #language-Baki #language-Bierebo #language-Bieria #language-Maii #language-Lamenu #language-Lewo #language-Uripiv-Wala-Rano-Atchin #language-Aulua #language-Burmbar #language-Maskelynes #language-Axamb #language-Port Sandwich #language-Rerep #language-Unua #language-Malua Bay #language-Mpotovoro #language-Vao #language-Larevat #language-Maragus #language-Dixon Reef #language-Nasarian #language-Letemboi #language-Repanbitip #language-Apma #language-Sa #language-Seke (Vanuatu) #language-Sowa #language-Hano #language-East Ambae #language-West Ambae #language-Mafea #language-Tutuba #language-Polonombauk #language-Tambotalo #language-Ngen #language-Aore #language-Araki #language-Sakao #language-Tolomako #language-Nokuku #language-Piamatsina #language-Tasmate #language-Valpei #language-Vunapu #language-Amblong #language-Morouas #language-Narango #language-Merei #language-Navut #language-Tiale #language-Akei #language-Baetora #language-Central Maewo #language-Lehalurup #language-Merlav #language-Mota #language-Nume #language-Vurës #language-Hiw #language-Lo-Toga #language-Lakon #language-Koro (Vanuatu) #language-Lemerig #language-Vera'a #language-Bughotu #language-Gela #language-Ghari #language-Lengo #language-Malango #language-Birao #language-Talise #language-Longgu #language-Sa'a #language-Kwaio #language-Wala #language-Baelelea #language-Fataleka #language-To'abaita #language-'Are'are #language-Dori'o #language-Oroha #language-Arosi #language-Fagani #language-Dehu #language-Nengone #language-Nêlêmwa-Nixumwak #language-Jawe #language-Pwaamei #language-Pije #language-Fwâi #language-Nemi #language-Cemuhî #language-Paicî #language-Hmwaveke #language-Vamale #language-Waamwang #language-Haveke #language-Bwatoo #language-Dumbea #language-Neku #language-Xârâcùù #language-Ajië #language-Arhâ #language-Arhö #language-Tiri #language-Aneityum #language-Ifo #language-Sie #language-Ura (Vanuatu) #language-North Tanna #language-Whitesands #language-Southwest Tanna #language-Mussau-Emira #language-Tenis #language-Nalögo #language-Natügu #language-Malo #language-Neo #language-Teanu #language-Amba (Solomon Islands) #language-Asumboa #language-Tomoip #language-Barok #language-Lavatbura-Lamusong #language-Madak #language-Konomala #language-Sursurunga #language-Kandas #language-Ramoaaina #language-Bilur #language-Label #language-Ririo #language-Babatana #language-Vaghua #language-Varisi #language-Torau #language-Uruava #language-Solos #language-Nehan #language-Papapana #language-Petats #language-Hakö #language-Halia #language-Hahon #language-Teop #language-Kazukuru #language-Ughele #language-Marovo #language-Vangunu #language-Roviana #language-Hoava #language-Kusaghe #language-Duke #language-Simbo #language-Lungga #language-Lawunuia #language-Blablanga #language-Zazao #language-Cheke Holo #language-Gao #language-Laghu #language-Zabana #language-Guramalum #language-Kuanua #language-Fanamaket #language-Warwar Feni #language-Niwer Mil #language-Mandara #language-Notsi #language-Kara (Papua New Guinea) #language-Nalik #language-Tiang #language-Tigak #language-Tungag #language-Bola #language-Bulu (Papua New Guinea) #language-Numbami #language-Labu #language-Aribwaung #language-Musom #language-Nafi #language-Adzera #language-Mari (Madang Province) #language-Sarasira #language-Sukurum #language-Wampur #language-Middle Watut #language-North Watut #language-South Watut #language-Bugawac #language-Kela (Papua New Guinea) #language-Iwal #language-Kapin #language-Piu #language-Vehes #language-Gorakor #language-Dambi #language-Kumalu #language-Patep #language-Zenag #language-Yamap #language-Bariai #language-Kove #language-Gitua #language-Maleu-Kilenge #language-Mbula #language-Sio #language-Tami #language-Mato #language-Ronji #language-Awad Bing #language-Mindiri #language-Wab #language-Gedaged #language-Marik #language-Matukar #language-Takia #language-Arop-Lokep #language-Karnai #language-Lote #language-Mamusi #language-Mengen #language-Amara #language-Akolet #language-Avau #language-Aiklep #language-Gimi (West New Britain) #language-Solong #language-Bebeli #language-Mangseng #language-Aighon #language-Karore #language-Kaulong #language-Miu #language-Sengseng #language-Lamogai #language-Mouk-Aria #language-Kayupulau #language-Ormu #language-Bonggo #language-Kaptiau #language-Masimasi #language-Tarpia #language-Liki #language-Sobei #language-Kairiru #language-Kaiep #language-Terebu #language-Medebur #language-Biem #language-Manam #language-Sepa (Papua New Guinea) #language-Kis #language-Wogeo #language-Ulau-Suain #language-Kap #language-Tumleo #language-Sera #language-Arop-Sissano #language-Malol #language-Sissano #language-Anuki #language-Gumawana #language-Maisin #language-Arifama-Miniafia #language-Ubir #language-Are #language-Doga #language-Gapapaiwa #language-Ghayavi #language-Minaveha #language-Tawala #language-Gweda #language-Haigwai #language-Maiwala #language-Taupota #language-Wa'ema #language-Yaleba #language-Wedau #language-Yakaikeke #language-Koluwawa #language-Bwaidoka #language-Iduna #language-Iamalele #language-Maiadomu #language-Dobu #language-Duau #language-Sewa Bay #language-Boselewa #language-Galeya #language-Bunama #language-Mwatebu #language-Dawawa #language-Kakabai #language-'Auhelawa #language-Buhutu #language-Bwanabwana #language-Oya'oya #language-Unubahe #language-Wagawaga #language-Saliba #language-Suau #language-Ouma #language-Bina (Papua New Guinea) #language-Magori #language-Yoba #language-Sinaugoro #language-Hula #language-Keapara #language-Abadi #language-Motu #language-Kuni #language-Lala #language-Mekeo #language-Toura (Papua New Guinea) #language-Waima #language-Budibud #language-Kilivila #language-Muyuw #language-Nimoa #language-Sudest #language-Nguluwan #language-Mor (Mor Islands) #language-Tandia #language-Waropen #language-Arguni #language-Bedoanas #language-Erokwanas #language-Dusner #language-Meoswar #language-Roon #language-Yeretuar #language-Yaur #language-Ambai #language-Ansus #language-Marau #language-Woi #language-Wamesa #language-Munggui #language-Papuma #language-Pom #language-Busami #language-Serui-Laut #language-Kurudu #language-Wabo #language-Yoke #language-As #language-Biga #language-Waigeo #language-Matbat #language-Kawe #language-Legenyem #language-Wauyai #language-Salawati #language-Buli (Indonesia) #language-Maba (Indonesia) #language-Patani #language-East Makian #language-Gane #language-Umiray Dumaget Agta #language-Bikol #language-Mamanwa #language-Alabat Island Agta #language-Isarog Agta #language-Mt. Iriga Agta #language-Mt. Iraya Agta #language-Bantoanon #language-Porohanon #language-Masbatenyo #language-Baybayanon #language-Kinabalian #language-Waray (Philippines) #language-Northern Binukidnon #language-Southern Binukidnon #language-Butuanon #language-Surigaonon #language-Tandaganon #language-Ata #language-Inonhan #language-Sulod #language-Cuyonon #language-Caluyanun #language-Davawenyo #language-Kamayo #language-Kagan Kalagan #language-Kalagan #language-Kasiguranin #language-Maranao #language-Bintauna #language-Kaidipang #language-Lolak #language-Suwawa #language-Mongondow #language-Ponosakan #language-Ata Manobo #language-Matigsalug Manobo #language-Agusan Manobo #language-Dibabawon Manobo #language-Rajah Kabunsuwan Manobo #language-Obo Manobo #language-Ilianen Manobo #language-Western Bukidnon Manobo #language-Tagabawa #language-Cotabato Manobo #language-Sarangani Manobo #language-Kagayanen #language-Higaonon #language-Tagbanwa #language-Batak #language-Central Tagbanwa #language-Molbog #language-Central Palawano #language-Brooke's Point Palawano #language-Southwest Palawano #language-Eastern Tawbuid #language-Western Tawbuid #language-Central Subanen #language-Eastern Subanen #language-Northern Subanen #language-Kolibugan Subanon #language-Western Subanon #language-Kawi #language-Caribbean Javanese #language-New Caledonian Javanese #language-Osing #language-Tengger #language-Agutaynen #language-Lampung Nyo #language-Lampung Api #language-Benyadu' #language-Rara Bakati' #language-Biatah Bidayuh #language-Tringgus-Sembaan Bidayuh #language-Bukar-Sadung Bidayuh #language-Ribun #language-Sanggau #language-Semandang #language-Sasak #language-Haroi #language-Eastern Cham #language-Western Cham #language-Cacgia Roglai #language-Chru #language-Southern Roglai #language-Northern Roglai #language-Tsat #language-Bih #language-Rade #language-Duano #language-Haji #language-Malayic Dayak #language-Old Malay #language-Keninjal #language-Seberuang #language-Beginci #language-Gerai #language-Cocos Islands Malay #language-Peranakan Indonesian #language-Kubu #language-Musi #language-Kota Bangun Kutai Malay #language-Banjar #language-Bukit Malay #language-Berau Malay #language-Sabah Malay #language-Bacanese Malay #language-Brunei #language-Jambi Malay #language-Bangka #language-Lubu #language-Negeri Sembilan Malay #language-Pekal #language-Balinese Malay #language-Jakun #language-Central Malay #language-Orang Kanaq #language-Orang Seletar #language-Tenggarong Kutai Malay #language-Kedah Malay #language-Pattani Malay #language-Standard Malay #language-Baba Malay #language-Makassar Malay #language-Malaccan Creole Malay #language-Kupang Malay #language-Larantuka Malay #language-Papuan Malay #language-Ambonese Malay #language-Banda Malay #language-Gorap #language-Manado Malay #language-North Moluccan Malay #language-Badui #language-Tonsawang #language-Tontemboan #language-Tondano #language-Tonsea #language-Moken #language-Moklen #language-Sikule #language-Batak Alas-Kluet #language-Batak Dairi #language-Batak Toba #language-Batak Angkola #language-Batak Mandailing #language-Alangan #language-Iraya #language-Tadyawan #language-Arta #language-Iloko #language-Isnag #language-Adasen #language-Ibanag #language-Faire Atta #language-Pamplona Atta #language-Pudtol Atta #language-Central Cagayan Agta #language-Itawit #language-Yogad #language-Ga'dang #language-Gaddang #language-Northern Alta #language-Southern Alta #language-Binongan Itneg #language-Inlaod Itneg #language-Lubuagan Kalinga #language-Butbut Kalinga #language-Tanudan Kalinga #language-Masadiit Itneg #language-Moyadan Itneg #language-Limos Kalinga #language-Banao Itneg #language-Mabaka Valley Kalinga #language-Balangao #language-Isinai #language-Bontok #language-Southern Bontok #language-Kankanaey #language-Maeng Itneg #language-Northern Kankanay #language-Amganad Ifugao #language-Tuwali Ifugao #language-Batad Ifugao #language-Mayoyao Ifugao #language-Ilongot #language-I-Wak #language-Kalanguya #language-Karao #language-Dupaninan Agta #language-Paranan #language-Dicamay Agta #language-Murik (Malaysia) #language-Bahau #language-Baram Kayan #language-Kayan River Kayan #language-Mendalam Kayan #language-Busang Kayan #language-Kayan Mahakam #language-Rejang Kayan #language-Modang #language-Segai #language-West Berawan #language-Central Berawan #language-East Berawan #language-Kiput #language-Tutong #language-Lelak #language-Kelabit #language-Lengilu #language-Lundayeh #language-Sa'ban #language-Tring #language-Uma' Lung #language-Uma' Lasan #language-Eastern Penan #language-Sebop #language-Western Penan #language-Bolongan #language-Bonggi #language-Ida'an #language-Lotud #language-Sabah Bisaya #language-Brunei Bisaya #language-Kimaragang #language-Klias River Kadazan #language-Kota Marudu Talantang #language-Kuijau #language-Tobilung #language-Kadazan Dusun #language-Minokok #language-Sugut Dusun #language-Rungus #language-Dumpas #language-Labuk-Kinabatangan Kadazan #language-Abai Sungai #language-Serudung Murut #language-Tombonuo #language-Lanas Lobu #language-Tampias Lobu #language-Upper Kinabatangan #language-Papar #language-Selungai Murut #language-Sembakung Murut #language-Gana #language-Paluan #language-Timugon Murut #language-Tagal Murut #language-Burusu #language-Northern Tidung #language-Southern Tidung #language-Sekapan #language-Kajaman #language-Lahanan #language-Central Melanau #language-Daro-Matu Melanau #language-Kanowit-Tanjong Melanau #language-Sibu Melanau #language-Aoheng #language-Kereho #language-Punan Aput #language-Punan Merah #language-Punan Batu 1 #language-Sihan #language-Bukat #language-Bukitan #language-Ukit #language-Punan Tubu #language-Punan Bah-Biau #language-Talaud #language-Sangir #language-Sangil #language-Bantik #language-Ratahan #language-Campalagian #language-Embaloh #language-Taman (Indonesia) #language-Coastal Konjo #language-Bentong #language-Makasar #language-Mamuju #language-Mandar #language-Maiwa (Indonesia) #language-Malimpung #language-Dakka #language-Pannei #language-Ulumanda' #language-Kalumpang #language-Mamasa #language-Tae' #language-Talondo' #language-Toraja-Sa'dan #language-Rampi #language-Bada (Indonesia) #language-Besoa #language-Napu #language-Seko Tengah #language-Seko Padang #language-Boano (Sulawesi) #language-Totoli #language-Kulon #language-Pazeh #language-Babuza #language-Papora #language-Central Aymara #language-Southern Aymara #language-Baibai #language-Kairak #language-Simbali #language-Ura (Papua New Guinea) #language-Makolkol #language-Guambiano #language-Totoro #language-Awa-Cuaiquer #language-Awbono #language-Bayono #language-Aduge #language-Ahirani #language-Anasi #language-Áncá #language-Arakwal #language-xss #language-Baga Kaloum #language-Baga Sobané #language-Bainouk-Samik #language-Bhalay #language-Bubia #language-Bumang #language-Buraka #language-Buso #language-Chetco #language-Chuanqiandian Cluster Miao #language-Con #language-Desiya #language-Foma #language-Fum #language-Gengle #language-Gowli #language-Gowlan #language-Idesa #language-Ihievbe #language-Inpui Naga #language-Ir #language-Jiarong #language-Judeo-Berber #language-Kang #language-Kayort #language-Kemiehua #language-Khao #language-Khua #language-Kisankasa #language-Kofa #language-Koko Babangk #language-Kon Keu #language-Kosena #language-Kpatili #language-Kuanhua #language-Kukna #language-Kuku-Mangk #language-Kumbaran #language-Laba #language-Lahta Karen #language-Lambichhong #language-Lang'e #language-Laopang #language-Laos Sign Language #language-Lenca #language-Loarki #language-Lopi #language-Lumba-Yakkha #language-Malay (individual language) #language-Mawayana #language-Mirgan #language-Munda #language-Nde-Gbite #language-Ndonde Hamba #language-Ngombe (Central African Republic) #language-nom #language-Norra #language-Northwestern Fars #language-tmk #language-Katukína #language-Nupbikha #language-Odut #language-Old Turkish #language-Olkol #language-Ontenu #language-Parsi #language-Parsi-Dari #language-Phangduwali #language-Pokangá #language-Puimei Naga #language-Punan Merap #language-Putoh #language-Quetzaltepec Mixe #language-Rufiji #language-Salumá #language-szd #language-Shuadit #language-Singapore Sign Language #language-Southwestern Nisu #language-Southern Lolopo #language-Southeastern Puebla Nahuatl #language-Tareng #language-Tawang Monpa #language-Tetete #language-Thu Lao #language-Tingui-Boto #language-Uradhi #language-Wahau Kayan #language-Xinca #language-Yamongeri #language-Yarsun #language-Yauma #language-Akyaung Ari Naga #language-Dawik Kui #language-Ekai Chin #language-Laitu Chin #language-Lao Naga #language-Ponyo-Gongwang Naga #language-Rungtu Chin #language-Songlai Chin #language-Ningera #language-Ainbai #language-Kilmeri #language-Pagi #language-Awyi #language-Amanab #language-Auwe #language-Daonda #language-Imonda #language-Senggi #language-Waris #language-Sowanda #language-Umeda #language-Umotína #language-Otuke #language-Kasua #language-Onobasulu #language-Sonia #language-Beami #language-Edolo #language-Gooniyandi #language-Kitsai #language-Pawnee #language-Apalaí #language-Galibi Carib #language-Akurio #language-Trió #language-Wayana #language-Kuikúro-Kalapálo #language-Matipuhy #language-Kaxuiâna #language-Hixkaryána #language-Waiwai #language-Bakairí #language-Tamanaku #language-Chaima #language-Mapoyo #language-Pémono #language-Yabarana #language-Macushi #language-Patamona #language-Akawaio #language-Waimiri-Atroari #language-Japrería #language-Ndrulo #language-Lombi #language-Asoa #language-Mamvu #language-Mangbutu #language-Bendi #language-Efe #language-Mvuba #language-Birri #language-Aringa #language-Avokaya #language-Logo #language-Lugbara #language-Keliko #language-Omi #language-Olu'bo #language-Southern Ma'di #language-Bongo #language-Baka (South Sudan) #language-Beli (South Sudan) #language-Mittu #language-Mo'da #language-Morokodo #language-Jur Modo #language-Nyamusa-Molo #language-Gula (Central African Republic) #language-Kara (Central African Republic) #language-Vale #language-Kenga #language-Jaya #language-Gula (Chad) #language-Morom #language-Berakou #language-Naba #language-Horo #language-Ngambay #language-Laka (Chad) #language-Gor #language-Mango #language-Dagba #language-Sara Kaba #language-Sara Kaba Náà #language-Sara Kaba Deme #language-Kulfa #language-Torá #language-Itene #language-Oro Win #language-Pech #language-Buglere #language-Ngäbere #language-Border Kuna #language-San Blas Kuna #language-Boruca #language-Cabécar #language-Cogui #language-Malayo #language-Angosturas Tunebo #language-Barro Negro Tunebo #language-Central Tunebo #language-Western Tunebo #language-Maléku Jaíka #language-Wasco-Wishram #language-Woun Meu #language-Emberá-Catío #language-Emberá-Baudó #language-Northern Emberá #language-Epena #language-Emberá-Tadó #language-Emberá-Chamí #language-Anserma #language-Caramanta #language-Alutor #language-Kerek #language-Barbareño #language-Ineseño #language-Purisimeño #language-Cochimi #language-Cocopa #language-Havasupai-Walapai-Yavapai #language-Mohave #language-Comecrudo #language-Garza #language-Onjob #language-Turaka #language-Maiwa (Papua New Guinea) #language-Daga #language-Mapena #language-Ginuman #language-Logorik #language-Dar Daju Daju #language-Dar Sila Daju #language-Njalgulgule #language-Baygo #language-Dar Fur Daju #language-Dizin #language-Nayi #language-Sheko #language-Donno So Dogon #language-Tommo So Dogon #language-Toro So Dogon #language-Bankan Tey Dogon #language-Ben Tey Dogon #language-Dogul Dom Dogon #language-Tebul Ure Dogon #language-Ana Tinga Dogon #language-Yanda Dom Dogon #language-Jamsay Dogon #language-Toro Tegu Dogon #language-Tomo Kan Dogon #language-Tiranige Diga Dogon #language-Ampari Dogon #language-Bunoge Dogon #language-Mombo Dogon #language-Doso #language-Turumsa #language-Northwestern Kolami #language-Southeastern Kolami #language-Mudhili Gadaba #language-Pottangi Ollar Gadaba #language-Kumarbhag Paharia #language-Sauria Paharia #language-Alu Kurumba #language-Holiya #language-Jennu Kurumba #language-Sholaga #language-Kannada #language-Kota (India) #language-Toda #language-Attapady Kurumba #language-Muduga #language-Kodava #language-Allar #language-Aranadan #language-Kadar #language-Kurichiya #language-Malankuravan #language-Malavedan #language-Malayalam #language-Malaryan #language-Mullu Kurumba #language-Thachanadan #language-Vishavan #language-Wayanad Chetti #language-Kalanadi #language-Kunduvadi #language-Pathiya #language-Ravula #language-Mala Malasar #language-Malapandaram #language-Old Tamil #language-Malasar #language-Mannan #language-Paliyan #language-Kaikadi #language-Pattapu #language-Yerukula #language-Korra Koraga #language-Mudu Koraga #language-Bellari #language-Kudiya #language-Northern Gondi #language-Eastern Muria #language-Western Muria #language-Adilabad Gondi #language-Aheri Gondi #language-Far Western Muria #language-Maria (India) #language-Dandami Maria #language-Konda-Dora #language-Kui (India) #language-Manda (India) #language-Pengo #language-Mukha-Dora #language-Waddar #language-Manna-Dora #language-Khirwar #language-Kamu #language-Kelo #language-Molo #language-Konai #language-Odoodee #language-Kubo #language-Samo #language-Fiwaga #language-Foi #language-Bine #language-Gizrra #language-Mednyj Aleut #language-Eastern Canadian Inuktitut #language-Kalaallisut #language-North Alaskan Inupiatun #language-Inuinnaqtun #language-Pacific Gulf Yupik #language-Garrwa #language-Wanyi #language-Bauzi #language-Demisa #language-Tefaro #language-Woria #language-Barapasi #language-Kofei #language-Sauri #language-Burate #language-Tunggare #language-Mangerr #language-Erre #language-Urningangg #language-Yemsa #language-Anfillo #language-Boro (Ethiopia) #language-Shekkacho #language-Chara #language-Koorete #language-Zayse-Zergulla #language-Basketo #language-Male (Ethiopia) #language-Dorze #language-Melo #language-Oyda #language-Wolaytta #language-Dawro #language-Gamo #language-Gofa #language-Mixed Great Andamanese #language-Cuiba #language-Playero #language-Kadiwéu #language-Abipon #language-Mocoví #language-Pilagá #language-Toba #language-Ngandi #language-Kunbarlang #language-Northern Haida #language-Southern Haida #language-Amarakaeri #language-Huachipaeri #language-Hatam #language-Ko #language-Warnang #language-Tira #language-Hibito #language-Jiongnai Bunu #language-Eastern Qiandong Miao #language-Northern Qiandong Miao #language-Southern Qiandong Miao #language-Eastern Xiangxi Miao #language-Western Xiangxi Miao #language-Bu-Nao Bunu #language-Ge #language-Luopohe Hmong #language-Hmong Daw #language-Horned Miao #language-Hmong Njua #language-Hmong Don #language-Hmong Dô #language-Northern Guiyang Hmong #language-Southern Guiyang Hmong #language-Southwestern Guiyang Hmong #language-Central Huishui Hmong #language-Eastern Huishui Hmong #language-Northern Huishui Hmong #language-Southwestern Huishui Hmong #language-Central Mashan Hmong #language-Northern Mashan Hmong #language-Southern Mashan Hmong #language-Western Mashan Hmong #language-Pa-Hng #language-Wunai Bunu #language-Younuo Bunu #language-Biao-Jiao Mien #language-Biao Mon #language-Kim Mun #language-Murui Huitoto #language-Hurrian #language-Urartian #language-Southeast Ijo #language-Nkoroo #language-Ibani #language-Kirike #language-Oruma #language-Biseni #language-Duriankere #language-Palaic #language-Carian #language-Cuneiform Luwian #language-Hieroglyphic Luwian #language-Pisidian #language-Lydian #language-Sidetic #language-Venetic #language-Gheg Albanian #language-Arbëreshë Albanian #language-Arvanitika Albanian #language-Classical Armenian #language-Middle Armenian #language-Western Armenian #language-Standard Latvian #language-Old Lithuanian #language-Old Russian #language-Church Slavic #language-Slavomolisano #language-Slovenian #language-Celtiberian #language-Galatian #language-Cisalpine Gaulish #language-Lepontic #language-Transalpine Gaulish #language-Middle Welsh #language-Old Welsh #language-Middle Breton #language-Old Breton #language-Old Cornish #language-Scottish Gaelic #language-Hiberno-Scottish Gaelic #language-Noric #language-Gothic #language-Elfdalian #language-Jutish #language-Old Norse #language-Norwegian Bokmål #language-Norwegian Nynorsk #language-Yiddish #language-Lower Silesian #language-Upper Saxon #language-Eastern Yiddish #language-Western Yiddish #language-Kölsch #language-Limburgan #language-Hunsrik #language-Pennsylvania German #language-Old High German (ca. 750-1050) #language-Colonia Tovar German #language-Swabian #language-Walser #language-Bavarian #language-Hutterite German #language-Unserdeutsch #language-Javindo #language-Petjo #language-Afrikaans #language-Oorlams #language-Berbice Creole Dutch #language-Negerhollands #language-Skepi Creole Dutch #language-Zeeuws #language-Old Dutch #language-Old Saxon #language-Low German #language-Middle Low German #language-Plautdietsch #language-Gronings #language-Achterhoeks #language-Drents #language-Sallands #language-Stellingwerfs #language-Twents #language-Veluws #language-Old English (ca. 450-1100) #language-Yola #language-Pitcairn-Norfolk #language-English #language-Virgin Islands Creole English #language-Bajan #language-Guyanese Creole English #language-Trinidadian Creole English #language-Antigua and Barbuda Creole English #language-Afro-Seminole Creole #language-Sea Island Creole English #language-Bahamas Creole English #language-Turks And Caicos Creole English #language-Vincentian Creole English #language-Grenadian Creole English #language-Tobagonian Creole English #language-Jamaican Creole English #language-Belize Kriol English #language-Nicaragua Creole English #language-Sranan Tongo #language-Kwinti #language-Krio #language-Ghanaian Pidgin English #language-Cameroon Pidgin #language-Nigerian Pidgin #language-Hawai'i Creole English #language-Kriol #language-Bislama #language-Pijin #language-Tok Pisin #language-Torres Strait Creole #language-Northern Frisian #language-Old Frisian #language-Western Frisian #language-Phrygian #language-Mycenaean Greek #language-Romano-Greek #language-Cappadocian Greek #language-Pontic #language-Mysian #language-Khowar #language-Sanskrit #language-Gawar-Bati #language-Shumashti #language-Grangali #language-Bhunjia #language-Kamar #language-Nahari #language-Kharia Thar #language-Lodhi #language-Tangchangya #language-Kurmukar #language-Naga Pidgin #language-Rajbanshi #language-Kupia #language-Lahnda #language-Western Panjabi #language-Northern Hindko #language-Southern Hindko #language-Pahari #language-Khetrani #language-Luwati #language-Sindhi Bhil #language-Lasi #language-Katkari #language-Goan Konkani #language-Old Marathi #language-Samvedi #language-Varhadi-Nagpuri #language-Andh #language-Rajasthani #language-Dubli #language-Kachi Koli #language-Vaghri #language-Wadiyara Koli #language-Merwari #language-Jandavra #language-Hadothi #language-Gade Lohar #language-Godwari #language-Marwari (India) #language-Bhaya #language-Goaria #language-Lambadi #language-Marwari (Pakistan) #language-Parkari Koli #language-Bauria #language-Dungra Bhil #language-Gamit #language-Mawchi #language-Vaagri Booli #language-Wagdi #language-Adiwasi Garasia #language-Rajput Garasia #language-Bhilali #language-Rathawi #language-Noiri #language-Dotyali #language-Jaunsari #language-Mandeali #language-Bhattiyali #language-Bilaspuri #language-Chambeali #language-Pangwali #language-Churahi #language-Bhadrawahi #language-Lahul Lohar #language-Kullu Pahari #language-Mahasu Pahari #language-Dhanki #language-Khandesi #language-Pali #language-Angika #language-Caribbean Hindustani #language-Kisan #language-Kudmali #language-Panchpargania #language-Oraon Sadri #language-Sadri #language-Rana Tharu #language-Chitwania Tharu #language-Kathoriya Tharu #language-Kochila Tharu #language-Dangaura Tharu #language-Sonha #language-Buksa #language-Majhi #language-Musasa #language-Kumhali #language-Darai #language-Dewas Rai #language-Powari #language-Surgujia #language-Domaaki #language-Balkan Romani #language-Baltic Romani #language-Caló #language-Kalo Finnish Romani #language-Braj #language-Kanauji #language-Bharia #language-Bundeli #language-Andaman Creole Hindi #language-Fiji Hindi #language-Hindi #language-Urdu #language-Ghera #language-Gurgula #language-Od #language-Khah #language-Wotapuri-Katarqalai #language-Indus Kohistani #language-Chilisso #language-Gowro #language-Mankiyali #language-Tirahi #language-Brokskat #language-Shina #language-Kohistani Shina #language-Ushojo #language-Savi #language-Dhivehi #language-Veddah #language-Avestan #language-Eastern Balochi #language-Koroshi #language-Southern Balochi #language-Western Balochi #language-Rudbari #language-Shahmirzadi #language-Gazi #language-Natanzi #language-Soi #language-Nayini #language-Lasgerdi #language-Sangisari #language-Sorkhei #language-Kurdish #language-Central Kurdish #language-Northern Kurdish #language-Southern Kurdish #language-Zaza #language-Gurani #language-Bajelani #language-Sarli #language-Kho'ini #language-Maraghei #language-Kajali #language-Kabatei #language-Upper Taromi #language-Harzani #language-Alviri-Vidari #language-Eshtehardi #language-Razajerdi #language-Takestani #language-Ashtiani #language-Vafsi #language-Old Ossetic #language-Yagnobi #language-Yazgulyam #language-Ormuri #language-Parachi #language-Waneci #language-Central Pashto #language-Northern Pashto #language-Southern Pashto #language-Khotanese #language-Tumshuqese #language-Old Persian (ca. 600-400 B.C.) #language-Pahlavi #language-Kumzari #language-Judeo-Tat #language-Muslim Tat #language-Judeo-Persian #language-Aimaq #language-Dari #language-Hazaragi #language-Bukharic #language-Lari #language-Dezfuli #language-Northern Luri #language-Bakhtiari #language-Southern Luri #language-Ashkun #language-Kamviri #language-Tregami #language-Faliscan #language-Latin #language-Istro Romanian #language-Megleno Romanian #language-Judeo-Italian #language-Sassarese Sardinian #language-Romagnol #language-Piemontese #language-Old French (842-ca. 1400) #language-Cajun French #language-Réunion Creole French #language-Tayo #language-Haitian #language-Guianese Creole French #language-Saint Lucian Creole French #language-Guadeloupean Creole French #language-San Miguel Creole French #language-Morisyen #language-Seselwa Creole French #language-Arpitan #language-Old Spanish #language-Ladino #language-Palenquero #language-Chavacano #language-Ternateño #language-Fala #language-Angolar #language-Principense #language-Sãotomense #language-Macanese #language-Timor Pidgin #language-Kabuverdianu #language-Papiamento #language-Upper Guinea Crioulo #language-Mozarabic #language-Gallurese Sardinian #language-Campidanese Sardinian #language-Logudorese Sardinian #language-Oscan #language-Umbrian #language-Hernican #language-Marrucinian #language-Paelignian #language-Vestinian #language-Sabine #language-South Picene #language-Aequian #language-Marsian #language-Volscian #language-Tokharian A #language-Tokharian B #language-Dacian #language-Lusitanian #language-Messapic #language-Thracian #language-Irántxe #language-Laurentian #language-Susquehannock #language-Nottoway #language-Wendat #language-Amurdak #language-Garig-Ilgar #language-Iwaidja #language-Old Japanese #language-Kikai #language-Oki-No-Erabu #language-Toku-No-Shima #language-Northern Amami-Oshima #language-Southern Amami-Oshima #language-Central Okinawan #language-Miyako #language-Jarawa (India) #language-Önge #language-Achuar-Shiwiar #language-Huambisa #language-Keiga #language-Tulishi #language-Krongo #language-Tumtum #language-Kanga #language-Katcha-Kadugli-Miri #language-Nukak Makú #language-Kamakan #language-Aekyom #language-Old Georgian #language-Judeo-Georgian #language-Katawixi #language-Kosadle #language-Qawasqar #language-Ap Ma #language-Eastern Keres #language-Western Keres #language-Korana #language-Xiri #language-Shua #language-Kua #language-Kxoe #language-Naro #language-Piro #language-Tiwa #language-Southern Tiwa #language-Bamu #language-Northeast Kiwai #language-Southern Kiwai #language-Waboda #language-Kerewo #language-Morigi #language-Ese #language-Ömie #language-Namiae #language-Barai #language-Biage #language-Mountain Koiali #language-Grass Koiari #language-Koitabu #language-Ndom #language-Kimaama #language-Uduk #language-Jejueo #language-Aja (South Sudan) #language-Bakwé #language-Wané #language-Gagnoa Bété #language-Kouya #language-Daloa Bété #language-Godié #language-Guiberoua Béte #language-Neyo #language-Yocoboué Dida #language-Lakota Dida #language-Kodia #language-Kuwaa #language-Mobumrin Aizi #language-Tiagbamrin Aizi #language-Southern Grebo #language-Northern Grebo #language-Barclayville Grebo #language-Central Grebo #language-Gboloo Grebo #language-Pye Krumen #language-Plapo Krumen #language-Tepo Krumen #language-Dewoin #language-Gbii #language-Tajuasohn #language-Nyabwa #language-Daho-Doo #language-Glaro-Twabo #language-Glio-Oubi #language-Sapo #language-Western Krahn #language-Wè Southern #language-Wè Western #language-Biangai #language-Kunimaipa #language-Weri #language-Mulaha #language-Humene #language-Uare #language-Isirawa #language-Bagusa #language-Kauwera #language-Trimuris #language-Airoran #language-Kwomtari #language-ǂHua #language-Awera #language-Rasawa #language-Saponi #language-Duvle #language-Edopi #language-Sikaritai #language-Doutai #language-Kaiy #language-Kwerisa #language-Papasena #language-Tause #language-Fayu #language-Owiniga #language-Ama (Papua New Guinea) #language-Nakwi #language-Nimo #language-Bo (Papua New Guinea) #language-Kembra #language-Lepki #language-Murkim #language-Wulna #language-Chambri #language-Yimas #language-Kopar #language-Murik (Papua New Guinea) #language-Banaro #language-Abu #language-Gorovu #language-Aiome #language-Anor #language-Breri #language-Romkun #language-Igana #language-Kominimung #language-Andarum #language-Tanguat #language-Tanggu #language-Borei #language-Awar #language-Bosngun #language-Watam #language-Massalat #language-Surbakhal #language-Karanga #language-Maba (Chad) #language-Kibet #language-Runga #language-Karon Dori #language-Northwest Maidu #language-Northeast Maidu #language-Valley Maidu #language-Laua #language-Morawa #language-Bauwaki #language-Mer #language-Mairasi #language-Semimi #language-Boko (Benin) #language-Bokobaru #language-Busa #language-Shanga #language-Matya Samo #language-Maya Samo #language-Southern Samo #language-Kla-Dan #language-Toura (Côte d'Ivoire) #language-Guro #language-Yaouré #language-Gbin #language-Mwan #language-Jalkunan #language-Ligbi #language-Tonjon #language-Bolon #language-Marka #language-Eastern Maninkakan #language-Konyanka Maninka #language-Manya #language-Sankaran Maninka #language-Mahou #language-Wojenaka #language-Worodougou #language-Koro (Côte d'Ivoire) #language-Koyaga #language-Mandinka #language-Kagoro #language-Kita Maninkakan #language-Jahanka #language-Western Maninkakan #language-Xaasongaxango #language-Kakabe #language-Kuranko #language-Lele (Guinea) #language-Kono (Sierra Leone) #language-Yalunka #language-Guinea Kpelle #language-Kono (Guinea) #language-Liberia Kpelle #language-Loma (Liberia) #language-Toma #language-Bandi #language-Mende (Sierra Leone) #language-Northern Bobo Madaré #language-Southern Bobo Madaré #language-Seeku #language-Bankagooma #language-Duungooma #language-Dzùùngoo #language-Kpeego #language-Jenaama Bozo #language-Tiemacèwè Bozo #language-Tiéyaxo Bozo #language-Sininkere #language-Mangarrayi #language-Alawa #language-Marra #language-Wandarang #language-Djeebbana #language-Burarra #language-Doromu-Koki #language-Maria (Papua New Guinea) #language-Hozo #language-Seze #language-Margu #language-Maca #language-Iyojwa'ja Chorote #language-Iyo'wujwa Chorote #language-Wichí Lhamtés Nocten #language-Wichí Lhamtés Vejoz #language-Wichí Lhamtés Güisnay #language-Kekchí #language-Uspanteco #language-Sacapulteco #language-Sipacapense #language-Tz'utujil #language-Cakchiquel-Quiché Mixed Language #language-K'iche' #language-Poqomam #language-Poqomchi' #language-Aguacateco #language-Ixil #language-Tektiteko #language-Epigraphic Mayan #language-Chol #language-Tabasco Chontal #language-Chortí #language-Tojolabal #language-Mocho #language-Popti' #language-Q'anjob'al #language-Itzá #language-Mopán Maya #language-Nungali #language-Gudanji #language-Wambaya #language-Mískito #language-Cacaopera #language-Matagalpa #language-Mayangna #language-Ulwa #language-Karkin #language-Plains Miwok #language-Central Sierra Miwok #language-Northern Sierra Miwok #language-Southern Sierra Miwok #language-Coast Miwok #language-Lake Miwok #language-Oluta Popoluca #language-Sayula Popoluca #language-Totontepec Mixe #language-Tlahuitoltepec Mixe #language-Coatlán Mixe #language-Isthmus Mixe #language-Mazatlán Mixe #language-Juquila Mixe #language-North Central Mixe #language-Chimalapa Zoque #language-Copainalá Zoque #language-Francisco León Zoque #language-Rayón Zoque #language-Highland Popoluca #language-Tabasco Zoque #language-Texistepec Popoluca #language-Yeniche #language-Gurindji Kriol #language-Media Lengua #language-Koneraw #language-Mombum #language-Kitan #language-Mogholi #language-Buriat #language-Mongolian #language-China Buriat #language-Mongolia Buriat #language-Russia Buriat #language-Halh Mongolian #language-Peripheral Mongolian #language-Kalmyk #language-East Yugur #language-Dongxiang #language-Kangjia #language-Monumbo #language-Smärky Kanum #language-Sota Kanum #language-Yei #language-Namat #language-Nambo #language-Neme #language-Nen #language-Nama (Papua New Guinea) #language-Namo #language-Arammba #language-Rema #language-Wára #language-Creek #language-Mikasuki #language-Apalachee #language-Nadëb #language-Dâw #language-Yuhup #language-Karata #language-Aghwan #language-Sabanê #language-Southern Nambikuára #language-Mamaindé #language-Lakondê #language-Latundê #language-Tawandê #language-Namla #language-Tofanma #language-Acheron #language-Torona #language-Boikin #language-Ngala #language-Ambulas #language-Hanga Hundi #language-Manambu #language-Koiwat #language-Sengo #language-Burui #language-Gaikundi #language-Sos Kundi #language-Kakwa #language-Mandari #language-Kuku #language-Imotong #language-Lango (South Sudan) #language-Logir #language-Okolie #language-Ngasa #language-Masai #language-Karamojong #language-Nyangatom #language-Kalenjin #language-Kipsigis #language-Nandi #language-Markweeta #language-Pökoot #language-Okiek #language-Burun #language-Jumjum #language-Mabaan #language-Northeastern Dinka #language-Northwestern Dinka #language-Southwestern Dinka #language-South Central Dinka #language-Southeastern Dinka #language-Anuak #language-Belanda Bor #language-Luwo #language-Thuri #language-Acoli #language-Adhola #language-Luo (Kenya and Tanzania) #language-Kumam #language-Lango (Uganda) #language-Mlap #language-Gresi #language-Kemtuik #language-Tabaru #language-Galela #language-Modole #language-Kao #language-Pagu #language-Tobelo #language-Tugutil #language-Ibu #language-Sahu #language-Waioli #language-Tidore #language-Rotokas #language-Old Nubian #language-Midob #language-Birked #language-Dair #language-Kadaru #language-El Hugeirat #language-Karko #language-Wali (Sudan) #language-Keoru-Ahia #language-Opao #language-Orokolo #language-Beli (Papua New Guinea) #language-Laeko-Libuat #language-Urim #language-Wom (Papua New Guinea) #language-Au #language-Elkei #language-Olo #language-Urat #language-Bumbita Arapesh #language-Abu' Arapesh #language-Bukiyip #language-Yambes #language-Eitiep #language-Kombio #language-Aruek #language-Buna #language-Bungain #language-Kamasau #language-Urimo #language-Ningil #language-Yil #language-Bragat #language-Ambrak #language-Yangum Gel #language-Yangum Mon #language-Yangum Dey #language-Gnau #language-Seta #language-Seti #language-Kwamtim One #language-Southern One #language-Inebu One #language-Kabore One #language-Molmo One #language-Northern One #language-Agi #language-Yau (Sandaun Province) #language-Yis #language-Guhu-Samane #language-Yekora #language-Suena #language-Zia #language-Binandere #language-Ewage-Notu #language-Doghoro #language-Gaina #language-Korafe-Yegha #language-Aeka #language-Hunjara-Kaina Ke #language-Orokaiva #language-Kamoro #language-Sempan #language-Central Asmat #language-Yaosakor Asmat #language-Citak #language-Diuwe #language-Tamnim Citak #language-Buruwai #language-Asue Awyu #language-Edera Awyu #language-North Awyu #language-South Awyu #language-Aghu #language-Central Awyu #language-Ketum #language-Wambon #language-Mandobo Atas #language-Mandobo Bawah #language-Kombai #language-Wanggom #language-Sawi #language-Komyandaret #language-Kopkaka #language-Burumakok #language-Kwer #language-North Muyu #language-South Muyu #language-Bimin #language-Faiwol #language-Setaman #language-Telefol #language-Tifal #language-Urapmin #language-Mian #language-Suganga #language-Nakai #language-Tangko #language-Imbongu #language-Umbu-Ungu #language-Bo-Ung #language-Melpa #language-Maring #language-Kandawo #language-Narak #language-Chuave #language-Nomane #language-Golin #language-Sinasina #language-North Wahgi #language-Wahgi #language-Nggem #language-Wano #language-Mid Grand Valley Dani #language-Hupla #language-Lower Grand Valley Dani #language-Upper Grand Valley Dani #language-Walak #language-Nduga #language-Angguruk Yali #language-Ninia Yali #language-Pass Valley Yali #language-Enga #language-Ipili #language-Kyaka #language-Lembena #language-Mae #language-Sari #language-Bisorio #language-Nete #language-Huli #language-Samberigi #language-Angal Heneng #language-Angal Enen #language-West Kewa #language-East Kewa #language-Erave #language-Mungkip #language-Numanggang #language-Nek #language-Nuk #language-Finongan #language-Mamaa #language-Nimi #language-Ma Manda #language-Nekgini #language-Neko #language-Ufim #language-Ngaing #language-Nukna #language-Som #language-Weliki #language-Yau (Morobe Province) #language-Tuma-Irumu #language-Awara #language-Forak #language-Degenan #language-Asaro'o #language-Bulgebi #language-Guya #language-Yagomi #language-Nankina #language-Ma (Papua New Guinea) #language-Bonkiman #language-Yopno #language-Yout Wam #language-Ono #language-Sialum #language-Kovai #language-Sene #language-Kâte #language-Mape #language-Migabac #language-Momare #language-Nomu #language-Kinalakna #language-Kumukio #language-Timbe #language-Selepet #language-Mese #language-Nabak #language-Dedua #language-Tobo #language-Gende #language-Fore #language-Gimi (Eastern Highlands) #language-Dano #language-Tokano #language-Benabena #language-Siane #language-Yaweyuha #language-Inoke-Yate #language-Kamano #language-Kanite #language-Keyagana #language-Yagaria #language-Abaga #language-Isabi #language-Usarufa #language-Awa (Papua New Guinea) #language-Agarabi #language-Gadsup #language-North Tairora #language-South Tairora #language-Waffa #language-Kambaira #language-Kenati #language-Amaimon #language-Korak #language-Waskia #language-Maiani #language-Mala (Papua New Guinea) #language-Miani #language-Bepour #language-Moere #language-Kowaki #language-Mawak #language-Yaben #language-Ukuriguma #language-Yarawata #language-Kare (Papua New Guinea) #language-Gumalu #language-Bau #language-Isebe #language-Panim #language-Baimak #language-Gal #language-Garus #language-Rempi #language-Yoidik #language-Bagupi #language-Mawan #language-Saruga #language-Silopi #language-Utu #language-Matepi #language-Nake #language-Rapting #language-Mosimo #language-Murupi #language-Samosa #language-Wamas #language-Munit #language-Kobon #language-Kalam #language-Tai #language-Wadaginam #language-Anam #language-Moresada #language-Kesawai #language-Sausi #language-Arawum #language-Lemio #language-Pulabu #language-Siroi #language-Bongu #language-Male (Papua New Guinea) #language-Jilim #language-Rerau #language-Yangulam #language-Danaru #language-Urigina #language-Biyom #language-Wasembo #language-Ganglau #language-Saep #language-Yabong #language-Eipomek #language-Una #language-Korupun-Sela #language-Kosarek Yale #language-Nipsan #language-Moni #language-Wolani #language-Auye #language-Dao #language-Ofayé #language-Krenak #language-Acroá #language-Xakriabá #language-Xavánte #language-Xerénte #language-Xokleng #language-São Paulo Kaingáng #language-Kayapó #language-Krahô #language-Pataxó Hã-Ha-Hãe #language-Koropó #language-Afitti #language-Ama (Sudan) #language-Warrwa #language-Ngumbarl #language-Dyugun #language-Yawuru #language-Nimanbur #language-Bardi #language-Djawi #language-Dyaberdyaber #language-Nyulnyul #language-Ipalapa Amuzgo #language-San Pedro Amuzgos Amuzgo #language-Tepeuxila Cuicatec #language-Teutila Cuicatec #language-Amoltepec Mixtec #language-Mixtepec Mixtec #language-Tezoatlán Mixtec #language-Northwest Oaxaca Mixtec #language-Silacayoapan Mixtec #language-Chayuco Mixtec #language-Ixtayutla Mixtec #language-Jamiltepec Mixtec #language-San Juan Colorado Mixtec #language-Tututepec Mixtec #language-Pinotepa Nacional Mixtec #language-Santa María Zacatepec Mixtec #language-Diuxi-Tilantongo Mixtec #language-Mitlatongo Mixtec #language-Peñoles Mixtec #language-Tlazoyaltepec Mixtec #language-Huitepec Mixtec #language-San Miguel Piedras Mixtec #language-Sindihui Mixtec #language-Tamazola Mixtec #language-Yutanduchi Mixtec #language-Alacatlatzala Mixtec #language-Alcozauca Mixtec #language-Metlatónoc Mixtec #language-Yoloxochitl Mixtec #language-Apasco-Apoala Mixtec #language-Southeastern Nochixtlán Mixtec #language-Soyaltepec Mixtec #language-Coatzospan Mixtec #language-Cuyamecalco Mixtec #language-Tidaá Mixtec #language-Cacaloxtepec Mixtec #language-Chazumba Mixtec #language-Chigmecatitlán Mixtec #language-Southern Puebla Mixtec #language-Ayutla Mixtec #language-Juxtlahuaca Mixtec #language-Western Juxtlahuaca Mixtec #language-Atatláhuca Mixtec #language-Itundujia Mixtec #language-Magdalena Peñasco Mixtec #language-Northern Tlaxiaco Mixtec #language-Ocotepec Mixtec #language-San Juan Teita Mixtec #language-San Miguel El Grande Mixtec #language-Santa Lucía Monteverde Mixtec #language-Sinicahua Mixtec #language-Southwestern Tlaxiaco Mixtec #language-Tijaltepec Mixtec #language-Yosondúa Mixtec #language-Yucuañe Mixtec #language-Chicahuaxtla Triqui #language-Copala Triqui #language-San Martín Itunyoso Triqui #language-Chochotec #language-Mezontla Popoloca #language-San Juan Atzingo Popoloca #language-San Luís Temalacayuca Popoloca #language-Coyotepec Popoloca #language-San Felipe Otlaltepec Popoloca #language-Santa Inés Ahuatempan Popoloca #language-Soyaltepec Mazatec #language-San Jerónimo Tecóatl Mazatec #language-Chiquihuitlán Mazatec #language-Jalapa De Díaz Mazatec #language-Ayautla Mazatec #language-Ixcatlán Mazatec #language-Huautla Mazatec #language-Mazatlán Mazatec #language-Zapotec #language-Zenzontepec Chatino #language-Tataltepec Chatino #language-Eastern Highland Chatino #language-Nopala Chatino #language-Western Highland Chatino #language-Zacatepec Chatino #language-Asunción Mixtepec Zapotec #language-Ayoquesco Zapotec #language-Mazaltepec Zapotec #language-Mitla Zapotec #language-San Pedro Quiatoni Zapotec #language-Santa Catarina Albarradas Zapotec #language-Santo Domingo Albarradas Zapotec #language-Tejalapan Zapotec #language-Lapaguía-Guivini Zapotec #language-Santa María Quiegolani Zapotec #language-Santiago Xanica Zapotec #language-Xadani Zapotec #language-Xanaguía Zapotec #language-Mixtepec Zapotec #language-Guevea De Humboldt Zapotec #language-Petapa Zapotec #language-Lachiguiri Zapotec #language-Quiavicuzas Zapotec #language-Chichicapan Zapotec #language-Güilá Zapotec #language-Western Tlacolula Valley Zapotec #language-Isthmus Zapotec #language-Ocotlán Zapotec #language-Zaachila Zapotec #language-Santa Inés Yatzechi Zapotec #language-Tilquiapan Zapotec #language-Yautepec Zapotec #language-Loxicha Zapotec #language-Ozolotepec Zapotec #language-San Agustín Mixtepec Zapotec #language-Choapan Zapotec #language-Cajonos Zapotec #language-Tabaa Zapotec #language-Yalálag Zapotec #language-Yatzachi Zapotec #language-Zoogocho Zapotec #language-Rincón Zapotec #language-Yatee Zapotec #language-Las Delicias Zapotec #language-Southern Rincon Zapotec #language-Aloápam Zapotec #language-Sierra de Juárez Zapotec #language-Southeastern Ixtlán Zapotec #language-Yareni Zapotec #language-Coatecas Altas Zapotec #language-Amatlán Zapotec #language-Tlacolulita Zapotec #language-San Vicente Coatlán Zapotec #language-Coatlán Zapotec #language-San Baltazar Loxicha Zapotec #language-Elotepec Zapotec #language-Texmelucan Zapotec #language-Zaniza Zapotec #language-Totomachapan Zapotec #language-El Alto Zapotec #language-Lachixío Zapotec #language-Ojitlán Chinantec #language-Sochiapam Chinantec #language-Usila Chinantec #language-Chiltepec Chinantec #language-Tlacoatzintepec Chinantec #language-Palantla Chinantec #language-Tepetotutla Chinantec #language-Ozumacín Chinantec #language-Valle Nacional Chinantec #language-Lalana Chinantec #language-Lealao Chinantec #language-Tepinapa Chinantec #language-Comaltepec Chinantec #language-Quiotepec Chinantec #language-Chichimeca-Jonaz #language-Atzingo Matlatzinca #language-San Francisco Matlatzinca #language-Central Mazahua #language-Michoacán Mazahua #language-Eastern Highland Otomi #language-Tenango Otomi #language-Texcatepec Otomi #language-Mezquital Otomi #language-Querétaro Otomi #language-Ixtenco Otomi #language-Tilapa Otomi #language-Estado de México Otomi #language-Temoaya Otomi #language-Central Pame #language-Northern Pame #language-Southern Pame #language-Chiapanec #language-Subtiaba #language-Azoyú Me'phaa #language-Malinaltepec Me'phaa #language-Acatepec Me'phaa #language-Tlacoapa Me'phaa #language-Idi #language-Atsugewi #language-Dyirbal #language-Kala Lagaw Ya #language-Kaytetye #language-Lower Southern Aranda #language-Alyawarr #language-Andegerebinha #language-Anmatyerre #language-Eastern Arrernte #language-Western Arrarnta #language-Ayerrerenge #language-Wirangu #language-Banggarla #language-Guyani #language-Narungga #language-Nauo #language-Ngadjuri #language-Nugunu (Australia) #language-Warumungu #language-Mangala #language-Nyangumarta #language-Warlpiri #language-Warlmanpa #language-Walmajarri #language-Gurindji #language-Mudburra #language-Jaru #language-Ngardi #language-Martu Wangka #language-Kukatja #language-Pintupi-Luritja #language-Ngaanyatjarra #language-Pitjantjatjara #language-Yankunytjatjara #language-Antakarinya #language-Kokata #language-Jandai #language-Yagara #language-Bigambal #language-Yugambal #language-Kalkutung #language-Yalarnnga #language-Yanda #language-Biri #language-Gangulu #language-Gugu Badhun #language-Gungabula #language-Guwamu #language-Kunggari #language-Mandandanyi #language-Wadjigu #language-Yandjibara #language-Gunya #language-Margany #language-Punthamara #language-Wangkumara #language-Pirlatapa #language-Dieri #language-Ngamini #language-Yarluyandi #language-Yandruwandha #language-Yawarawarga #language-Nhirrpi #language-Arabana #language-Pitta Pitta #language-Pirriya #language-Dyangadi #language-Nganyaywana #language-Yanyuwa #language-Thawa #language-Wagaya #language-Yindjilandji #language-Nyawaygi #language-Yuru #language-Gugadj #language-Ikaranggal #language-Tagalaka #language-Thaypan #language-Pakanha #language-Wikngenchera #language-Kanju #language-Kuuku-Ya'u #language-Umbindhamu #language-Flinders Island #language-Wik-Epa #language-Wik-Me'anha #language-Wik-Iiyanh #language-Wik-Mungkan #language-Kuku-Uwanh #language-Kuku-Ugbanh #language-Kuku-Mu'inh #language-Wikalkan #language-Lamalama #language-Mayaguduna #language-Ngawun #language-Mayi-Thakurti #language-Mayi-Yapi #language-Mayi-Kulan #language-Wunumara #language-Mbara (Australia) #language-Walangama #language-Kuthant #language-Areba #language-Yinwum #language-Anguthimri #language-Awngthim #language-Ndra'ngith #language-Gudang #language-Atampaya #language-Angkamuthi #language-Alngith #language-Mpalitjanh #language-Gugubera #language-Kuuk-Yak #language-Bayali #language-Dharumbal #language-Mirning #language-Yinggarda #language-Nhanda #language-Badimaya #language-Malgana #language-Wajarri #language-Kalaamaya #language-Ngadjunmaya #language-Kalarko #language-Bibbulman #language-Goreng #language-Pinjarup #language-Wajuk #language-Wardandi #language-Bayungu #language-Pinigura #language-Burduna #language-Dhalandji #language-Djiwarli #language-Thiin #language-Dhargari #language-Wariyangga #language-Nhuwala #language-Tjurruru #language-Kariyarra #language-Ngarluma #language-Yinhawangka #language-Kurrama #language-Yindjibarndi #language-Ngarla #language-Nyamal #language-Bandjalang #language-Muruwari #language-Kuri #language-Awabakal #language-Worimi #language-Birrpayi #language-Gundungurra #language-Ngunawal #language-Dhurga #language-Jaitmatang #language-Ngarigu #language-Kumbainggar #language-Yaygir #language-Gureng Gureng #language-Dhungaloo #language-Wakawaka #language-Wuliwuli #language-Dhudhuroa #language-Pallanganmiddang #language-Yabula Yabula #language-Wathawurrung #language-Ladji Ladji #language-Madhi Madhi #language-Nari Nari #language-Wadi Wadi #language-Wotjobaluk #language-Wergaia #language-Daungwurrung #language-Woiwurrung #language-Bunganditj #language-Dadi Dadi #language-Yitha Yitha #language-Malyangapa #language-Wadikali #language-Yardliyawarra #language-Guugu Yimidhirr #language-Djangun #language-Kuku-Yalanji #language-Muluridyi #language-Dayi #language-Dhangu-Djangu #language-Djambarrpuyngu #language-Gupapuyngu #language-Dhuwal #language-Gumatj #language-Dhuwaya #language-Djinba #language-Djinang #language-Golpa #language-Yan-nhangu #language-Cashibo-Cacataibo #language-Kaxararí #language-Tuxináwa #language-Chácobo #language-Karipuna #language-Pacahuara #language-Panobo #language-Sensi #language-Capanahua #language-Shipibo-Conibo #language-Amahuaca #language-Cashinahua #language-Shanenawa #language-Sharanahua #language-Yaminahua #language-Yawanawa #language-Yora #language-Atsahuaca #language-Marúbo #language-Panoan Katukína #language-Isconahua #language-Nukuini #language-Poyanáwa #language-Matís #language-Korubo #language-Kulina Pano #language-Cavineña #language-Tacana #language-Araona #language-Toromono #language-Emumu #language-Karkar-Yuri #language-Yafi #language-Dubu #language-Towei #language-Pinai-Hagahai #language-Nefamese #language-Mobilian #language-Pidgin Delaware #language-Chinese Pidgin English #language-Tay Boi #language-Barikanchi #language-Gibanawa #language-Broome Pearling Lugger Pidgin #language-Hiri Motu #language-Ndyuka-Trio Pidgin #language-Fanagalo #language-Southeastern Pomo #language-Central Pomo #language-Northern Pomo #language-Southern Pomo #language-Puri #language-Pacaraos Quechua #language-Cajatambo North Lima Quechua #language-Chiquián Ancash Quechua #language-Huallaga Huánuco Quechua #language-Margos-Yarowilca-Lauricocha Quechua #language-Panao Huánuco Quechua #language-Huamalíes-Dos de Mayo Huánuco Quechua #language-Huaylas Ancash Quechua #language-Northern Conchucos Ancash Quechua #language-Southern Conchucos Ancash Quechua #language-Corongo Ancash Quechua #language-Sihuas Ancash Quechua #language-Huaylla Wanca Quechua #language-Jauja Wanca Quechua #language-Ambo-Pasco Quechua #language-North Junín Quechua #language-Santa Ana de Tusi Pasco Quechua #language-Cajamarca Quechua #language-Lambayeque Quechua #language-Classical Quechua #language-Chachapoyas Quechua #language-San Martín Quechua #language-Arequipa-La Unión Quechua #language-Ayacucho Quechua #language-North Bolivian Quechua #language-Santiago del Estero Quichua #language-South Bolivian Quechua #language-Calderón Highland Quichua #language-Salasaca Highland Quichua #language-Loja Highland Quichua #language-Cañar Highland Quichua #language-Imbabura Highland Quichua #language-Napo Lowland Quechua #language-Tena Lowland Quichua #language-Northern Pastaza Quichua #language-Southern Pastaza Quechua #language-Cusco Quechua #language-Eastern Apurímac Quechua #language-Puno Quechua #language-Chincha Quechua #language-Yauyos Quechua #language-Tegali #language-Tenino #language-Umatilla #language-Berti #language-Kube #language-Kanembu #language-Tarjumo #language-Tumari Kanuri #language-Central Kanuri #language-Bilma Kanuri #language-Manga Kanuri #language-Dazaga #language-Tedaga #language-Bella Coola #language-Halkomelem #language-Sechelt #language-Straits Salish #language-Southern Puget Sound Salish #language-Skagit #language-Snohomish #language-Clallam #language-Cowlitz #language-Columbia-Wenatchi #language-Kalispel-Pend d'Oreille #language-Spokane #language-Sáliba #language-Maco #language-Dera (Indonesia) #language-Nafri #language-Sentani #language-Abau #language-Amal #language-Iwam #language-Chenapian #language-Wogamusin #language-Kwoma #language-Kwanga #language-Mende (Papua New Guinea) #language-Awtuw #language-Karawa #language-Pouye #language-Ayi (Papua New Guinea) #language-Pasi #language-Mehek #language-Bahinemo #language-Bisis #language-Mari (East Sepik Province) #language-Sumariup #language-Kapriman #language-Alamblak #language-Kaningra #language-Saniyo-Hiyewe #language-Hewa #language-Niksek #language-Piame #language-Ak #language-Namia #language-Shasta #language-Armenian Sign Language #language-Australian Aborigines Sign Language #language-Monastic Sign Language #language-Plains Indian Sign Language #language-Afghan Sign Language #language-Albanian Sign Language #language-Argentine Sign Language #language-Cambodian Sign Language #language-Guatemalan Sign Language #language-Hausa Sign Language #language-Maltese Sign Language #language-Mauritian Sign Language #language-Mozambican Sign Language #language-Nicaraguan Sign Language #language-Penang Sign Language #language-Sri Lankan Sign Language #language-Tanzanian Sign Language #language-Tibetan Sign Language #language-Turkish Sign Language #language-Zambian Sign Language #language-Zimbabwe Sign Language #language-Egypt Sign Language #language-Libyan Sign Language #language-Saudi Arabian Sign Language #language-Maritime Sign Language #language-British Sign Language #language-New Zealand Sign Language #language-Auslan #language-Papua New Guinean Sign Language #language-Namibian Sign Language #language-South African Sign Language #language-Chilean Sign Language #language-Paraguayan Sign Language #language-Uruguayan Sign Language #language-Hanoi Sign Language #language-Ho Chi Minh City Sign Language #language-Chinese Sign Language #language-German Sign Language #language-Israeli Sign Language #language-Polish Sign Language #language-Swiss-German Sign Language #language-Nepalese Sign Language #language-Indian Sign Language #language-Pakistan Sign Language #language-Japanese Sign Language #language-Korean Sign Language #language-Taiwan Sign Language #language-Algerian Sign Language #language-Austrian Sign Language #language-Brazilian Sign Language #language-Estonian Sign Language #language-French Sign Language #language-Greek Sign Language #language-Irish Sign Language #language-Latvian Sign Language #language-Mexican Sign Language #language-Philippine Sign Language #language-Swiss-French Sign Language #language-Dominican Sign Language #language-Ethiopian Sign Language #language-Ghanaian Sign Language #language-Guinean Sign Language #language-Moroccan Sign Language #language-Puerto Rican Sign Language #language-Quebec Sign Language #language-Salvadoran Sign Language #language-Sierra Leone Sign Language #language-Thai Sign Language #language-Trinidad and Tobago Sign Language #language-American Sign Language #language-Jamaican Sign Language #language-Costa Rican Sign Language #language-Honduras Sign Language #language-Panamanian Sign Language #language-Malaysian Sign Language #language-Selangor Sign Language #language-Chadian Sign Language #language-Nigerian Sign Language #language-Rwandan Sign Language #language-Ugandan Sign Language #language-Bolivian Sign Language #language-Colombian Sign Language #language-Ecuadorian Sign Language #language-Peruvian Sign Language #language-Catalan Sign Language #language-Valencian Sign Language #language-Bulgarian Sign Language #language-Czech Sign Language #language-Hungarian Sign Language #language-Romanian Sign Language #language-Slovakian Sign Language #language-Dutch Sign Language #language-Langue des signes de Belgique Francophone #language-Vlaamse Gebarentaal #language-Italian Sign Language #language-Swiss-Italian Sign Language #language-Tunisian Sign Language #language-Danish Sign Language #language-Icelandic Sign Language #language-Madagascar Sign Language #language-Norwegian Sign Language #language-Yugoslavian Sign Language #language-Haiphong Sign Language #language-Chiangmai Sign Language #language-Lithuanian Sign Language #language-Moldova Sign Language #language-Mongolian Sign Language #language-Ukrainian Sign Language #language-Russian Sign Language #language-Spanish Sign Language #language-Venezuelan Sign Language #language-Portuguese Sign Language #language-Swedish Sign Language #language-Finland-Swedish Sign Language #language-Finnish Sign Language #language-Cuba Sign Language #language-International Sign #language-Adamorobe Sign Language #language-Albarradas Sign Language #language-Al-Sayyid Bedouin Sign Language #language-Ban Khor Sign Language #language-Bribri Sign Language #language-Brunca Sign Language #language-Ghandruk Sign Language #language-Inuit Sign Language #language-Jamaican Country Sign Language #language-Jhankot Sign Language #language-Jumla Sign Language #language-Mardin Sign Language #language-Martha's Vineyard Sign Language #language-Miriwoong Sign Language #language-Miyakubo Sign Language #language-Old Kentish Sign Language #language-Seychelles Sign Language #language-Sivia Sign Language #language-Solomon Islands Sign Language #language-Tebul Sign Language #language-Urubú-Kaapor Sign Language #language-Yucatec Maya Sign Language #language-Providencia Sign Language #language-Olekha #language-Dakpakha #language-Dzalakha #language-Chalikha #language-Bumthangkha #language-Khengkha #language-Kurtokha #language-Classical Tibetan #language-Zangskari #language-Purik #language-Tibetan #language-Humla #language-Lhomi #language-Walungge #language-Dolpo #language-Tichurong #language-Tsum #language-Kyerung #language-Mugom #language-Jirel #language-Naaba #language-Khams Tibetan #language-Tseku #language-Bhoti Kinnauri #language-Stod Bhoti #language-Jad #language-Spiti Bhoti #language-Brokpake #language-Chocangacakha #language-Groma #language-Dzongkha #language-Layakha #language-Lunanakha #language-Khamba #language-Amdo Tibetan #language-Kaike #language-Northern Ghale #language-Southern Ghale #language-Eastern Gorkha Tamang #language-Seke (Nepal) #language-Gurung #language-Nar Phu #language-Chantyal #language-Eastern Tamang #language-Western Tamang #language-Rongpo #language-Rangkas #language-Chaudangsi #language-Byangsi #language-Kanashi #language-Tukpa #language-Jangshung #language-Shumcho #language-Pattani #language-Kalaktang Monpa #language-Tshangla #language-Kok Borok #language-Riang (India) #language-Tippera #language-Usui #language-Kachari #language-Atong (India) #language-Koch #language-Ruga #language-Chak #language-Kadu #language-Taman (Myanmar) #language-Chang Naga #language-Konyak Naga #language-Phom Naga #language-Wancho Naga #language-Khiamniungan Naga #language-Leinong Naga #language-Makyan Naga #language-Nocte Naga #language-Tutsa Naga #language-Ugong #language-Hpon #language-Maru #language-Pela #language-Taungyo #language-Danu #language-Intha #language-Old Burmese #language-Tavoyan #language-Marma #language-Pholo #language-Phana' #language-Bisu #language-Laomian #language-Pyen #language-Côông #language-Honi #language-Biyo #language-Enu #language-Kaduo #language-Akeu #language-Akha #language-Chepya #language-Muda #language-Sila #language-Buyuan Jinuo #language-Youle Jinuo #language-Kucong #language-Lahu Shi #language-Katso #language-Samatao #language-Lawu #language-Miqie #language-Limi #language-Mili #language-Sonaga #language-Kuamasi #language-Kua-nsi #language-Dongshanba Lalo #language-Western Lalu #language-Xishanba Lalo #language-Eastern Lalu #language-Lamu #language-Naluo Yi #language-Laghuu #language-Thopho #language-Qila Muji #language-Bokha #language-Phuma #language-Northern Muji #language-Southern Muji #language-Ani Phowa #language-Labo Phowa #language-Hlepho Phowa #language-Khlula #language-Zokhuo #language-Southern Nisu #language-Eastern Nisu #language-Northern Nisu #language-Sichuan Yi #language-Gepo #language-Samei #language-Sanie #language-Wuding-Luquan Yi #language-Ayizi #language-Chesu #language-Wumeng Nasu #language-Wusa Nasu #language-Aluo #language-Ache #language-Alugu #language-Phupa #language-Phuza #language-Phala #language-Alo Phola #language-Azha #language-Axi Yi #language-Azhe #language-Nisi (China) #language-Nusu #language-Zauzou #language-Ersu #language-Narua #language-Queyu #language-Northern Pumi #language-Southern Pumi #language-Southern Qiang #language-Northern Tujia #language-Southern Tujia #language-Toto #language-Lepcha #language-Lhokpu #language-Dura #language-Gamale Kham #language-Sheshi Kham #language-Eastern Parbate Kham #language-Western Parbate Kham #language-Eastern Magar #language-Western Magar #language-Saam #language-Sampang #language-Chukwa #language-Kulung (Nepal) #language-Nachering #language-Camling #language-Dungmali #language-Waling #language-Chhulung #language-Athpariya #language-Belhariya #language-Lohorung #language-Southern Yamphu #language-Yamphu #language-Eastern Meohang #language-Western Meohang #language-Jerung #language-Bahing #language-Wayu #language-Dumi #language-Baraamu #language-Mobwa Karen #language-Geba Karen #language-Manumanaw Karen #language-Yintale Karen #language-Eastern Kayah #language-Western Kayah #language-Geko Karen #language-Yinbaw Karen #language-Pa'o Karen #language-Pwo Eastern Karen #language-Pwo Western Karen #language-Phrae Pwo Karen #language-Pwo Northern Karen #language-Paku Karen #language-Wewaw #language-Bugun #language-Manipuri #language-Khezha Naga #language-Angami Naga #language-Chokri Naga #language-Mao Naga #language-Poumei Naga #language-Northern Rengma Naga #language-Pochuri Naga #language-Southern Rengma Naga #language-Sumi Naga #language-Ao Naga #language-Lotha Naga #language-Sangtam Naga #language-Jejara Naga #language-Yimchungru Naga #language-Long Phuri Naga #language-Makuri Naga #language-Amri Karbi #language-Bawm Chin #language-Bualkhaw Chin #language-Falam Chin #language-Biete #language-Darlong #language-Hmar #language-Senthang Chin #language-Zotung Chin #language-Mara Chin #language-Shendu #language-Aimol #language-Anal #language-Kom (India) #language-Monsang Naga #language-Ranglong #language-Eastern Khumi Chin #language-Khumi Chin #language-Ngawn Chin #language-Zou #language-Gangte #language-Vaiphei #language-Kharam Naga #language-Paite Chin #language-Purum #language-Ralte #language-Tedim Chin #language-Thado Chin #language-Asho Chin #language-Sumtu Chin #language-Chinbon Chin #language-Daai Chin #language-Kaang Chin #language-Mün Chin #language-Maring Naga #language-Maram Naga #language-Rongmei Naga #language-Thangal Naga #language-Liangmai Naga #language-Mzieme Naga #language-Zeme Naga #language-Galo #language-Na #language-Tagin #language-Central Bai #language-Southern Bai #language-Mru #language-Drung #language-Raji #language-Raute #language-Rawat #language-Old Chinese #language-Waxianghua #language-Literary Chinese #language-Gan Chinese #language-Hakka Chinese #language-Xiang Chinese #language-Jinyu Chinese #language-Mandarin Chinese #language-Wutunhua #language-Wu Chinese #language-Yue Chinese #language-Min Dong Chinese #language-Pu-Xian Chinese #language-Min Bei Chinese #language-Min Zhong Chinese #language-Omaha-Ponca #language-Iowa-Oto #language-Ofo #language-Uni #language-Bouni #language-Puare #language-Rawo #language-Womo #language-Vanimo #language-Momina #language-Momuna #language-Humburi Senni Songhay #language-Koyraboro Senni Songhai #language-Tondi Songway Kiini #language-Dendi (Benin) #language-Koyra Chiini Songhay #language-Tadaksahak #language-Kaburi #language-Kokoda #language-Kemberano #language-Arandai #language-Dime #language-Aari #language-Gayil #language-Hamer-Banna #language-Karo (Ethiopia) #language-Uisai #language-Simeku #language-Naasioi #language-Daantanai' #language-Koromira #language-La'bi #language-Lomavren #language-Ngatik Men's Creole #language-Traveller Danish #language-Tavringer Romani #language-Traveller Norwegian #language-Shelta #language-Callawalla #language-Camtho #language-Suki #language-Gogodala #language-Ari #language-Waruna #language-Kwegu #language-Me'en #language-Mursi #language-Murle #language-Tennet #language-Didinga #language-Laarim #language-Cun #language-Hlai #language-E'ma Buyang #language-En #language-Langnian Buyang #language-Baha Buyang #language-Laha (Viet Nam) #language-A'ou #language-Red Gelao #language-Qau #language-Lachi #language-White Lachi #language-Lingao #language-Minz Zhuang #language-Nung (Viet Nam) #language-Tày Sa Pa #language-Lü #language-Tày Tac #language-Tai Pao #language-Nyaw #language-Tai Do #language-Tai Long #language-Khamyang #language-Turung #language-Tai Nüa #language-Tai Hongjin #language-Pa Di #language-Tai Thanh #language-Northeastern Thai #language-Yoy #language-Zuojiang Zhuang #language-Central Hongshuihe Zhuang #language-Eastern Hongshuihe Zhuang #language-Guibian Zhuang #language-Guibei Zhuang #language-Lianshan Zhuang #language-Liujiang Zhuang #language-Liuqian Zhuang #language-Qiubei Zhuang #language-Tay Khang #language-Ts'ün-Lao #language-Youjiang Zhuang #language-Yongnan Zhuang #language-Yongbei Zhuang #language-Mulam #language-Southern Dong #language-Cao Miao #language-Northern Dong #language-T'en #language-Ai-Cham #language-Mak (China) #language-Chadong #language-Maonan #language-Lakkia #language-Mararit #language-Assangori #language-Tama (Chad) #language-Ganggalida #language-Kayardild #language-Purepecha #language-Western Highland Purepecha #language-Taulil #language-Dadibi #language-Folopa #language-Highland Oaxaca Chontal #language-Lowland Oaxaca Chontal #language-Bunak #language-Sawila #language-Kui (Indonesia) #language-Kamang #language-Adang #language-Hamap #language-Kabola #language-Kaera #language-Tereweng #language-Nedebang #language-Fataluku #language-Oirata #language-Orya #language-Berik #language-Itik #language-Kwesten #language-Mander #language-Maremgi #language-Bonerif #language-Dabe #language-Jofotek-Bromnya #language-Keder #language-Vitou #language-Huehuetla Tepehua #language-Pisaflores Tepehua #language-Tlachichilco Tepehua #language-Yecuatla Totonac #language-Papantla Totonac #language-Coyutla Totonac #language-Highland Totonac #language-Xicotepec De Juárez Totonac #language-Tecpatlán Totonac #language-Upper Necaxa Totonac #language-Waimaha #language-Yurutí #language-Arapaso #language-Yahuna #language-Tama (Colombia) #language-Macaguaje #language-Udihe #language-Orok #language-Jurchen #language-Sibe #language-Oroqen #language-Kepkiriwát #language-Arikem #language-Karitiâna #language-Sateré-Mawé #language-Awetí #language-Kamayurá #language-Xetá #language-Chiripá #language-Paraguayan Guaraní #language-Western Bolivian Guaraní #language-Tapieté #language-Jorá #language-Yuqui #language-Nhengatu #language-Tupinambá #language-Cocama-Cocamilla #language-Omagua #language-Potiguára #language-Tupinikin #language-Xingú Asuriní #language-Amanayé #language-Anambé #language-Araweté #language-Tapirapé #language-Parakanã #language-Suruí Do Pará #language-Tocantins Asurini #language-Turiwára #language-Guajajára #language-Júma #language-Paranawát #language-Wiraféd #language-Tenharim #language-Apiaká #language-kgm #language-Kayabí #language-Amundava #language-Uru-Eu-Wau-Wau #language-Urubú-Kaapor #language-Wayampi #language-Suruí #language-Cinta Larga #language-Gavião Do Jiparaná #language-Kuruáya #language-Mundurukú #language-Puruborá #language-Karo (Brazil) #language-Urumi #language-Makuráp #language-Akuntsu #language-Tuparí #language-Jurúna #language-Xipaya #language-Maritsauá #language-Barikewa #language-Mouwase #language-Bolgarian #language-Tuvinian #language-Ainu (China) #language-West Yugur #language-Uighur #language-Northern Uzbek #language-Kirghiz #language-Kara-Kalpak #language-Pecheneg #language-Karachay-Balkar #language-Qashqa'i #language-slq #language-North Azerbaijani #language-South Azerbaijani #language-Giyug #language-Mawa (Nigeria) #language-Moksela #language-Pankararé #language-Rer Bare #language-Sentinel #language-Tremembé #language-Truká #language-Wakoná #language-Wasu #language-Weyto #language-Agavotaguerra #language-Aguano #language-Himarimã #language-Dek #language-Dungu #language-Esuma #language-Kaivi #language-Mala (Nigeria) #language-Nshi #language-ksa #language-Tumi #language-Vono #language-Sorsogon Ayta #language-Villa Viciosa Agta #language-Agariya #language-Nagarchal #language-Pardhan #language-Badeshi #language-Manangkari #language-Yugul #language-Alapmunte #language-Yalakalore #language-Wik-Keyangan #language-Pisabo #language-Wares #language-Morerebi #language-Tukumanféd #language-Ngurmbur #language-Bazigar #language-Camunic #language-Elymian #language-Eteocretan #language-Eteocypriot #language-Gail #language-Haitian Vodoun Culture Language #language-Illyrian #language-Kaimbé #language-Kapinawá #language-Karirí-Xocó #language-Katabaga #language-Koguryo #language-Lemnian #language-Minoan #language-North Picene #language-Numidian #language-Paekche #language-Pictish #language-Pijao #language-Polari #language-Quinqui #language-Raetic #language-Tartessian #language-Traveller Scottish #language-Uamué #language-Uru-Pa-In #language-Wakabunga #language-Liv #language-Livvi #language-Ludian #language-Kven Finnish #language-Mulgi #language-Eastern Mari #language-Western Mari #language-Komi-Zyrian #language-Komi-Permyak #language-Nenets #language-Forest Enets #language-Tundra Enets #language-Selkup #language-Panamint #language-Ute-Southern Paiute #language-Mono (USA) #language-Northern Paiute #language-Tubar #language-Mayo #language-Highland Puebla Nahuatl #language-Huaxcaleca Nahuatl #language-Northern Oaxaca Nahuatl #language-Ometepec Nahuatl #language-Pipil #language-Central Huasteca Nahuatl #language-Eastern Huasteca Nahuatl #language-Western Huasteca Nahuatl #language-Isthmus-Cosoleacaque Nahuatl #language-Isthmus-Pajapan Nahuatl #language-Isthmus-Mecayapan Nahuatl #language-Tabasco Nahuatl #language-Orizaba Nahuatl #language-Central Puebla Nahuatl #language-Santa María La Alta Nahuatl #language-Sierra Negra Nahuatl #language-Zacatlán-Ahuacatlán-Tepetzintla Nahuatl #language-Central Nahuatl #language-Classical Nahuatl #language-Morelos Nahuatl #language-Northern Puebla Nahuatl #language-Tetelcingo Nahuatl #language-Pochutec #language-Temascaltepec Nahuatl #language-Coatepec Nahuatl #language-Tlamacazapa Nahuatl #language-Michoacán Nahuatl #language-Eastern Durango Nahuatl #language-Western Durango Nahuatl #language-El Nayar Cora #language-Santa Teresa Cora #language-Central Tarahumara #language-Lowland Tarahumara #language-Northern Tarahumara #language-Southwestern Tarahumara #language-Southeastern Tarahumara #language-Tohono O'odham #language-Northern Tepehuan #language-Southeastern Tepehuan #language-Southwestern Tepehuan #language-Tepecano #language-Heiltsuk #language-Tuwari #language-Yawiyo #language-Walio #language-Pei #language-Moi (Indonesia) #language-Seget #language-Kalabra #language-Moraid #language-Marimanindji #language-Maringarr #language-Marti Ke #language-Maridjabin #language-Maridan #language-Mariyedi #language-Marriammu #language-Maranunggu #language-Ami #language-Manda (Australia) #language-Wilawila #language-Wunambal #language-Gambera #language-Kwini #language-Miwa #language-Unggumi #language-Worrorra #language-Umiida #language-Unggaranggu #language-Yawijibaya #language-Dagoman #language-Wardaman #language-Yangman #language-Bariji #language-Yareba #language-Yawa #language-Arin #language-Pumpokol #language-Changriwa #language-Mekmek #language-Biwat #language-Bun #language-Northern Yukaghir #language-Chuvantsy #language-Wappo #language-Ayoreo #language-Andoa #language-Cahuarano #language-Iquito #language-Aushiri #language-Záparo #language-Alumu-Tesu #language-Eastern Abnaki #language-Aasáx #language-Manide #language-Western Abnaki #language-Abkhazian #language-Abellen Ayta #language-Achinese #language-Mesopotamian Arabic #language-Atauran #language-Lidzonka #language-Adi #language-Northeast Pashai #language-Putukwam #language-Nanubae #language-Remontado Dumagat #language-Ainu (Japan) #language-Andajin #language-Algerian Jewish Sign Language #language-Tosk Albanian #language-Alaba-K’abeena #language-Amol #language-Anu-Hkongso Chin #language-Alor #language-Pahanan Agta #language-Ambul #language-Official Aramaic (700-300 BCE) #language-Aruá (Rodonia State) #language-Cishingini #language-Abishira #language-Atemble #language-Atong (Cameroon) #language-Avaric #language-Jair Awyu #language-Awun #language-Xârâgurè #language-Ayabadhu #language-Magbukun Ayta #language-Mai Brat #language-Bainouk-Gunyuño #language-Baluchi #language-Baga Pokur #language-Bunuba #language-Central Bikol #language-Babine #language-Bainouk-Gunyaamolo #language-Bai (South Sudan) #language-Belait #language-Bekati' #language-Panyi Bai #language-Gahri #language-Bangandu #language-Bo (Laos) #language-Balkan Gagauz Turkish #language-Bohtan Neo-Aramaic #language-Baloi #language-Bidyogo #language-Bedjond #language-Binukid #language-Northern Sorsoganon #language-Bekwel #language-Bote-Majhi #language-Somba-Siawari #language-Butmas-Tur #language-Bamako Sign Language #language-Bonjo #language-Borôro #language-Daakaka #language-Kaure #language-Bishnupriya #language-Bilakura #language-Wumboko #language-Bengkala Sign Language #language-Bodo (India) #language-Bilbil #language-Kati #language-Brem #language-Barein #language-Baniva #language-Baniwa #language-Tairaha #language-Birale #language-Binahari #language-Biao #language-Bidjara #language-Naami #language-Kɛlɛngaxo Bozo #language-Tsimané #language-Chachi #language-Tsucuba #language-Cacua #language-Cafundo Creole #language-Cinda-Regi-Tiyal #language-Centúúm #language-Chinook #language-Mari (Russia) #language-Chinook jargon #language-Chakavian #language-Chukot #language-Cakfem-Mushere #language-Chilcotin #language-Idu-Mishmi #language-Lautu Chin #language-Classical Mongolian #language-Michigamea #language-Mro-Khimi Chin #language-Northern Ping Chinese #language-Chenoua #language-Middle Cornish #language-Colorado #language-Cori #language-Jola-Kasa #language-Southern Ping Chinese #language-Croatia Sign Language #language-Southern Ohlone #language-Northern Ohlone #language-Siyin Chin #language-Coos #language-Thaiphum Chin #language-Chhintange #language-Northern Catanduanes Bikol #language-Moundadan Chetty #language-Chug #language-Huizhou Chinese #language-Knaanic #language-Bondum Dom Dogon #language-Deccan #language-West Goodenough #language-Dido #language-Delaware #language-Slave (Athapascan) #language-Southern Dagaare #language-Casiguran Dumagat Agta #language-Andaandi #language-Dogri (individual language) #language-Dhodia #language-Dhanwar (Nepal) #language-Kumiai #language-Dimli (individual language) #language-Diriku #language-Djadjawurrung #language-Djamindjung #language-Eastern Maroon Creole #language-Medefaidrin #language-Dama #language-Kemedzung #language-Dení #language-Dogri (macrolanguage) #language-C'Lela #language-Disa #language-Daur #language-Adithinngithigh #language-Tene Kan Dogon #language-Daatsʼíin #language-Uyajitaya #language-Middle Dutch (ca. 1050-1350) #language-Duli-Gey #language-Djabugay #language-Karenggapa #language-Teke-Ebo #language-Emilian #language-Standard Estonian #language-Modern Greek (1453-) #language-Emerillon #language-Eastern Minyag #language-Middle English (1100-1500) #language-Northwest Alaska Inupiatun #language-Central Yupik #language-Etchemin #language-Eton (Cameroon) #language-Fa d'Ambu #language-Faita #language-Paloor #language-Fanti #language-Southwestern Fars #language-West Albay Bikol #language-Tornedalen Finnish #language-Foau #language-Flaaitaal #language-Fanbak #language-Fernando Po Creole English #language-Middle French (ca. 1400-1600) #language-Eastern Frisian #language-Fortsenal #language-Fulah #language-Nigerian Fulfulde #language-Guarequena #language-Galolen #language-Gbaya (Central African Republic) #language-Karajarri #language-Gbanziri #language-Gagadu #language-Gabi-Gabi #language-Gadjerawang #language-Ghodoberi #language-Kungardutyi #language-Ywom #language-ut-Ma'in #language-Eviya #language-Gurr-goni #language-Gagu #language-Ghadamès #language-Ghulfan #language-Kuke #language-Kija #language-Gaɓogbo #language-Githabul #language-Hinukh #language-Green Gelao #language-Mulao #language-White Gelao #language-Gunditjmara #language-Magɨ (Madang Province) #language-ǂUngkue #language-Belning #language-Northwest Pashai #language-Garlali #language-Magɨyi #language-Middle High German (ca. 1050-1500) #language-Mgbolizhia #language-ǁGana #language-Gozarkhani #language-Guana (Brazil) #language-Ancient Greek (to 1453) #language-Taznatit #language-Nema #language-Swiss German #language-Aghu-Tharnggala #language-Gunwinggu #language-Guana (Paraguay) #language-Guanano #language-Pará Gavião #language-Gawwada #language-ǀGwi #language-Hamba #language-Serbo-Croatian #language-Herdé #language-Hemba #language-Haiǁom #language-Kerak #language-Hoyahoya #language-Tsoa #language-Hong Kong Sign Language #language-Matu Chin #language-Large Flowery Miao #language-Maek #language-Hmong Shua #language-ǁAni #language-Hovongan #language-Hawai'i Sign Language (HSL) #language-Hértevin #language-Middle Hittite #language-San Francisco Del Mar Huave #language-Hungana #language-San Mateo Del Mar Huave #language-San Dionisio Del Mar Huave #language-Sabu #language-Santa María Del Mar Huave #language-Islander Creole English #language-Indo-Portuguese #language-Keley-I Kallahan #language-Iha Based Pidgin #language-Bidhawal #language-Inuktitut #language-Iranun (Malaysia) #language-Iranun (Philippines) #language-Inga #language-Jungle Inga #language-Indonesian Sign Language #language-Inupiaq #language-Iresim #language-Izii #language-Jamamadí #language-Jakati #language-Badjiri #language-Jabutí #language-Jeri Kuo #language-Gwak #language-Bu (Kaduna State) #language-sTodsde #language-Guanyinqiao #language-Koro (India) #language-Amami Koniya Sign Language #language-Jogi #language-Jordanian Sign Language #language-Judeo-Arabic #language-Hupdë #language-Kachin #language-Kabiyè #language-Ngkâlmpw Kanum #language-Kachama-Ganjule #language-Kannada Kurumba #language-Kachhi #language-Karingani #language-Bädi Kanum #language-Khvarshi #language-Kele (Democratic Republic of Congo) #language-Karagas #language-Agob #language-Kirmanjki (individual language) #language-Khinalugh #language-Harijan Kinnauri #language-Kaikavian Literary Language #language-Kaeku #language-Gamilaraay #language-Tagakaulo #language-Migum #language-Majukayang Kalinga #language-Kwama #language-Karipúna Creole French #language-Khorasani Turkish #language-Konda #language-Koongo #language-Western Kanjobal #language-Kanamarí #language-Konkani (individual language) #language-Kung-Ekoka #language-Kodi #language-Kacipo-Bale Suri #language-Konkani (macrolanguage) #language-Kugama #language-Koy Sanjaq Surat #language-Eastern Krahn #language-Kinaray-A #language-Gbaya (Sudan) #language-Southern Kalinga #language-Krisa #language-Juǀʼhoan #language-Kuman (Papua New Guinea) #language-Tsakwambo #language-Kwa #language-Kwakiutl #language-Kofyar #language-Zayein Karen #language-Kanoé #language-Koro (Papua New Guinea) #language-Kalapuya #language-Kelon #language-Southern Subanen #language-Linear A #language-Lama Bai #language-Libon Bikol #language-Rmeet #language-Dũya #language-Lamma #language-Lezghian #language-Lingarak #language-T'apo #language-Mlahsö #language-Likila #language-Lika #language-Lingala #language-Liberian English #language-Yirandali #language-Kungkari #language-Pévé #language-South Lembata #language-Langobardic #language-Leningitij #language-Langam #language-Lorediakarkar #language-Lanima #language-Louisiana Creole #language-Loke #language-Laro #language-Burundian Sign Language #language-Lish #language-Late Middle Chinese #language-Thur #language-Luxembourgish #language-Luiseno #language-Lushai #language-Lushootseed #language-Lavi #language-Levuka #language-Lakurumau #language-Lyngngam #language-Mandingo #language-Ombamba #language-Maquiritari #language-Malaccan Creole Portuguese #language-Cameroon Mambila #language-Minanibai #language-Maguindanaon #language-Miriwoong #language-Mano #language-Mogofin #language-Middle Irish (900-1200) #language-Manda (Tanzania) #language-Mongol #language-Mócheno #language-Digaro-Mishmi #language-Uncoded languages #language-Makalero #language-Tu #language-Mahican #language-Malas #language-Kinamiging Manobo #language-Makasae #language-Malagasy #language-Motlav #language-Malfaxal #language-Malaynon #language-Mundat #language-Musar #language-Musak #language-Manikion #language-Innu #language-Malak Malak #language-Mapidian #language-Misima-Panaeati #language-Pano #language-Marino #language-Malay (macrolanguage) #language-Mono (Solomon Islands) #language-Mator #language-Multiple languages #language-Murrinh-Patha #language-Labo #language-Marwari #language-Miju-Mishmi #language-Nigeria Mambila #language-Inapang #language-Ngan'gityemerri #language-Ca̱hungwa̱rya̱ #language-Ngarrindjeri #language-Ngbinda #language-Ngarinyman #language-South Ndebele #language-Na-kara #language-Chothe Naga #language-North Ndebele #language-Nadruvian #language-Nyenkha #language-Neo-Hittite #language-Nepali (macrolanguage) #language-Newari #language-Ayiwo #language-Nafaanra #language-Mfumte #language-Ngbaka #language-Dalabon #language-Ngurimi #language-Engdewu #language-Kriang #language-Guerrero Nahuatl #language-Nakame #language-Gilyak #language-Nisa #language-Nyishi #language-Khoibu Naga #language-Ngul #language-Nahali #language-Tangkhul Naga (India) #language-Manangba #language-ǃXóõ #language-Moyon Naga #language-Nyangga #language-Nepali (individual language) #language-Noipx #language-Southern Nago #language-Kyan-Karyaw Naga #language-Jèrriais #language-Northern Kalapuya #language-Lower Nossob #language-Northwestern Nisu #language-Tase Naga #language-Ngantangarra #language-Ikoma-Nata-Isenye #language-Tangkhul Naga (Myanmar) #language-Yuanga #language-Anong #language-Classical Newari #language-Ngayawung #language-Middle Newar #language-Nottoway-Meherrin #language-Koki Naga #language-Nyikina #language-Nyungar #language-Nanga Dama Dogon #language-Old Avar #language-Occitan (post 1500) #language-Old Cham #language-Old Hittite #language-Old Hungarian #language-Ontong Java #language-Kobo #language-Koresh-e Rostam #language-Middle Korean (10th-16th cent.) #language-Old Korean (3rd-9th cent.) #language-Omok #language-Old Manipuri #language-Onin Based Pidgin #language-Ong #language-Opata #language-Oriya (macrolanguage) #language-Adivasi Oriya #language-Old Sundanese #language-Ottoman Turkish (1500-1928) #language-Old Tibetan #language-Tagargrent #language-Oune #language-Old Uighur #language-Paumarí #language-Panjabi #language-Pakaásnovos #language-E'ñapa Woromaipu #language-Puebla Mazatec #language-Pyu (Papua New Guinea) #language-Parenga #language-Kayan #language-Northeastern Pomo #language-Kunja #language-Iranian Persian #language-Pere #language-Pfaelzisch #language-Sudanese Creole Arabic #language-Gāndhārī #language-Primitive Irish #language-Phalura #language-Pahari-Potwari #language-Piratapuyo #language-Pileni #language-Ardhamāgadhī Prākrit #language-Pankhu #language-plj #language-San Marcos Tlacoyalco Popoloca #language-Māhārāṣṭri Prākrit #language-Pamlico #language-Lingua Franca #language-Paynamar #language-Pangu #language-Banyjima #language-Pwapwâ #language-Prussian #language-Parauk #language-Prasuni #language-Old Provençal (to 1500) #language-Phai #language-Iranian Sign Language #language-Southwest Pashai #language-Southeast Pashai #language-Pauserna #language-Sauraseni Prākrit #language-Pindiini #language-Puoc #language-Pushto #language-Pyu (Myanmar) #language-Quechua #language-Chimborazo Highland Quichua #language-Yanahuanca Pasco Quechua #language-Kuman (Russia) #language-Kwalhioqua-Tlatskanai #language-Quiripi #language-Canela #language-Rarotongan #language-Rapa #language-Northern Bontok #language-Miraya Bikol #language-Remo #language-Retta #language-Roria #language-Tarifit #language-Riang Lang #language-Ritharrngu #language-Carpathian Romani #language-Sinte Romani #language-Romany #language-Arritinngithigh #language-Romano-Serbian #language-Yurats #language-Macedo-Romanian #language-Karuwali #language-Rāziḥī #language-Chabu #language-Sileibi #language-Sri Lankan Creole Malay #language-Hyolmo #language-Sha #language-Sicel #language-Shabak #language-Surubu #language-Cebaara Senoufo #language-Suarmin #language-Senara Sénoufo #language-Small Flowery Miao #language-Old Irish (to 900) #language-Mag-antsi Ayta #language-Suga #language-Singpho #language-Shahrudi #language-Shehri #language-Tachawit #language-Akkala Sami #language-Sajau Basap #language-Kildin Sami #language-Pite Sami #language-Kemi Sami #language-Sajalong #language-Ter Sami #language-Ume Sami #language-Sakirabiá #language-Sakalava Malagasy #language-Kutong #language-Sissala #language-Ma'ya #language-Southern Sami #language-Northern Sami #language-Lule Sami #language-Inari Sami #language-Skolt Sami #language-Somray #language-Bau Bidayuh #language-South West Bay #language-Songomeno #language-Songo #language-Swo #language-Sian #language-Loreto-Ucayali Spanish #language-Siculo Arabic #language-Kufr Qassem Sign Language (KQSL) #language-Sara #language-Southern Sorsoganon #language-So'a #language-Shark Bay #language-Settla #language-Saterfriesisch #language-Tirmaga-Chai Suri #language-Skalvian #language-Swahili (macrolanguage) #language-Swahili (individual language) #language-Sawknah #language-Sicanian #language-Shuhi #language-Southern Kalapuya #language-Selian #language-Samre #language-Sorothaptic #language-Tabassaran #language-Dharawal #language-Datooga #language-Tawr Chin #language-Tandroy-Mahafaly Malagasy #language-Teke-Tege #language-Tereno #language-Tewa (USA) #language-Tanaina #language-Kuuk Thaayorre #language-Aheu #language-Tidikelt Tamazight #language-Tiéfo #language-Tjungundji #language-Temacine Tamazight #language-Tjupany #language-Talodi #language-Filomena Mata-Coahuitlán Totonac #language-Sou Nama #language-Katbol #language-Tamashek #language-Tembo (Motembo) #language-Ménik #language-Ten'edn #language-tpw #language-Tembé #language-Western Totonac #language-Tarao Naga #language-Sediq #language-Tsishingini #language-Long Wat #language-Tewa (Indonesia) #language-Northern Tiwa #language-Kyanga #language-Central Atlas Tamazight #language-Buhi'non Bikol #language-Tanjijili #language-Muak Sa-aak #language-Meriam Mir #language-Morrobalama #language-Undetermined #language-Kurnai #language-Urali #language-us-Saare #language-ut-Hun #language-Sekele #language-Valman #language-Southwestern Bontok #language-Korlai Creole Portuguese #language-Vlaams #language-Martuyhunira #language-Barbaram #language-Mainfränkisch #language-Vano #language-Vinmavis #language-Awa (China) #language-Walla Walla #language-Wagiman #language-Wara #language-Waigali #language-West Bengal Sign Language #language-Warnman #language-Yanomámi #language-Wadjabangayi #language-Kiunum #language-Westphalien #language-Rawngtu Chin #language-Wejewa #language-Wangkangurru #language-Sou Upaa #language-Wahau Kenyah #language-Wik Ngathan #language-Keerray-Woorroong #language-Wangkayutyuru #language-Wailapa #language-Western Minyag #language-Mokati #language-Kuwema #language-Wè Northern #language-Waluwarra #language-Warungu #language-Gugu Warra #language-Wae Rana #language-Waray (Australia) #language-Wusi #language-Owenia #language-Wetamut #language-Wangaaybuwan-Ngiyambaa #language-Ararandewára #language-ǀXam #language-Aquitanian #language-Kamas #language-Lower Burdekin #language-Bindal #language-Batjala #language-Cumbric #language-Chorasmian #language-Curonian #language-Darkinyung #language-Dharuk #language-Eblan #language-ǁXegwi #language-Epi-Olmec #language-Gabrielino-Fernandeño #language-Garingbal #language-Galindan #language-Harami #language-Hunnic #language-Middle Khmer (1400 to 1850 CE) #language-Indus Valley Language #language-Minjungbal #language-Northern Nago #language-Kenyan Sign Language #language-Kachok #language-Loup B #language-Ligurian (Ancient) #language-Liburnian #language-Alanic #language-Median #language-Kugu-Muminh #language-Ancient Macedonian #language-Manichaean Middle Persian #language-Kanakanabu #language-Middle Mongolian #language-Ngoni (Tanzania) #language-Nganakarti #language-Ngoni (Mozambique) #language-Narragansett #language-Nukunul #language-Nyiyaparli #language-Komo (Sudan) #language-Northeastern Tasmanian #language-Oyster Bay Tasmanian #language-Southeast Tasmanian #language-North Midlands Tasmanian #language-Port Sorell Tasmanian #language-Puyo-Paekche #language-Northern Tasmanian #language-Northwestern Tasmanian #language-Southwestern Tasmanian #language-Puyo #language-Bruny Island Tasmanian #language-Kreye #language-Minang #language-Krikati-Timbira #language-Armazic #language-Aranama-Tamique #language-Sabaean #language-Sambal #language-Scythian #language-Sudovian #language-Early Tripuri #language-Tacahua Mixtec #language-Vandalic #language-Written Oirat #language-Boro (Ghana) #language-Ke'o #language-Zemgalian #language-Ancient Zapotec #language-Yaka (Democratic Republic of Congo) #language-Yakama #language-Yuwana #language-Yakha #language-Yabaâna #language-Yela #language-Yiningayi #language-Yolŋu Sign Language #language-Yan-nhaŋu Sign Language #language-Yidiny #language-Riang Lai #language-Kathu #language-Nyâlayu #language-Yokuts #language-Yongkom #language-Yirrk-Mel #language-Yerong #language-Yaroamë #language-Yassic #language-Myanmar Sign Language #language-Sirenik Yupik #language-Talu #language-Tanglang #language-Yatay #language-Yucateco #language-Yug #language-Yuracare #language-Mayawali #language-Yir Yoront #language-Miahuatlán Zapotec #language-Balaibalan #language-Bu (Bauchi State) #language-Zhuang #language-zkb #language-Khorezmian #language-Kanan #language-Kott #language-Krevinian #language-Khazar #language-Matngala #language-Zande (individual language) #language-Kara (Korea) #language-Zerenkel #language-Kaskean #language-Quioquitani-Quierí Zapotec #language-No linguistic content #language-Zyphe Chin #license-cc-by-4.0 #region-us \n",
"# Description\nDataset listing 27,328 languages and dialects (also includes macrolanguage names). \nFor each language, either the ISO 639 code, the Glottolog code or both are provided.",
"# Columns\n- 'English_Name': Language name in English (e.g. '\"French\"').\n- 'Native_Name': If value is not '0', corresponds to the name of the language by native speakers (e.g. '\"Français\"') which may have been found in Wikipedia's 'nativename' field.\n- 'Glottocode': The language tag in the Glottolog convention (e.g. 'stan1290').\n- 'near_ISO6393': the ISO 639-3 code closest to the Glottolog convention (e.g. 'fra') This information comes from Glottolog and may therefore be incomplete compared with column '639-3' from ISO.\n- '639-3': The language tag in the ISO 639-3 convention (e.g. 'fra').\n- '639-2_B': The language tag in the ISO 639-2_B (B for bibliographic) convention (e.g. 'fre').\n- '639-2_T': The language tag in the ISO 639-2_T (T for terminological) convention (e.g. 'fra').\n- '639-1': The language tag in the ISO 639-1 convention (e.g. 'fr').\n- 'Scope': If value is not '0', 'I' for an individual language (e.g. \"French\"), 'M' for a macrolanguage, 'S' for special i.e non-language codes (e.g. \"und\" for Undetermined)).\n- 'Language_Type': If value is not '0', 'A' for ancient language that went extinct long ago (e.g. 'got' for Gothic), 'C' for constructed i.e artificial languages, excluding programming languages (e.g. 'epo' for Esperanto), 'E' for extinct i.e. language that went extinct recently (e.g. 'rbp' for Barababaraba), 'H' for historical i.e. extinct language distinct from modern languages that descended from it (e.g. 'ofs' for Old Frisian), 'L' for living i.e. currently spoken language (e.g. 'fra' for French), 'S' for special i.e. non-language codes (e.g. 'und' for Undetermined).\n- '#L1_Speakers': Indicates a (rounded) estimate of the number of speakers (L1) per language; the estimate comes from Writing System and Speaker Metadata for 2,800+ Language Varieties."
] | [
51334,
43,
601
] | [
"passage: ",
"passage: TAGS\n#size_categories-1K<n<10K #language-Afade #language-Pará Arára #language-Afar #language-Aka-Bea #language-Abon #language-Abaza #language-Pal #language-Aneme Wake #language-Abui #language-Aka-Cari #language-Aka-Kora #language-Akar-Bale #language-Achang #language-Achi #language-Achumawi #language-Adele #language-Adonara #language-Adnyamathanha #language-Adyghe #language-Haeke #language-Aer #language-Ambakich #language-Amele #language-Andai #language-Akrukay #language-Defaka #language-Eloyi #language-Obokuitai #language-Agatu #language-Angal #language-Angor #language-Ngelima #language-Fembe #language-Tainae #language-Aghem #language-Aguaruna #language-Kahua #language-Aghul #language-Qimant #language-Ahom #language-Ake #language-Aimele #language-Aiton #language-Aka-Jeru #language-Akkadian #language-Aklanon #language-Aka-Bo #language-Siwu #language-Akhvakh #language-Aka-Kede #language-Aka-Kol #language-Alabama #language-Alago #language-Aleut #language-Alege #language-Algonquin #language-Southern Altai #language-Alur #language-Yanesha' #language-Amis #language-Amdang #language-Guerrero Amuzgo #language-Ambelau #language-Andaqui #language-Nend #language-Andi #language-Obolo #language-Andoque #language-Denya #language-Anyin #language-Pemon #language-Angoram #language-Anindilyakwa #language-Mufian #language-Taikat #language-Atorada #language-Uab Meto #language-Apinayé #language-A-Pucikwar #language-Apatani #language-Western Apache #language-Safeyoka #language-Archi #language-Atohwaim #language-Atakapa #language-Angaité #language-Aragonese #language-Arhuaco #language-Arikara #language-Arikapú #language-Arabela #language-Arapaho #language-Arawak #language-Assiniboine #language-Casuarina Coast Asmat #language-Assamese #language-Ipulo #language-Asturian #language-Muratayak #language-Zaiwa #language-Atikamekw #language-Aralle-Tabulahan #language-Reel #language-Northern Altai #language-Arutani #language-Waorani #language-Aguna #language-Aushi #language-Heyo #language-Makayam #language-Anus #language-Aurá #language-Awiyaana #language-Avatime #language-Avá-Canoeiro #language-Awadhi #language-Mato Grosso Arára #language-Ginyanga #language-Aymara #language-Azerbaijani #language-Bashkir #language-Bambara #language-Balinese #language-Bantawa #language-Vengo #language-Barama #language-Babanki #language-Bats #language-Uneapa #language-Bamali #language-Girawa #language-Baba #language-Bannoni #language-Kaluli #language-Bench #language-Budukh #language-Baldemu #language-Bahnar #language-Bokoto #language-Oroko #language-Bodo Parja #language-Baham #language-Budong-Budong #language-Iceve-Maci #language-Beja #language-Belarusian #language-Bengali #language-Blagar #language-Betawi #language-Bari #language-Pauri Bareli #language-Betaf #language-Bofi #language-Blafe #language-Mmen #language-Badaga #language-Balti #language-Bantayanon #language-Bagheli #language-Gwamhi-Wuri #language-Haryanvi #language-Rathwi Bareli #language-Bagri #language-Bhatri #language-Bhili #language-Bhojpuri #language-Bima #language-Buwal #language-Biak #language-Bhele #language-Bissa #language-Bile #language-Nai #language-Bila #language-Berinomo #language-Southern Birifor #language-Budza #language-Burji #language-Binumarien #language-Baruga #language-Beeke #language-Pande #language-Buhid #language-Bekwarra #language-Bokyi #language-Bolango #language-Buol #language-Biloxi #language-Southern Catanduanes Bikol #language-Baluan-Pam #language-Blang #language-Tai Dam #language-Notre #language-Balantak #language-Lame #language-Kein #language-Bagirmi #language-Bomu #language-Muinane #language-Bookan #language-Masiwang #language-Benga #language-Bangi #language-Bunun #language-Bintulu #language-Bora #language-Boma #language-Anjam #language-Bole #language-Berom #language-Bosnian #language-Buamu #language-Bauni #language-Botlikh #language-Orowe #language-Dzao Min #language-Barrow Point #language-Palya Bareli #language-Bilba #language-Baima #language-Bandial #language-Biritai #language-Bamukumbit #language-Koro Wachi #language-Baangi #language-Breton #language-Bira #language-Brahui #language-Brokkat #language-Abinomn #language-Bassari #language-Wushi #language-Bashkardi #language-Bangwinji #language-Basa-Gumna #language-Barasana-Eduria #language-Bassa #language-Yangkam #language-Bata #language-Gamo-Ningi #language-Ratagnon #language-Rinconada Bikol #language-Batak Simalungun #language-Bete-Bendi #language-Batu #language-Bateri #language-Batak Karo #language-Bushi #language-Ntcham #language-Beothuk #language-Buginese #language-Bulgarian #language-Terei #language-Budu #language-Baeggu #language-Belanda Viri #language-Baan #language-Bolgo #language-Bwe Karen #language-Bafaw-Balong #language-Bwa #language-Cwi Bwamu #language-Bebil #language-Bhujel #language-Burak #language-Medumba #language-Qaqet #language-Andio #language-Bribri #language-Mapos Buang #language-Chuj #language-Caddo #language-Nivaclé #language-Kaqchikel #language-Carolinian #language-Chipaya #language-Catalan #language-Chiquitano #language-Cayuga #language-Carapana #language-Carijona #language-Chimila #language-Chayahuita #language-Candoshi-Shapra #language-Carabayo #language-Chamicuro #language-Chopi #language-Atsam #language-Chakma #language-Choni #language-Chenchu #language-Chiru #language-Chodri #language-Chepang #language-Lower Chehalis #language-Cebuano #language-Chamacoco #language-Czech #language-Cara #language-Chamorro #language-Chibcha #language-Catawba #language-Chechen #language-Chagatai #language-Chuukese #language-Cahuilla #language-Choctaw #language-Chipewyan #language-Cherokee #language-Cholón #language-Chuvash #language-Chuwabu #language-Cheyenne #language-Cia-Cia #language-Chickasaw #language-Chinali #language-Chitkuli Kinnauri #language-Cimbrian #language-Upper Chehalis #language-Chamalal #language-Chokwe #language-Shor #language-Cibak #language-Koasati #language-Kavalan #language-Chulym #language-Cerma #language-Changthang #language-Northern Qiang #language-Hakha Chin #language-Asháninka #language-Chung #language-Montenegrin #language-Chicomuceltec #language-Koreguaje #language-Chong #language-Comanche #language-Cofán #language-Comox #language-Coptic #language-Cornish #language-Corsican #language-Caquinte #language-Wamey #language-Nanti #language-Capiznon #language-Lonwolwol #language-Coeur d'Alene #language-Cree #language-Crimean Tatar #language-Plains Cree #language-Moose Cree #language-Crow #language-Carolina Algonquian #language-Chaura #language-Carrier #language-Cruzeño #language-Kashubian #language-Swampy Cree #language-Chittagonian #language-Chitimacha #language-Cubeo #language-Mashco Piro #language-Cumanagoto #language-Cupeño #language-Tai Ya #language-Kwere #language-Welsh #language-Dangaléat #language-Dagbani #language-Gwahatike #language-Dakota #language-Danish #language-Dargwa #language-Bangime #language-Dadiya #language-Dibiyaso #language-Dongotono #language-Dagik #language-Dehwari #language-Dem #language-Deori #language-Desano #language-German #language-Domung #language-Dogrib #language-Dogoso #language-Dhundari #language-Dhimal #language-Zemba #language-Dia #language-Digo #language-Dilling #language-Dinka #language-Dibo #language-Dimasa #language-Ding #language-Zarma #language-Jawoyn #language-Jangkang #language-Dolgan #language-Dahalik #language-Dalmatian #language-Gavak #language-Dameli #language-East Damar #language-Demta #language-Dungan #language-Dan #language-Dengka #language-Danau #language-Western Dani #language-Dom #language-Domu #language-Bussa #language-Minderico #language-Darmiya #language-Paakantyi #language-West Damar #language-Rukai #language-Lower Sorbian #language-Ditidaht #language-Dumun #language-Jola-Fonyi #language-Dyula #language-Tunzu #language-Eastern Bontok #language-Ebrié #language-Embu #language-E #language-Efik #language-Eggon #language-Askopan #language-Ekari #language-Koti #language-Yace #language-Elepi #language-Nding #language-Mamulique #language-Erromintxela #language-Apali #language-Enlhet #language-Engenni #language-Enxet #language-Eravallan #language-Ogea #language-Horpa #language-Eritai #language-Ese Ejja #language-Esselen #language-Central Siberian Yupik #language-Estonian #language-Eskayan #language-Eten #language-Basque #language-Even #language-Uvbie #language-Evenki #language-Ewe #language-Extremaduran #language-Keiyo #language-Fasu #language-Wagi #language-Faroese #language-Persian #language-Foia Foia #language-Fongoro #language-Nobiin #language-Faifi #language-Fijian #language-Filipino #language-Finnish #language-Fipa #language-Firan #language-Kirya-Konzəl #language-Fania #language-Fon #language-Fas #language-French #language-Fordata #language-Frankish #language-Pulaar #language-Friulian #language-Furu #language-Fur #language-Fwe #language-Ga #language-Gagauz #language-Alekano #language-Gamkonora #language-Gants #language-Nobonob #language-Gayo #language-Gaddi #language-Garhwali #language-Zoroastrian Dari #language-Mali #language-Galice #language-Gurdjar #language-Dirasha #language-Laal #language-Umanakaina #language-Wipi #language-Geruma #language-Kire #language-Gebe #language-Gen #language-Gera #language-Garre #language-Enya #language-Patpatar #language-Kungarakany #language-Ghanongga #language-Gidar #language-Gilbertese #language-Gitxsan #language-Gujari #language-Kok-Nar #language-Nanai #language-Irish #language-Galician #language-Gilaki #language-Manx #language-Glavda #language-Gula'alaa #language-Kaansa #language-Ngangam #language-Guntai #language-Gongduk #language-Gogo #language-Gobasi #language-Gondi #language-Gorontalo #language-Goo #language-Guiqiong #language-Grebo #language-Gbiri-Niragu #language-Guarani #language-Garo #language-Shiki #language-Wayuu #language-Guahibo #language-Eastern Bolivian Guaraní #language-Gujarati #language-Mbyá Guaraní #language-Guayabero #language-Aché #language-Farefare #language-Yanomamö #language-Gun #language-Gusii #language-Duwet #language-Guajá #language-Gulay #language-Gawri #language-Gweno #language-Gwichʼin #language-Gwere #language-Gyalsumdo #language-Guarayu #language-Ganza #language-Haida #language-Hajong #language-Hangaza #language-Ha #language-Harari #language-Haisla #language-Hausa #language-Havu #language-Hawaiian #language-Haya #language-Huba #language-Heiban #language-Huichol #language-Hebrew #language-Hehe #language-Herero #language-Hoia Hoia #language-Hidatsa #language-Pamosu #language-Hinduri #language-Hiligaynon #language-Hittite #language-Hunde #language-Halbi #language-Hlersu #language-Hmong #language-Hamtai #language-Chhattisgarhi #language-Hani #language-Hanunoo #language-Ho #language-Horom #language-Holikachuk #language-Holu #language-Holoholo #language-Hopi #language-Hote #language-Hrangkhol #language-Hruso #language-Croatian #language-Upper Sorbian #language-Minica Huitoto #language-Hadza #language-Huilliche #language-Hungarian #language-Hupa #language-Huastec #language-Hukumina #language-Nüpode Huitoto #language-Hunzib #language-Armenian #language-Iaai #language-Iatmul #language-Iban #language-Ibibio #language-Ibaloi #language-Agoi #language-Igbo #language-Idon #language-Idoma #language-Kanggape #language-Iha #language-Izon #language-Kalabari #language-Ik #language-Ikizu #language-Ila #language-Ili Turki #language-Anamgura #language-Miluk #language-Milyan #language-Indonesian #language-Ingush #language-Inor #language-Irarutu #language-Rigwe #language-Iraqw #language-Irula #language-Kamberau #language-Esan #language-Nkem-Nkum #language-Ishkashimi #language-Icelandic #language-Isanzu #language-Istriot #language-Italian #language-Itelmen #language-Itonama #language-Iteri #language-Iu Mien #language-Ivatan #language-Iwur #language-Sepik Iwam #language-Ixcatec #language-Mesaka #language-Ingrian #language-Izere #language-Hyam #language-Yabem #language-Yalahatan #language-Javanese #language-Nafusi #language-Jukun Takum #language-Krymchak #language-Jadgali #language-Jebero #language-Yelmek #language-Manem #language-Ngbee #language-Ngomba #language-Tol #language-Jingulu #language-Jiamao #language-Jita #language-Shuar #language-Labir #language-Ngile #language-Dima #language-Zumbun #language-Jumli #language-Janji #language-Jowulu #language-Japanese #language-Jaqaru #language-Jarai #language-Wapan #language-Juang #language-Jiba #language-Jwira-Pepesa #language-Kabyle #language-Adara #language-Jju #language-Bezhta #language-Kashmiri #language-Georgian #language-Kanuri #language-Kazakh #language-Kabardian #language-Kari #language-Kafa #language-Kabutra #language-Duhwa #language-Khanty #language-Tyap #language-Kalanga #language-Nubi #language-Kamo #language-Katla #language-Kaian #language-Kabwari #language-Korandje #language-Makonde #language-Tem #language-Numèè #language-Kunda #language-Karaim #language-Kuy #language-Kam #language-Kerewe #language-Tese #language-Keak #language-Kenyang #language-Ket #language-Kanikkaran #language-Koya #language-Kinnauri #language-Khunsari #language-Korwa #language-Korku #language-Kanjari #language-Kumaoni #language-Komering #language-Kusunda #language-Kaiwá #language-Kaingang #language-Somyev #language-Kobol #language-Karas #language-Khasi #language-Korowai #language-Lusi #language-Khmer #language-Kharia #language-Khamti #language-Koalib #language-Kikuyu #language-Kariya #language-Kiowa #language-Kimbu #language-Kirikiri #language-Khmu #language-Khakas #language-Highland Konjo #language-Kháng #language-Kunjen #language-Kashaya #language-Ramopa #language-Kinuku #language-Khün #language-Kokota #language-Kiong #language-Giiwo #language-Koi #language-Kangean #language-Kaska #language-Kiliwa #language-Kendeje #language-Khalaj #language-Rumu #language-Khaling #language-Kalasha #language-Klao #language-Kalao #language-Konni #language-Kanufi #language-Kwanja #language-Tabo #language-Kendayan #language-Kalamsé #language-Komi #language-Kongo #language-Waube #language-Korean #language-Lagwan #language-Koyukon #language-Kutto #language-Kpelle #language-Komba #language-Kapingamarangi #language-Karajá #language-Koho #language-Tehit #language-Kafoa #language-Koryak #language-Kupsabiny #language-Mum #language-Khe #language-Kyenele #language-Kaonde #language-Kimré #language-Seroa #language-Okolod #language-Panará #language-Kurama #language-Karelian #language-Kurukh #language-Kryts #language-Shambala #language-Kansa #language-Kumba #language-Kaba #language-Borong #language-S'gaw Karen #language-Nubri #language-Kurti #language-Kwinsu #language-Kuria #language-Kumyk #language-Kunama #language-Kusaal #language-Kutenai #language-Upper Kuskokwim #language-Kunza #language-Bagvalal #language-Kalabakan #language-Kabalai #language-Kayaw #language-Kerinci #language-Wersing #language-Kwerba #language-Kwara'ae #language-Kowiai #language-Kwangali #language-Kwese #language-Kwadi #language-Keningau Murut #language-Kuvi #language-Kayagar #language-Rapoisi #language-Kayeli #language-Kais #language-Karang #language-Lacandon #language-Lambya #language-Lamba #language-Laru #language-Lao #language-Qabiao #language-Latvian #language-Aribwatsa #language-Lak #language-Tinani #language-Ladakhi #language-Central Bontok #language-Wampar #language-Lardil #language-Loncong #language-Lisela #language-Luhu #language-Luri #language-Lemoro #language-Kaan #language-Loo #language-Tso #language-Lala-Bisa #language-Leco #language-Lendu #language-Lyélé #language-Lelemi #language-Lenje #language-Lengola #language-Lese #language-Lesing-Gelimi #language-Luang #language-Lemolang #language-Logba #language-Pahi #language-Lahu #language-Limbu #language-Lihir #language-Ligurian #language-Lillooet #language-Lisu #language-Lithuanian #language-Col #language-Laiyolo #language-Lakha #language-Laki #language-Remun #language-Khayo #language-Päri #language-Lakota #language-Lokoya #language-Ladin #language-Lole #language-Lilau #language-North Efate #language-Lau #language-Limilngan #language-Lumun #language-Lamkang #language-Lombard #language-Limbum #language-Lanoh #language-Longuda #language-Loloda #language-Lobi #language-Saluan #language-Logol #language-Loko #language-Mongo #language-Malawi Lomwe #language-Lopa #language-Otuho #language-Lozi #language-Lipo #language-Lopit #language-Marachi #language-Lashi #language-Aruop #language-Latgalian #language-Luba-Katanga #language-Lunda #language-Lumbu #language-Lwalu #language-Luyana #language-Litzlitz #language-Laz #language-Madurese #language-Magahi #language-Marshallese #language-Maithili #language-Mam #language-Marathi #language-Mampruli #language-Maxakalí #language-Macaguán #language-Mbula-Bwazza #language-Memoni #language-Bitur #language-Matsés #language-Mvanip #language-Mbunda #language-Moksha #language-Mangbetu #language-Mbole #language-Mbere #language-Ikobi #language-Megam #language-Meyah #language-Meru #language-Maaka #language-Menominee #language-Naki #language-Wandala #language-Mbe #language-Marrithiyel #language-Moru #language-Maklew #language-Mpumpong #language-Abureni #language-Malila #language-Mambwe-Lungu #language-Mailu #language-Matengo #language-Matumbi #language-Mbugu #language-Ma'di #language-Mauwake #language-Mandan #language-Mbukushu #language-Mi'kmaq #language-Mandaic #language-Minangkabau #language-Akoye #language-Muskum #language-Miship #language-Karbi #language-Mbre #language-Mal Paharia #language-Siliput #language-Macedonian #language-Dhatki #language-Mokilese #language-Byep #language-Mingang Doso #language-Moikodi #language-Bay Miwok #language-Cao Lan #language-Mal #language-Ilwana #language-Bargam #language-Vame #language-Masalit #language-Maltese #language-Moloko #language-Mangga Buang #language-Siawi #language-Malalamai #language-Miriti #language-Emae #language-Muna #language-Manchu #language-Mondé #language-Munji #language-Mansi #language-Mon #language-Mohawk #language-Mboi #language-Morori #language-Mangue #language-Moro #language-Barí #language-Molima #language-Mpoto #language-Majang #language-Marba #language-Maung #language-Mpi #language-Manipa #language-West Makian #language-Maricopa #language-Elseng #language-Mising #language-Mangareva #language-Mandaya #language-Mekwei #language-Mansaka #language-Caac #language-Aruamu #language-Mualang #language-Moskona #language-Montol #language-Muong #language-Mewari #language-Nabi #language-Mundang #language-Musgu #language-Nyong #language-Malvi #language-Muthuvan #language-Duri #language-Massep #language-Marfa #language-Juwal #language-Mirandese #language-Sar #language-Mentawai #language-Mele-Fila #language-Malgbe #language-Meramera #language-Mbowe #language-Burmese #language-Mbay #language-Myene #language-Bambassi #language-Manta #language-Makah #language-Pirahã #language-Erzya #language-Macuna #language-Mumuye #language-Mazanderani #language-Movima #language-Mintil #language-Deg #language-Nakanai #language-Neapolitan #language-Khoekhoe #language-Navajo #language-Ndoe #language-Nkukoli #language-Nnam #language-Iyo #language-Nisga'a #language-Natchez #language-Nde-Nsele-Nta #language-Ndengereko #language-Ndali #language-Ndo #language-Lutos #language-Negidal #language-Ná-Meo #language-Yahadian #language-Nyaheun #language-Nez Perce #language-Dhao #language-Ahwai #language-Nǁng #language-Lomwe #language-Ngwo #language-Ngulu #language-Nagumi #language-Tibea #language-Beng #language-Nias #language-Niellim #language-Ngalakgan #language-Nii #language-Southern Nicobarese #language-Ninzo #language-Nganasan #language-Nimboran #language-Niuean #language-Hema #language-Ngiti #language-Nkoya #language-Koireng #language-Nukuoro #language-North Asmat #language-Nalca #language-Dutch #language-Nyali #language-Big Nambas #language-Ngam #language-Kwasio #language-Namakura #language-Nambya #language-Nimbari #language-Namuyi #language-Nawdm #language-Nande #language-Ngiemboon #language-Ngindo #language-Dwang #language-Northern Thai #language-Nimadi #language-Nogai #language-Nonuya #language-Nooksack #language-Nomlaki #language-Norwegian #language-Nomatsiguenga #language-Nyambo #language-Noy #language-Nara #language-Narom #language-Norn #language-Nsenga #language-Naskapi #language-Nsongo #language-Nisenan #language-Natioro #language-Delo #language-Mantsi #language-Nuu-chah-nulth #language-Nuer #language-Nunggubuyu #language-Nyokon #language-Nawaru #language-Naxi #language-Ninggerum #language-Nyanga #language-Nyaneka #language-Nyoro #language-Nyang'i #language-Nyungwe #language-Njebi #language-Nzadi #language-Nzakambay #language-Oroch #language-Obispeño #language-Ocaina #language-Ogbia #language-Khana #language-Ogbronuagum #language-Okanagan #language-Okodia #language-Oko-Juwoi #language-Oku #language-Olrat #language-Mochica #language-Utarmbung #language-Omotik #language-Ona #language-Oneida #language-Onondaga #language-Sartang #language-Oksapmin #language-Orejón #language-Oromo #language-Odia #language-Osage #language-Ososo #language-Ossetian #language-Oti #language-Otoro #language-Pagibete #language-Pangasinan #language-Pe #language-Parya #language-Palauan #language-Pankararú #language-Páez #language-Paraujano #language-Parkwa #language-Badyara #language-Pangwa #language-Pnar #language-Pear #language-Bouyei #language-Picard #language-Paniya #language-Duruwa #language-Pardhi #language-Piti #language-Podena #language-Eastern Pomo #language-Bonan #language-Phudagi #language-Phuong #language-Phukha #language-Phake #language-Phunoi #language-Phu Thai #language-Phuan #language-Pahlavani #language-Pima Bajo #language-Yine #language-Pinji #language-Piaroa #language-Piapoco #language-Pero #language-Pimbwe #language-Pokomo #language-Maleng #language-Palu'e #language-Palikúr #language-Tuamotuan #language-Penrhyn #language-Paleni #language-Polish #language-Pohnpeian #language-Portuguese #language-Potawatomi #language-Polabian #language-Pogolo #language-Paipai #language-Uma #language-Pare #language-Puragi #language-Parawen #language-Panasuan #language-Pai Tavytera #language-Zo'é #language-Enrekang #language-Bambam #language-Port Vato #language-Pentlatch #language-Puelche #language-Puinave #language-Puma #language-Punu #language-Patwin #language-Paiwan #language-Quapaw #language-Quileute #language-Quinault #language-Logooli #language-Rabha #language-Riantana #language-Rao #language-Rawang #language-Barababaraba #language-Reli #language-Rejang #language-Rengao #language-Reshe #language-Reyesano #language-Ringgou #language-Rohingya #language-Yahang #language-Nungu #language-Rikbaktsa #language-Rakhine #language-Rangpuri #language-Rama #language-Rembarrnga #language-Angloromani #language-Domari #language-Welsh Romani #language-Vlax Romani #language-Ruund #language-Rungwa #language-Rombo #language-Romansh #language-Romblomanon #language-Romanian #language-Dela-Oenale #language-Ruthenian #language-Rotuman #language-Gungu #language-Ruuli #language-Rusyn #language-Luguru #language-Russian #language-Rutul #language-Ruma #language-Rawa #language-Yaeyama #language-Sandawe #language-Sango #language-Yakut #language-Sake #language-Samaritan Aramaic #language-Samburu #language-Santali #language-Saleman #language-Saya #language-Saurashtra #language-Safwa #language-Sabüm #language-Kimki #language-Soli #language-Sakachep #language-Sicilian #language-Scots #language-Sa'och #language-Suundi #language-Sherdukpen #language-Semai #language-Seneca #language-Seri #language-Sekani #language-Serrano #language-Secoya #language-Sehwi #language-Shughni #language-Sangkong #language-Singa #language-Samogitian #language-Sanglechi #language-Ninam #language-Sonde #language-Kundal Shahi #language-Shoshoni #language-Shatt #language-Shilluk #language-Shan #language-Shi #language-Shuswap #language-Shwai #language-She #language-Siamou #language-Paasaal #language-Zire #language-Sikiana #language-Sinhala #language-Sikkimese #language-Siuslaw #language-Sinagen #language-Siwai #language-Sumau #language-Sivandi #language-Siwi #language-Xibe #language-Surjapuri #language-Siar-Lak #language-Shawnee #language-Saek #language-Saraiki #language-Maia #language-Skou #language-Slovak #language-Salt-Yui #language-Salar #language-Salampasu #language-Selayar #language-Bolinao #language-Samoan #language-Simeulue #language-Simte #language-Sumbawa #language-Semnani #language-Shona #language-Sindhi #language-Noon #language-Soninke #language-Siona #language-Sam #language-Kou #language-Thai Song #language-Sogdian #language-Aka #language-Somali #language-Kanasi #language-Somrai #language-Southern Thai #language-Spanish #language-Sapé #language-Akukem #language-Sanapaná #language-Saposa #language-Sapuan #language-Sambalpuri #language-Sabaot #language-Shau #language-Albanian #language-Soqotri #language-Squamish #language-Sora #language-Sardinian #language-Sarikoli #language-Siriano #language-Saramaccan #language-Serbian #language-Sirionó #language-Serer #language-Sirmauri #language-Thao #language-Sansi #language-Sunam #language-Semnam #language-Owa #language-Stoney #language-Siberian Tatar #language-Suku #language-Sukuma #language-Sundanese #language-Susu #language-Puroik #language-Sumbwa #language-Sumerian #language-Suyá #language-Sunwar #language-Svan #language-Swedish #language-Sui #language-Saweru #language-Shekhawati #language-Sighu #language-Saaroa #language-Sukur #language-Sylheti #language-Suoy #language-Syriac #language-Sinyar #language-Kagate #language-Samay #language-Ngalum #language-Silesian #language-Sula #language-Suabo #language-Sawai #language-Lower Tanana #language-Tagoi #language-Tahitian #language-Tamil #language-Yami #language-Taabwa #language-Tamasheq #language-Tatar #language-Upper Tanana #language-Tatuyo #language-Tocho #language-Aikanã #language-Tanimbili #language-Gaam #language-Calamian Tagbanwa #language-Taworta #language-Tembo (Kitembo) #language-Ticuna #language-Tanacross #language-Tamagario #language-Tulu #language-Tagdal #language-Thulung #language-Toro #language-Terik #language-Teressa #language-Tehuelche #language-Torricelli #language-Telugu #language-Teso #language-Temein #language-Tetum #language-Soo #language-Tetserret #language-Teribe #language-Ternate #language-Tajik #language-Tagalog #language-Tangoa #language-Tagish #language-Thai #language-Thangmi #language-Thompson #language-Thakali #language-Tahltan #language-Tha #language-Tigre #language-Tiene #language-Tilung #language-Tillamook #language-Tindi #language-Tigrinya #language-Tinigua #language-Tiv #language-Tai Laing #language-Djabwurrung #language-Takelma #language-Tsakhur #language-Mur Pano #language-Klingon #language-Tlingit #language-Tetela #language-Tai Loi #language-Khehek #language-Talysh #language-Haruai #language-Toba-Maskoy #language-Samarokena #language-Tima #language-Iau #language-Temuan #language-Tanimuca-Retuarã #language-Tobanga #language-Kwamera #language-Lenakel #language-Tabla #language-Tanema #language-Tongwe #language-Tolowa #language-Tombulu #language-Toposa #language-Jemez #language-Tobian #language-Kula #language-Trumai #language-Tinputz #language-Lehali #language-Toaripi #language-Taushiro #language-Turoyo #language-Torwali #language-Tsaangi #language-Tsamai #language-Tswa #language-Tsakonian #language-Tausug #language-Tswana #language-Tsonga #language-Tsou #language-Tsogo #language-Mubami #language-Tutelo #language-Gaa #language-Tobati #language-Tooro #language-Totela #language-Titan #language-Wiarumus #language-Tübatulabal #language-Mutu #language-Tuyuca #language-Turkmen #language-Tumbuka #language-Tunica #language-Tucano #language-Turkish #language-Tuscarora #language-Tututni #language-Turkana #language-Tugen #language-Turka #language-Southeast Ambrym #language-Taivoan #language-Twana #language-Tai Dón #language-Twendi #language-Tasawaq #language-Termanu #language-Tsetsaut #language-Tangut #language-Ikpeng #language-Tii #language-Tatana #language-Tauya #language-Tai Daeng #language-Tày #language-Tzeltal #language-Tzotzil #language-Tabriak #language-Kuan #language-Tairuma #language-Ubykh #language-Udi #language-Udmurt #language-Kubachi #language-Ukrainian #language-Ukwuani-Aboh-Ndoni #language-Ulukwumi #language-Ulch #language-Lule #language-Usku #language-Ulithian #language-Ullatan #language-Umpila #language-Munsee #language-Uneme #language-Ngarinyin #language-Mundari #language-Urarina #language-Uru #language-Urak Lawoi' #language-Sop #language-Uya #language-Urum #language-U #language-West Uvean #language-Uri #language-Uzbek #language-Southern Uzbek #language-Vai #language-Huarijio #language-Vasavi #language-Vanuma #language-Varli #language-Venetian #language-Venda #language-Ventureño #language-Veps #language-Vietnamese #language-Vili #language-Kaur #language-Lungalunga #language-Makhuwa #language-Votic #language-Võro #language-Vumbu #language-Wan #language-Washo #language-Kaninuwa #language-Waritai #language-Wanda #language-Vwanji #language-Wakhi #language-Wa #language-Wadjiginy #language-Warrgamay #language-Wichita #language-Minidien #language-Ho-Chunk #language-Vitu #language-Waja #language-Wakde #language-Walloon #language-Wallisian #language-Wambule #language-Wamin #language-Mwani #language-Wantoat #language-Wanggamala #language-Wanap #language-Usan #language-Wintu #language-Wolof #language-Wongo #language-Wiradjuri #language-Warembori #language-Watiwa #language-Berta #language-Watakataui #language-Mewati #language-Silimo #language-Wurrugu #language-Wutung #language-Waama #language-Wymysorys #language-Wyandot #language-Wayoró #language-Adai #language-Xamtanga #language-Kawaiisu #language-Bactrian #language-Kambiwá #language-Chemakum #language-Kaitag #language-Hdi #language-Kembayan #language-Guwa #language-Xhosa #language-Kalkoti #language-Mainstream Kenyah #language-Kiorr #language-Kgalagadi #language-Kamula #language-Lycian #language-Mbudum #language-Mingrelian #language-Mengaka #language-Anglo-Norman #language-Kangri #language-Kenzi #language-Soga #language-Konkomba #language-Mohegan-Pequot #language-Parthian #language-Karakhanid #language-Solano #language-Sherpa #language-Sanumá #language-Saisiyat #language-Ketengban #language-Betta Kurumba #language-Kunigami #language-Kuo #language-Kwaza #language-Woccon #language-Kwerba Mamberamo #language-Wemba Wemba #language-Yorta Yorta #language-Zhang-Zhung #language-Yagua #language-Yao #language-Yapese #language-Yaqui #language-Yala #language-Yemba #language-Hasha #language-Yukuben #language-Lolopo #language-Yucuna #language-Yidgha #language-Yevanic #language-Tarok #language-Nyankpa #language-Yapunda #language-Yeyi #language-Awu #language-Yasa #language-Yaul #language-Yele #language-Yelogu #language-Yameo #language-Moji #language-Makwe #language-Yamna #language-Muzi #language-Naukan Yupik #language-Yong #language-Yansi #language-Yonaguni #language-Yoron #language-Phola #language-Phupha #language-Sani #language-Yessan-Mayo #language-Yuchi #language-Yuki #language-Yulu #language-Quechan #language-Yukpa #language-Yurok #language-Southern Yukaghir #language-Kalou #language-Yuyu #language-Zaghawa #language-Zenaga #language-Kinga #language-Zhaba #language-Dai Zhuang #language-Zhire #language-Nong Zhuang #language-Chinese #language-Zialo #language-Mesme #language-Zinza #language-Zigula #language-Zizilivakan #language-Karankawa #language-Zakhring #language-Kaurna #language-Zimba #language-Mfinu #language-Mbangwe #language-Mpuono #language-Mbariman-Gudhinma #language-Zarphatic #language-Zulu #language-Zuni #language-Zay #language-Yang Zhuang #language-Abun #language-Anem #language-Bilua #language-Bogaya #language-Burmeso #language-Burushaski #language-Camsá #language-Canichana #language-Cayuse #language-Cayubaba #language-Chimariko #language-Coahuilteco #language-Cotoname #language-Cuitlatec #language-Damal #language-Duna #language-Elamite #language-Etruscan #language-Fulniô #language-Fuyug #language-Guató #language-Gule #language-Gumuz #language-Guriaso #language-Hattic #language-Iberian #language-Kaki Ae #language-Kapori #language-Karami #language-Karok #language-Kehu #language-Kenaboi #language-Kibiri #language-Klamath-Modoc #language-Kol (Papua New Guinea) #language-Kujarge #language-Kuot #language-Lafofa #language-Laragia #language-Lavukaleve #language-Máku #language-Mawes #language-Meroitic #language-Minkin #language-Molale #language-Molof #language-Mor (Bomberai Peninsula) #language-Mpur #language-Muniche #language-Nihali #language-Odiai #language-Omurano #language-Papi #language-Pawaia #language-Pele-Ata #language-Pumé #language-Puquina #language-Purari #language-Salinan #language-Sause #language-Savosavo #language-Shom Peng #language-Sulka #language-Taiap #language-Tambora #language-Tanahmerah #language-Taruma #language-Tauade #language-Timucua #language-Tiwi #language-Tonkawa #language-Touo #language-Tsimshian #language-Tuxá #language-Umbugarla #language-Vilela #language-Warao #language-Wiru #language-Xukurú #language-Yale #language-Yámana #language-Yana #language-Yerakai #language-Yetfa #language-Hoti #language-Awjilah #language-Tumzabt #language-Sened #language-Tachelhit #language-Standard Moroccan Tamazight #language-Ghomara #language-Senhaja De Srair #language-Tahaggart Tamahaq #language-Tawallammat Tamajaq #language-Tayart Tamajeq #language-Guanche #language-Mbuko #language-Mbara (Chad) #language-Hya #language-Psikye #language-Bana #language-Kamwe #language-Buduma #language-Jina #language-Majera #language-Mser #language-Maslam #language-Mpade #language-Lamang #language-Vemgo-Mabas #language-Marghi Central #language-Marghi South #language-Bura-Pabir #language-Nggwahyi #language-Putai #language-Dghwede #language-Gvoko #language-Cineni #language-Guduf-Gava #language-Matal #language-Dugwor #language-Merey #language-Zulgo-Gemzek #language-Mofu-Gudur #language-North Mofu #language-Mada (Cameroon) #language-Muyang #language-Wuzlam #language-North Giziga #language-South Giziga #language-Bacama #language-Gudu #language-Ngwaba #language-Jimi (Cameroon) #language-Fali #language-Gude #language-Holma #language-Nzanyi #language-Sharwa #language-Tsuvan #language-Mina (Cameroon) #language-Gavar #language-Mazagway #language-Daba #language-Boga #language-Ga'anda #language-Hwana #language-Jara #language-Tera #language-Cuvok #language-Mafa #language-Mefele #language-Jilbe #language-Mukulu #language-Mabire #language-Birgit #language-Mogum #language-Toram #language-Bidiyo #language-Migaama #language-Jonkor Bourmataguil #language-Kajakse #language-Masmaje #language-Mubi #language-Mawa (Chad) #language-Ubi #language-Boor #language-Miltu #language-Saba #language-Sokoro #language-Tamki #language-Kera #language-Kwang #language-Lele (Chad) #language-Nancere #language-Gabri #language-Ndam #language-Tumak #language-Gadang #language-Sarua #language-Musey #language-Masana #language-Zumaya #language-Ngete #language-Fyer #language-Tambas #language-Kulere #language-Ron #language-Gwandara #language-Karekare #language-Galambu #language-Ngamo #language-Beele #language-Deno #language-Kubi #language-Bure #language-Kholok #language-Nyam #language-Dera (Nigeria) #language-Kushi #language-Piya-Kwonci #language-Tangale #language-Kwaami #language-Mwaghavul #language-Ngas #language-Goemai #language-Tal #language-Koenoem #language-Pyapun #language-Jakattoe #language-Nteng #language-Duwai #language-Ngizim #language-Bade #language-Auyokawa #language-Teshenawa #language-Ajawa #language-Ciwogai #language-Diri #language-Mburku #language-Pa'a #language-Siri #language-Miya #language-Warji #language-Boghom #language-Kir-Balar #language-Mangas #language-Guruntum-Mbaaru #language-Jimi (Nigeria) #language-Ju #language-Tala #language-Zangwal #language-Geji #language-Dass #language-Zeem #language-Zari #language-Awngi #language-Bilin #language-Dahalo #language-Hadiyya #language-Libido #language-Kambaata #language-Gedeo #language-Sidamo #language-Saho #language-Konso #language-West Central Oromo #language-Borana-Arsi-Guji Oromo #language-Orma #language-Eastern Oromo #language-Waata #language-Girirra #language-Maay #language-Rendille #language-Baiso #language-Jiiddu #language-Dabarre #language-Tunni #language-Aweer #language-Arbore #language-Daasanach #language-El Molo #language-Yaaku #language-Boon #language-Kw'adza #language-Burunge #language-Alagwa #language-Gorowa #language-Egyptian (Ancient) #language-Ancient North Arabian #language-Arabic #language-Standard Arabic #language-Hadrami Arabic #language-Hijazi Arabic #language-Judeo-Yemeni Arabic #language-Sanaani Arabic #language-Shihhi Arabic #language-Ta'izzi-Adeni Arabic #language-Baharna Arabic #language-Dhofari Arabic #language-Gulf Arabic #language-Najdi Arabic #language-Omani Arabic #language-Tajiki Arabic #language-Uzbeki Arabic #language-Judeo-Iraqi Arabic #language-North Mesopotamian Arabic #language-Eastern Egyptian Bedawi Arabic #language-Egyptian Arabic #language-Saidi Arabic #language-Chadian Arabic #language-Sudanese Arabic #language-Cypriot Arabic #language-Levantine Arabic #language-South Levantine Arabic #language-Algerian Arabic #language-Algerian Saharan Arabic #language-Hassaniyya #language-Judeo-Tripolitanian Arabic #language-Judeo-Moroccan Arabic #language-Libyan Arabic #language-Tunisian Arabic #language-Andalusian Arabic #language-Moroccan Arabic #language-Classical Syriac #language-Assyrian Neo-Aramaic #language-Chaldean Neo-Aramaic #language-Jewish Babylonian Aramaic (ca. 200-1200 CE) #language-Senaya #language-Barzani Jewish Neo-Aramaic #language-Lishana Deni #language-Hulaulá #language-Lishán Didán #language-Lishanid Noshan #language-Classical Mandaic #language-Western Neo-Aramaic #language-Jewish Palestinian Aramaic #language-Old Aramaic (up to 700 BCE) #language-Ancient Hebrew #language-Samaritan #language-Edomite #language-Moabite #language-Ugaritic #language-Phoenician #language-Punic #language-Hadrami #language-Minaean #language-Qatabanian #language-Geez #language-Amharic #language-Argobba #language-Silt'e #language-Wolane #language-Gafat #language-Kistane #language-Mesqan #language-Sebat Bet Gurage #language-Mesmes #language-Hobyót #language-Bathari #language-Harsusi #language-Mehri #language-Wiyot #language-Siksika #language-Nawathinehena #language-Gros Ventre #language-Northern East Cree #language-Southern East Cree #language-Woods Cree #language-Michif #language-Malecite-Passamaquoddy #language-Powhatan #language-Unami #language-Nanticoke #language-Piscataway #language-Loup A #language-Wampanoag #language-Miami #language-Kickapoo #language-Meskwaki #language-Ojibwa #language-Ottawa #language-Central Ojibwa #language-Chippewa #language-Eastern Ojibwa #language-Northwestern Ojibwa #language-Western Ojibwa #language-Severn Ojibwa #language-Alsea #language-Amto #language-Angaataha #language-Yagwoia #language-Baruya #language-Simbari #language-Menya #language-Kawacha #language-Kamasa #language-Susuami #language-Ankave #language-Ipiko #language-Kuni-Boazi #language-Zimakani #language-Bian Marind #language-Marind #language-Warkay-Bipim #language-Yaqay #language-Abom #language-Baramu #language-Tapei #language-Mapudungun #language-Yavitero #language-Baré #language-Taino #language-Garifuna #language-Island Carib #language-Enawené-Nawé #language-Parecís #language-Saraveca #language-Yawalapití #language-Mehináku #language-Waurá #language-Cabiyarí #language-Tariana #language-Curripaco #language-Achagua #language-Mandahuaca #language-Resígaro #language-Xiriâna #language-Wapishana #language-Baure #language-Paunaka #language-Ignaciano #language-Trinitario #language-Chané #language-Ajyíninka Apurucayali #language-Ashéninka Perené #language-Pichis Ashéninka #language-Ucayali-Yurúa Ashéninka #language-Ashéninka Pajonal #language-South Ucayali Ashéninka #language-Machiguenga #language-Apurinã #language-Iñapari #language-Machinere #language-Aruá (Amazonas State) #language-Suruahá #language-Madi #language-Culina #language-Afrihili #language-Blissymbols #language-Brithenig #language-Dutton World Speedwords #language-Interlingua (International Auxiliary Language Association) #language-Interglossa #language-Interlingue #language-Kotava #language-Láadan #language-Lingua Franca Nova #language-Lojban #language-Malawian Sign Language #language-N'Ko #language-Novial #language-Quenya #language-Romanova #language-Sindarin #language-Talossan #language-Toki Pona #language-Volapük #language-Esperanto #language-Ido #language-Eyak #language-Sarsi #language-Kiowa Apache #language-Jicarilla Apache #language-Lipan Apache #language-Mescalero-Chiricahua Apache #language-Southern Carrier #language-Han #language-Degexit'an #language-Northern Tutchone #language-Southern Tutchone #language-Beaver #language-North Slavey #language-South Slavey #language-Kato #language-Mattole #language-Wailaki #language-Upper Umpqua #language-Coquille #language-Ahtena #language-Gola #language-Mansoanka #language-East Limba #language-West-Central Limba #language-Sherbro #language-Bom-Kim #language-Bullom So #language-Northern Kissi #language-Southern Kisi #language-Baga Manduri #language-Baga Sitemu #language-Baga Koga #language-Landoma #language-Timne #language-Ndut #language-Saafi-Saafi #language-Lehar #language-Balanta-Kentohe #language-Balanta-Ganja #language-Bayot #language-Ejamat #language-Kuwaataay #language-Karon #language-Mlomp #language-Gusilay #language-Mankanya #language-Mandjak #language-Papel #language-Biafada #language-Mbulungish #language-Nalu #language-Borgu Fulfulde #language-Maasina Fulfulde #language-Pular #language-Western Niger Fulfulde #language-Central-Eastern Niger Fulfulde #language-Adamawa Fulfulde #language-Bagirmi Fulfulde #language-Kasanga #language-Kobiana #language-Gambian Wolof #language-Ega #language-Gade #language-Oko-Eni-Osayen #language-Ukaan #language-Akpes #language-Epie #language-Degema #language-Ghotuo #language-Yekhee #language-Bini #language-Emai-Iuleha-Ora #language-Enwan (Edo State) #language-Ikpeshi #language-Ivbie North-Okpela-Arhe #language-Igwe #language-Sasaru #language-Iyayu #language-Uhami #language-Ehueun #language-Ukue #language-Okpamheri #language-Oloma #language-Akuku #language-Okpe (Northwestern Edo) #language-Eruwa #language-Isoko #language-Okpe (Southwestern Edo) #language-Urhobo #language-Tikar #language-Samba Daka #language-Dirim #language-Lamja-Dengsa-Tola #language-Dong #language-Ndoola #language-Bung #language-Luo (Cameroon) #language-Njerep #language-Yeni #language-Mbongno #language-Ndunda #language-Vute #language-Wawa #language-Bishuo #language-Busuu #language-Bikya #language-Bukwen #language-Mashi (Nigeria) #language-Noone #language-Mbuk #language-Ncane #language-Bumaji #language-Obanliku #language-Bete #language-Ubang #language-Ukpe-Bayobiri #language-Buru (Nigeria) #language-Ejagham #language-Efutop #language-Abanyom #language-Ekajuk #language-Kendem #language-Seki #language-Kande #language-Simba #language-Bubi #language-Dimbong #language-Bafia #language-Lefa #language-Bankon #language-Barombi #language-Bakoko #language-Basa (Cameroon) #language-Hijuk #language-Bulu (Cameroon) #language-Fang (Equatorial Guinea) #language-Mengisa #language-Bebele #language-Ewondo #language-Kota (Gabon) #language-Mahongwe #language-Ndasa #language-Wumbvu #language-Kélé #language-Ngom #language-Ndambomo #language-Bonkeng #language-Nkongho #language-Mokpwe #language-Bassossi #language-Mbo (Cameroon) #language-Akoose #language-Bakaka #language-Kako #language-Kwakum #language-Bomwali #language-Mpiemo #language-Ukhwejo #language-Koonzime #language-Njyem #language-Makaa #language-Kol (Cameroon) #language-Gyele #language-Pomo #language-Batanga #language-Molengue #language-Ngumbi #language-Duala #language-Malimba #language-Bakole #language-Isu (Fako Division) #language-Mashi (Zambia) #language-Nyengo #language-Simaa #language-Sanga (Democratic Republic of Congo) #language-Kanyok #language-Bangubangu #language-Luba-Lulua #language-Binji #language-Luna #language-Songe #language-Zula #language-Mbangala #language-Phende #language-Mbala #language-Kibala #language-Kimbundu #language-Mpinda #language-Luvale #language-Luchazi #language-Nkangala #language-Nyemba #language-Luimbi #language-Mbwela #language-Kete #language-Umbundu #language-Kuvale #language-Kwandu #language-Ngendelengo #language-Kuanyama #language-Kwambi #language-Ndonga #language-Mbalanhu #language-Ngandyera #language-Nkhumbi #language-Ndombe #language-Mbesa #language-Lombo #language-Poke #language-Moingi #language-So (Democratic Republic of Congo) #language-Mbo (Democratic Republic of Congo) #language-Ndaka #language-Sengele #language-Bolia #language-Ntomba #language-Lalia #language-Ngando (Democratic Republic of Congo) #language-Ombo #language-Bushoong #language-Lele (Democratic Republic of Congo) #language-Dengese #language-Nkutu #language-Kusu #language-Kela (Democratic Republic of Congo) #language-Akwa #language-Mboko #language-Koyo #language-Mbosi #language-Dibole #language-Mbati #language-Ngundi #language-Yaka (Central African Republic) #language-Bomitaba #language-Bongili #language-Ngando (Central African Republic) #language-Lusengo #language-Bamwe #language-Dzando #language-Ndolo #language-Bomboma #language-Bomboli #language-Bozaba #language-Bali (Democratic Republic of Congo) #language-Amba (Uganda) #language-Kango (Tshopo District) #language-Komo (Democratic Republic of Congo) #language-Kango (Bas-Uélé District) #language-Nyanga-li #language-Homa #language-Mayeka #language-Bodo (Central African Republic) #language-Boguru #language-Ligenza #language-Ngombe (Democratic Republic of Congo) #language-Bwela #language-Bolondo #language-Babango #language-Boko (Democratic Republic of Congo) #language-Lobala #language-Boloki #language-Moi (Congo) #language-Bangala #language-Likuba #language-Likwala #language-Mabaale #language-Ndobo #language-Libinza #language-Samba #language-Beembe #language-Kaamba #language-Kunyi #language-Doondo #language-Laari #language-Hungu #language-Kituba (Congo) #language-Kituba (Democratic Republic of Congo) #language-San Salvador Kongo #language-Yombe #language-Bwisi #language-Sangu (Gabon) #language-Sira #language-Lonzo #language-Pelende #language-Ngongo #language-Ibali Teke #language-Sakata #language-Teke-Fuumu #language-Teke-Tyee #language-Teke-Kukuya #language-Teke-Tsaayi #language-Tchitchege #language-Kaningi #language-Ndumu #language-Teke-Laali #language-Yaka (Congo) #language-Duma #language-Wandji #language-Ngungwel #language-Teke-Nzikou #language-Dombe #language-Sala #language-Tonga (Zambia) #language-Subiya #language-Bungu #language-Nyamwanga #language-Nyika (Tanzania) #language-Nyika (Malawi and Zambia) #language-Nyiha (Malawi) #language-Nyiha (Tanzania) #language-Nyakyusa-Ngonde #language-Rangi #language-Mbugwe #language-Dhaiso #language-Kamba (Kenya) #language-Chuka #language-Tharaka #language-Temi #language-Mwimbi-Muthambi #language-Suba #language-Suba-Simbiti #language-Kabwa #language-Zanaki #language-Kara (Tanzania) #language-Kwaya #language-Luyia #language-Idakho-Isukha-Tiriki #language-Bukusu #language-Kabras #language-Masaaba #language-East Nyala #language-Kisa #language-Marama #language-Nyore #language-Tachoni #language-Tsotso #language-Wanga #language-Saamia #language-Nyole #language-Ganda #language-Kenyi #language-Talinga-Bwisi #language-Chiga #language-Nyankole #language-Subi #language-Nyindu #language-Fuliiru #language-Joba #language-Kinyarwanda #language-Rundi #language-Vinza #language-Shubi #language-Konzo #language-Kahe #language-Mochi #language-Vunjo #language-Machame #language-Rwa #language-Sagalla #language-Taita #language-Mwali Comorian #language-Ngazidja Comorian #language-Maore Comorian #language-Ndzwani Comorian #language-Chonyi-Dzihana-Kauma #language-Duruma #language-Giryama #language-Segeju #language-Congo Swahili #language-Cutchi-Swahili #language-Taveta #language-Asu (Tanzania) #language-Kagulu #language-Doe #language-Kami (Tanzania) #language-Kutu #language-Zaramo #language-Bondei #language-Mushungulu #language-Sagala #language-Vidunda #language-Bena (Tanzania) #language-Benamanga #language-Magoma #language-Kisi #language-Sangu (Tanzania) #language-Nyamwezi #language-Konongo #language-Ruwila #language-Bende #language-Bembe #language-Songoora #language-Buyu #language-Lega-Mwenga #language-Kanu #language-Lega-Shabunda #language-Mituku #language-Kwami #language-Nilamba #language-Nyaturu #language-Ndamba #language-Mbunga #language-Ndwewe #language-Ndendeule #language-Nindi #language-Machinga #language-Mwera (Chimwera) #language-Bwile #language-Bemba (Zambia) #language-Seba #language-Ndau #language-Manyika #language-Tewe #language-Tawara #language-Dema #language-Gitonga #language-Swati #language-Ronga #language-Kokola #language-Maindo #language-Manyawa #language-Nathembo #language-Lolo #language-Marenje #language-Takwane #language-Makhuwa-Shirima #language-Makhuwa-Meetto #language-Makhuwa-Marrevone #language-Makhuwa-Moniga #language-Makhuwa-Saka #language-Birwa #language-Pedi #language-Tswapong #language-Southern Sotho #language-Koma #language-Mwera (Nyasa) #language-Nyanja #language-Barwe #language-Malawi Sena #language-Sena #language-Phimbi #language-Tonga (Nyasa) #language-Bube #language-Mbonga #language-Kulung (Nigeria) #language-Mama #language-Dulbu #language-Bada (Nigeria) #language-Duguri #language-Bankal #language-Gwa #language-Nubaca #language-Bati (Cameroon) #language-Mbule #language-Yangben #language-Mmaala #language-Elip #language-Nugunu (Cameroon) #language-Leti (Cameroon) #language-Tuki #language-Tuotomb #language-Yambeta #language-Nomaande #language-Tunen #language-Esimbi #language-Evant #language-Iyive #language-Otank #language-Caka #language-Eman #language-Ambo #language-Bitare #language-Ambele #language-Befang #language-Ndemli #language-Mbe' #language-Yamba #language-Kwaja #language-Fe'fe' #language-Ghomálá' #language-Kwa' #language-Nda'nda' #language-Ngombale #language-Ngwe #language-Bafanji #language-Bambalang #language-Bamun #language-Bangolan #language-Mungaka #language-Bamenyam #language-Awing #language-Beba #language-Pinyin #language-Bafut #language-Bambili-Bambui #language-Mendankwe-Nkwen #language-Ngemba #language-Kpati #language-Mundani #language-Njen #language-Ngie #language-Ngoshie #language-Meta' #language-Ngamambo #language-Lamnso' #language-Kung #language-Kom (Cameroon) #language-Mbessa #language-Bum #language-Kuk #language-Laimbue #language-Isu (Menchum Division) #language-Zhoa #language-Weh #language-Bamunka #language-Kenswei Nsei #language-Balo #language-Busam #language-Osatu #language-Menka #language-Viti #language-Fang (Cameroon) #language-Koshin #language-Ajumbu #language-Abar #language-Mundabli #language-Fam #language-Sambe #language-Lijili #language-Cen #language-Ganang #language-Shall-Zwall #language-Doka #language-Iku-Gora-Ankwa #language-Kuturmi #language-Bo-Rukul #language-Fyam #language-Sur #language-Tiyaa #language-Bijim #language-Kadung #language-Ikulu #language-Aninka #language-Ayu #language-Numana #language-Kaningdon-Nindem #language-Che #language-Mada (Nigeria) #language-Kagoma #language-Kamantan #language-Shamang #language-Ashe #language-Koro Nulu #language-Kapya #language-Akum #language-Beezen #language-Lufu #language-Arigidi #language-Àhàn #language-Ayere #language-Igala #language-Isekiri #language-Mokole #language-Ede Cabe #language-Ede Ije #language-Lucumi #language-Yoruba #language-Kura Ede Nago #language-Ede Idaca #language-Ede Ica #language-Ifè #language-Abua #language-Odual #language-Kugbo #language-Ogbogolo #language-Obulom #language-O'chi'chi' #language-Ebughu #language-Ibino #language-Iko #language-Ilue #language-Okobo #language-Oro #language-Usaghade #language-Efai #language-Anaang #language-Ukwa #language-Ekit #language-Etebi #language-Ibuoro #language-Ito #language-Itu Mbon Uzo #language-Nkari #language-Enwan (Akwa Ibom State) #language-Uda #language-Eki #language-Idere #language-Gokana #language-Tee #language-Eleme #language-Ukpet-Ehom #language-Bakpinka #language-Doko-Uyanga #language-Olulumo-Ikom #language-Lokaa #language-Lubila #language-Cross River Mbembe #language-Legbo #language-Lenyima #language-Leyigha #language-Oring #language-Kukele #language-Uzekwe #language-Ubaghara #language-Agwagwune #language-Kohumono #language-Umon #language-Durop #language-Ebira #language-Gbagyi #language-Gbari #language-Asu (Nigeria) #language-Nupe-Nupe-Tako #language-Kakanda #language-Kupa #language-Kami (Nigeria) #language-Gupa-Abawa #language-Koro Zuba #language-Igede #language-Etulo #language-Akpa #language-Ekpeye #language-Ika #language-Ikwere #language-Ogbah #language-Ezaa #language-Ikwo #language-Kutep #language-Tigon Mbembe #language-Wãpha #language-Jibu #language-Hõne #language-Wannu #language-Como Karim #language-Jiru #language-Shoo-Minda-Nye #language-Etkywan #language-Kpan #language-Basa (Nigeria) #language-Basa-Gurmana #language-Bassa-Kontagora #language-Amo #language-Bina (Nigeria) #language-Kono (Nigeria) #language-Lere #language-Gyem #language-Kudu-Camo #language-Iguta #language-Jere #language-Panawa #language-Izora #language-Sanga (Nigeria) #language-Sheni #language-Damakawa #language-Cicipu #language-Tsuvadi #language-Tsikimba #language-Rogo #language-Eastern Acipa #language-Shama-Sambuga #language-Bauchi #language-Fungwa #language-Gurmana #language-Baissa Fali #language-Tita #language-Adangme #language-Aja (Benin) #language-Eastern Xwla Gbe #language-Tofin Gbe #language-Ci Gbe #language-Defi Gbe #language-Maxi Gbe #language-Weme Gbe #language-Wudu #language-Ayizo Gbe #language-Gbesi Gbe #language-Kotafon Gbe #language-Saxwe Gbe #language-Western Xwla Gbe #language-Xwela Gbe #language-Adangbe #language-Kpessi #language-Waci Gbe #language-Nyangbo #language-Tafi #language-Akebu #language-Animere #language-Igo #language-Ikposo #language-Tuwuli #language-Anii #language-Sekpele #language-Selee #language-Attié #language-Abé #language-Abidji #language-Adioukrou #language-Alladian #language-Avikam #language-Mbato #language-Krobu #language-Abron #language-Akan #language-Wasa #language-Twi #language-Anufo #language-Baoulé #language-Anyin Morofo #language-Ahanta #language-Nzima #language-Dompo #language-Gonja #language-Nkami #language-Nkonya #language-Nawuri #language-Foodo #language-Gikyode #language-Kplang #language-Krache #language-Chumburung #language-Tchumbuli #language-Nchumbulu #language-Awutu #language-Larteh #language-Cherepon #language-Gua #language-Abure #language-Beti (Côte d'Ivoire) #language-Day #language-Tunia #language-Bua #language-Bon Gula #language-Zan Gula #language-Gula Iro #language-Koke #language-Besme #language-Goundo #language-Kim #language-Lala-Roba #language-Bena (Nigeria) #language-Voro #language-Mághdì #language-Mak (Nigeria) #language-Kyak #language-Leelau #language-Moo #language-Dza #language-Mbum #language-Kare (Central African Republic) #language-Pana (Central African Republic) #language-Ndai #language-Mambai #language-Tupuri #language-Mono (Cameroon) #language-To #language-Pangseng #language-Rang #language-Bali (Nigeria) #language-Kpasam #language-Yotti #language-Teme #language-Waka #language-Yendang #language-Doyayo #language-Gimme #language-Gimnime #language-Mom Jango #language-Longto #language-Dii #language-Dugun #language-Duupa #language-Kolbila #language-Samba Leko #language-Wom (Nigeria) #language-Mbandja #language-Ngbundu #language-West Central Banda #language-Banda-Yangere #language-Banda-Mbrès #language-Banda-Banda #language-Banda-Bambari #language-Banda-Ndélé #language-Togbo-Vara Banda #language-Gobu #language-Kpagua #language-Mid-Southern Banda #language-Mono (Democratic Republic of Congo) #language-Ngundu #language-Langbashe #language-South Central Banda #language-Ma (Democratic Republic of Congo) #language-Dongo #language-Mba #language-Ndunga #language-Gbayi #language-Dendi (Central African Republic) #language-Mbangi #language-Northern Ngbandi #language-Southern Ngbandi #language-Yakoma #language-Riverain Sango #language-Mündü #language-Bangba #language-Mayogo #language-Gundi #language-Limassa #language-Baka (Cameroon) #language-Ganzi #language-Gilima #language-Ngbaka Ma'bo #language-Monzombo #language-Kpala #language-Yango #language-Feroge #language-Mangayat #language-Indri #language-Togoyo #language-Ndogo #language-Sere #language-Tagbu #language-Barambu #language-Pambia #language-Geme #language-Nzakara #language-Oblo #language-Gbanu #language-Manza #language-Ali #language-Ngbaka Manza #language-Gbaya-Mbodomo #language-Northwest Gbaya #language-Gbaya-Bozoum #language-Gbaya-Bossangoa #language-Suma #language-Southwest Gbaya #language-Viemo #language-Koromfé #language-Láá Láá Bwamu #language-Buli (Ghana) #language-Gourmanchéma #language-Bimoba #language-Moba #language-Akaselem #language-Yom #language-Kantosi #language-Mossi #language-Safaliba #language-Dagaari Dioula #language-Wali (Ghana) #language-Northern Dagara #language-Malba Birifor #language-Hanga #language-Kamara #language-Biali #language-Nateni #language-Ditammari #language-Mbelime #language-Baatonum #language-Dogosé #language-Khisa #language-Lama (Togo) #language-Lukpa #language-Bago-Kusuntu #language-Chala #language-Phuie #language-Winyé #language-Vagla #language-Chakali #language-Tampulma #language-Tumulung Sisaala #language-Western Sisaala #language-Pana (Burkina Faso) #language-Kasem #language-Northern Nuni #language-Southern Nuni #language-Dyan #language-Dijim-Bwilim #language-Awak #language-Tula #language-Bondoukou Kulango #language-Bouna Kulango #language-Loma (Côte d'Ivoire) #language-Téén #language-Northern Toussian #language-Southern Toussian #language-Eastern Karaboro #language-Western Karaboro #language-Mamara Senoufo #language-Nanerigé Sénoufo #language-Sìcìté Sénoufo #language-Supyire Senoufo #language-Syenara Senoufo #language-Shempire Senoufo #language-Nyarafolo Senoufo #language-Palaka Senoufo #language-Djimini Senoufo #language-Tagwana Senoufo #language-Miyobe #language-Aproumu Aizi #language-North Fali #language-South Fali #language-Jah Hut #language-Chewong #language-Kensiu #language-Kintaq #language-Jehai #language-Minriq #language-Batek #language-Temiar #language-Besisi #language-Semaq Beri #language-Semelai #language-Temoq #language-Cua #language-Katua #language-Takua #language-Monom #language-Todrah #language-Hre #language-Sedang #language-Kayong #language-Halang #language-Jeh #language-Halang Doan #language-Romam #language-Alak #language-Brao #language-Oy #language-Kavet #language-Krung #language-Laven #language-Sou #language-Maa #language-Chrau #language-Eastern Mnong #language-Central Mnong #language-Kraol #language-Southern Mnong #language-Budeh Stieng #language-Bulo Stieng #language-Mel-Khaonh #language-Tampuan #language-Talieng #language-Trieng #language-Pacoh #language-Eastern Katu #language-Western Katu #language-Lower Ta'oih #language-Upper Ta'oih #language-Eastern Bru #language-Northern Katang #language-Southern Katang #language-Sô #language-Western Bru #language-Nyeu #language-War-Jaintia #language-Hu #language-Man Met #language-Mok #language-Bit #language-Samtao #language-Eastern Lawa #language-Western Lawa #language-Rumai Palaung #language-Ruching Palaung #language-Shwe Palaung #language-Northern Khmer #language-Old Khmer #language-Mlabri #language-Khuen #language-O'du #language-Phong-Kniang #language-Mang #language-Bolyu #language-Bugan #language-Nyahkur #language-Old Mon #language-Gata' #language-Bodo Gadaba #language-Bondo #language-Birhor #language-Koda #language-Majhwar #language-Turi #language-Asuri #language-Bijori #language-Kodaku #language-Kol (Bangladesh) #language-Mahali #language-Juray #language-Car Nicobarese #language-Central Nicobarese #language-Arem #language-Chut #language-Hung #language-Tho #language-Nguôn #language-Puyuma #language-Atayal #language-Sakizaya #language-Basay #language-Ketangalan #language-Siraya #language-Ati #language-Enggano #language-Nasal #language-Basap #language-Dusun Malang #language-Dusun Deyah #language-Ampanang #language-Tunjung #language-Lawangan #language-Tawoyan #language-Kohin #language-Ot Danum #language-Siang #language-Inabaknon #language-Yakan #language-Pangutaran Sama #language-Indonesian Bajau #language-Mapun #language-West Coast Bajau #language-Balangingi #language-Central Sama #language-Southern Sama #language-Dusun Witu #language-Ma'anyan #language-Paku #language-Plateau Malagasy #language-Southern Betsimisaraka Malagasy #language-Antankarana Malagasy #language-Northern Betsimisaraka Malagasy #language-Tsimihety Malagasy #language-Tesaka Malagasy #language-Bara Malagasy #language-Tanosy Malagasy #language-Masikoro Malagasy #language-Bakumpai #language-Ngaju #language-Ibatan #language-Giangan #language-Tiruray #language-Tboli #language-Koronadal Blaan #language-Sarangani Blaan #language-Banggai #language-Bobongko #language-Batui #language-Moronene #language-Bahonsuai #language-Bungku #language-Koroni #language-Kulisusu #language-Mori Bawah #language-Taloki #language-Wawonii #language-Mori Atas #language-Padoe #language-Tomadino #language-Kodeoha #language-Rahambuu #language-Tolaki #language-Waru #language-Kumbewaha #language-Lasalimu #language-Busoa #language-Kaimbulawa #language-Kioko #language-Liabuku #language-Pancana #language-Bonerate #language-Tukang Besi North #language-Tukang Besi South #language-Dondo #language-Lauje #language-Tomini #language-Balaesang #language-Dampelas #language-Pendau #language-Taje #language-Tajio #language-Topoiyo #language-Sedoa #language-Baras #language-Da'a Kaili #language-Ledo Kaili #language-Unde Kaili #language-Moma #language-Tado #language-Pamona #language-Tombelala #language-Sarudu #language-Wotu #language-Kamaru #language-Wolio #language-Pampanga #language-Ambala Ayta #language-Botolan Sambal #language-Mag-Indi Ayta #language-East Tarangan #language-West Tarangan #language-Batuley #language-Mariri #language-Lola #language-Lorang #language-Manombai #language-Dobel #language-Koba #language-Barakai #language-Karey #language-Ujir #language-Kola #language-Kompane #language-Kedang #language-Sika #language-Lamaholot #language-Lewotobi #language-Lamalera #language-Ile Ape #language-West Lembata #language-Lamatuka #language-Lewo Eleng #language-Kepo' #language-Komodo #language-Manggarai #language-Riung #language-Rembong #language-Rajong #language-Ende #language-Li'o #language-Nage #language-Ngad'a #language-Rongga #language-Eastern Ngad'a #language-Kambera #language-Mamboru #language-Anakalangu #language-Wanukaka #language-Lamboya #language-Laura #language-Banda (Indonesia) #language-Watubela #language-Bati (Indonesia) #language-Geser-Gorom #language-Bobot #language-Benggoi #language-Liana-Seti #language-Salas #language-Huaulu #language-North Nuaulu #language-South Nuaulu #language-Sepa (Indonesia) #language-Paulohi #language-Kaibobo #language-Laha (Indonesia) #language-Seit-Kaitetu #language-Hitu #language-Tulehu #language-Kamarian #language-Haruku #language-Amahai #language-Nusa Laut #language-Latu #language-Saparua #language-Asilulu #language-Boano (Maluku) #language-Larike-Wakasihu #language-Wemale #language-Hulung #language-Lisabata-Nuniali #language-Loun #language-Alune #language-Naka'ela #language-Kur #language-Teor #language-Buru (Indonesia) #language-Mangole #language-Kadai #language-Taliabu #language-Kei #language-Yamdena #language-Onin #language-Sekar #language-Uruangnirin #language-Helong #language-Idaté #language-Lakalei #language-Habu #language-Tetun Dili #language-Kairui-Midiki #language-Nauete #language-Waima'a #language-Amarasi #language-Baikeno #language-Maku'a #language-Dai #language-Dawera-Daweloor #language-North Babar #language-Central Masela #language-East Masela #language-Serili #language-Southeast Babar #language-West Masela #language-Emplawas #language-Imroing #language-Tela-Masbuar #language-Kisar #language-Roma #language-Leti (Indonesia) #language-Selaru #language-Seluwasan #language-Te'un #language-Nila #language-Serua #language-Ili'uun #language-Tugun #language-Aputai #language-Perai #language-Mambae #language-Welaun #language-Kemak #language-Tukudede #language-Pak-Tong #language-Andra-Hus #language-Leipon #language-Ponam #language-Lele (Papua New Guinea) #language-Nali #language-Ere #language-Kele (Papua New Guinea) #language-Elu #language-Loniu #language-Mokerang #language-Bipi #language-Hermit #language-Nyindrou #language-Sori-Harengan #language-Mondropolon #language-Tulu-Bohuai #language-Likum #language-Lenkau #language-Nauna #language-Penchal #language-Lou #language-Pam #language-Seimat #language-Wuvulu-Aua #language-Kaniet #language-Gone Dau #language-Lauan #language-Lomaiviti #language-Anuta #language-East Futuna #language-Rennell-Bellona #language-Tikopia #language-Niuafo'ou #language-Niuatoputapu #language-Tuvalu #language-Pukapuka #language-Tokelau #language-Sikaiana #language-Nukumanu #language-Nukuria #language-Takuu #language-Rapanui #language-North Marquesan #language-South Marquesan #language-Maori #language-Rakahanga-Manihiki #language-Austral #language-Futuna-Aniwa #language-Tonga (Tonga Islands) #language-Namosi-Naitasiri-Serua #language-Western Fijian #language-Pingelapese #language-Mapia #language-Woleaian #language-Mortlockese #language-Puluwatese #language-Satawalese #language-Namonuito #language-Pááfang #language-Tanapag #language-Sonsorol #language-Kosraean #language-Nauru #language-Paama #language-North Ambrym #language-Lelepa #language-Eton (Vanuatu) #language-South Efate #language-Baki #language-Bierebo #language-Bieria #language-Maii #language-Lamenu #language-Lewo #language-Uripiv-Wala-Rano-Atchin #language-Aulua #language-Burmbar #language-Maskelynes #language-Axamb #language-Port Sandwich #language-Rerep #language-Unua #language-Malua Bay #language-Mpotovoro #language-Vao #language-Larevat #language-Maragus #language-Dixon Reef #language-Nasarian #language-Letemboi #language-Repanbitip #language-Apma #language-Sa #language-Seke (Vanuatu) #language-Sowa #language-Hano #language-East Ambae #language-West Ambae #language-Mafea #language-Tutuba #language-Polonombauk #language-Tambotalo #language-Ngen #language-Aore #language-Araki #language-Sakao #language-Tolomako #language-Nokuku #language-Piamatsina #language-Tasmate #language-Valpei #language-Vunapu #language-Amblong #language-Morouas #language-Narango #language-Merei #language-Navut #language-Tiale #language-Akei #language-Baetora #language-Central Maewo #language-Lehalurup #language-Merlav #language-Mota #language-Nume #language-Vurës #language-Hiw #language-Lo-Toga #language-Lakon #language-Koro (Vanuatu) #language-Lemerig #language-Vera'a #language-Bughotu #language-Gela #language-Ghari #language-Lengo #language-Malango #language-Birao #language-Talise #language-Longgu #language-Sa'a #language-Kwaio #language-Wala #language-Baelelea #language-Fataleka #language-To'abaita #language-'Are'are #language-Dori'o #language-Oroha #language-Arosi #language-Fagani #language-Dehu #language-Nengone #language-Nêlêmwa-Nixumwak #language-Jawe #language-Pwaamei #language-Pije #language-Fwâi #language-Nemi #language-Cemuhî #language-Paicî #language-Hmwaveke #language-Vamale #language-Waamwang #language-Haveke #language-Bwatoo #language-Dumbea #language-Neku #language-Xârâcùù #language-Ajië #language-Arhâ #language-Arhö #language-Tiri #language-Aneityum #language-Ifo #language-Sie #language-Ura (Vanuatu) #language-North Tanna #language-Whitesands #language-Southwest Tanna #language-Mussau-Emira #language-Tenis #language-Nalögo #language-Natügu #language-Malo #language-Neo #language-Teanu #language-Amba (Solomon Islands) #language-Asumboa #language-Tomoip #language-Barok #language-Lavatbura-Lamusong #language-Madak #language-Konomala #language-Sursurunga #language-Kandas #language-Ramoaaina #language-Bilur #language-Label #language-Ririo #language-Babatana #language-Vaghua #language-Varisi #language-Torau #language-Uruava #language-Solos #language-Nehan #language-Papapana #language-Petats #language-Hakö #language-Halia #language-Hahon #language-Teop #language-Kazukuru #language-Ughele #language-Marovo #language-Vangunu #language-Roviana #language-Hoava #language-Kusaghe #language-Duke #language-Simbo #language-Lungga #language-Lawunuia #language-Blablanga #language-Zazao #language-Cheke Holo #language-Gao #language-Laghu #language-Zabana #language-Guramalum #language-Kuanua #language-Fanamaket #language-Warwar Feni #language-Niwer Mil #language-Mandara #language-Notsi #language-Kara (Papua New Guinea) #language-Nalik #language-Tiang #language-Tigak #language-Tungag #language-Bola #language-Bulu (Papua New Guinea) #language-Numbami #language-Labu #language-Aribwaung #language-Musom #language-Nafi #language-Adzera #language-Mari (Madang Province) #language-Sarasira #language-Sukurum #language-Wampur #language-Middle Watut #language-North Watut #language-South Watut #language-Bugawac #language-Kela (Papua New Guinea) #language-Iwal #language-Kapin #language-Piu #language-Vehes #language-Gorakor #language-Dambi #language-Kumalu #language-Patep #language-Zenag #language-Yamap #language-Bariai #language-Kove #language-Gitua #language-Maleu-Kilenge #language-Mbula #language-Sio #language-Tami #language-Mato #language-Ronji #language-Awad Bing #language-Mindiri #language-Wab #language-Gedaged #language-Marik #language-Matukar #language-Takia #language-Arop-Lokep #language-Karnai #language-Lote #language-Mamusi #language-Mengen #language-Amara #language-Akolet #language-Avau #language-Aiklep #language-Gimi (West New Britain) #language-Solong #language-Bebeli #language-Mangseng #language-Aighon #language-Karore #language-Kaulong #language-Miu #language-Sengseng #language-Lamogai #language-Mouk-Aria #language-Kayupulau #language-Ormu #language-Bonggo #language-Kaptiau #language-Masimasi #language-Tarpia #language-Liki #language-Sobei #language-Kairiru #language-Kaiep #language-Terebu #language-Medebur #language-Biem #language-Manam #language-Sepa (Papua New Guinea) #language-Kis #language-Wogeo #language-Ulau-Suain #language-Kap #language-Tumleo #language-Sera #language-Arop-Sissano #language-Malol #language-Sissano #language-Anuki #language-Gumawana #language-Maisin #language-Arifama-Miniafia #language-Ubir #language-Are #language-Doga #language-Gapapaiwa #language-Ghayavi #language-Minaveha #language-Tawala #language-Gweda #language-Haigwai #language-Maiwala #language-Taupota #language-Wa'ema #language-Yaleba #language-Wedau #language-Yakaikeke #language-Koluwawa #language-Bwaidoka #language-Iduna #language-Iamalele #language-Maiadomu #language-Dobu #language-Duau #language-Sewa Bay #language-Boselewa #language-Galeya #language-Bunama #language-Mwatebu #language-Dawawa #language-Kakabai #language-'Auhelawa #language-Buhutu #language-Bwanabwana #language-Oya'oya #language-Unubahe #language-Wagawaga #language-Saliba #language-Suau #language-Ouma #language-Bina (Papua New Guinea) #language-Magori #language-Yoba #language-Sinaugoro #language-Hula #language-Keapara #language-Abadi #language-Motu #language-Kuni #language-Lala #language-Mekeo #language-Toura (Papua New Guinea) #language-Waima #language-Budibud #language-Kilivila #language-Muyuw #language-Nimoa #language-Sudest #language-Nguluwan #language-Mor (Mor Islands) #language-Tandia #language-Waropen #language-Arguni #language-Bedoanas #language-Erokwanas #language-Dusner #language-Meoswar #language-Roon #language-Yeretuar #language-Yaur #language-Ambai #language-Ansus #language-Marau #language-Woi #language-Wamesa #language-Munggui #language-Papuma #language-Pom #language-Busami #language-Serui-Laut #language-Kurudu #language-Wabo #language-Yoke #language-As #language-Biga #language-Waigeo #language-Matbat #language-Kawe #language-Legenyem #language-Wauyai #language-Salawati #language-Buli (Indonesia) #language-Maba (Indonesia) #language-Patani #language-East Makian #language-Gane #language-Umiray Dumaget Agta #language-Bikol #language-Mamanwa #language-Alabat Island Agta #language-Isarog Agta #language-Mt. Iriga Agta #language-Mt. Iraya Agta #language-Bantoanon #language-Porohanon #language-Masbatenyo #language-Baybayanon #language-Kinabalian #language-Waray (Philippines) #language-Northern Binukidnon #language-Southern Binukidnon #language-Butuanon #language-Surigaonon #language-Tandaganon #language-Ata #language-Inonhan #language-Sulod #language-Cuyonon #language-Caluyanun #language-Davawenyo #language-Kamayo #language-Kagan Kalagan #language-Kalagan #language-Kasiguranin #language-Maranao #language-Bintauna #language-Kaidipang #language-Lolak #language-Suwawa #language-Mongondow #language-Ponosakan #language-Ata Manobo #language-Matigsalug Manobo #language-Agusan Manobo #language-Dibabawon Manobo #language-Rajah Kabunsuwan Manobo #language-Obo Manobo #language-Ilianen Manobo #language-Western Bukidnon Manobo #language-Tagabawa #language-Cotabato Manobo #language-Sarangani Manobo #language-Kagayanen #language-Higaonon #language-Tagbanwa #language-Batak #language-Central Tagbanwa #language-Molbog #language-Central Palawano #language-Brooke's Point Palawano #language-Southwest Palawano #language-Eastern Tawbuid #language-Western Tawbuid #language-Central Subanen #language-Eastern Subanen #language-Northern Subanen #language-Kolibugan Subanon #language-Western Subanon #language-Kawi #language-Caribbean Javanese #language-New Caledonian Javanese #language-Osing #language-Tengger #language-Agutaynen #language-Lampung Nyo #language-Lampung Api #language-Benyadu' #language-Rara Bakati' #language-Biatah Bidayuh #language-Tringgus-Sembaan Bidayuh #language-Bukar-Sadung Bidayuh #language-Ribun #language-Sanggau #language-Semandang #language-Sasak #language-Haroi #language-Eastern Cham #language-Western Cham #language-Cacgia Roglai #language-Chru #language-Southern Roglai #language-Northern Roglai #language-Tsat #language-Bih #language-Rade #language-Duano #language-Haji #language-Malayic Dayak #language-Old Malay #language-Keninjal #language-Seberuang #language-Beginci #language-Gerai #language-Cocos Islands Malay #language-Peranakan Indonesian #language-Kubu #language-Musi #language-Kota Bangun Kutai Malay #language-Banjar #language-Bukit Malay #language-Berau Malay #language-Sabah Malay #language-Bacanese Malay #language-Brunei #language-Jambi Malay #language-Bangka #language-Lubu #language-Negeri Sembilan Malay #language-Pekal #language-Balinese Malay #language-Jakun #language-Central Malay #language-Orang Kanaq #language-Orang Seletar #language-Tenggarong Kutai Malay #language-Kedah Malay #language-Pattani Malay #language-Standard Malay #language-Baba Malay #language-Makassar Malay #language-Malaccan Creole Malay #language-Kupang Malay #language-Larantuka Malay #language-Papuan Malay #language-Ambonese Malay #language-Banda Malay #language-Gorap #language-Manado Malay #language-North Moluccan Malay #language-Badui #language-Tonsawang #language-Tontemboan #language-Tondano #language-Tonsea #language-Moken #language-Moklen #language-Sikule #language-Batak Alas-Kluet #language-Batak Dairi #language-Batak Toba #language-Batak Angkola #language-Batak Mandailing #language-Alangan #language-Iraya #language-Tadyawan #language-Arta #language-Iloko #language-Isnag #language-Adasen #language-Ibanag #language-Faire Atta #language-Pamplona Atta #language-Pudtol Atta #language-Central Cagayan Agta #language-Itawit #language-Yogad #language-Ga'dang #language-Gaddang #language-Northern Alta #language-Southern Alta #language-Binongan Itneg #language-Inlaod Itneg #language-Lubuagan Kalinga #language-Butbut Kalinga #language-Tanudan Kalinga #language-Masadiit Itneg #language-Moyadan Itneg #language-Limos Kalinga #language-Banao Itneg #language-Mabaka Valley Kalinga #language-Balangao #language-Isinai #language-Bontok #language-Southern Bontok #language-Kankanaey #language-Maeng Itneg #language-Northern Kankanay #language-Amganad Ifugao #language-Tuwali Ifugao #language-Batad Ifugao #language-Mayoyao Ifugao #language-Ilongot #language-I-Wak #language-Kalanguya #language-Karao #language-Dupaninan Agta #language-Paranan #language-Dicamay Agta #language-Murik (Malaysia) #language-Bahau #language-Baram Kayan #language-Kayan River Kayan #language-Mendalam Kayan #language-Busang Kayan #language-Kayan Mahakam #language-Rejang Kayan #language-Modang #language-Segai #language-West Berawan #language-Central Berawan #language-East Berawan #language-Kiput #language-Tutong #language-Lelak #language-Kelabit #language-Lengilu #language-Lundayeh #language-Sa'ban #language-Tring #language-Uma' Lung #language-Uma' Lasan #language-Eastern Penan #language-Sebop #language-Western Penan #language-Bolongan #language-Bonggi #language-Ida'an #language-Lotud #language-Sabah Bisaya #language-Brunei Bisaya #language-Kimaragang #language-Klias River Kadazan #language-Kota Marudu Talantang #language-Kuijau #language-Tobilung #language-Kadazan Dusun #language-Minokok #language-Sugut Dusun #language-Rungus #language-Dumpas #language-Labuk-Kinabatangan Kadazan #language-Abai Sungai #language-Serudung Murut #language-Tombonuo #language-Lanas Lobu #language-Tampias Lobu #language-Upper Kinabatangan #language-Papar #language-Selungai Murut #language-Sembakung Murut #language-Gana #language-Paluan #language-Timugon Murut #language-Tagal Murut #language-Burusu #language-Northern Tidung #language-Southern Tidung #language-Sekapan #language-Kajaman #language-Lahanan #language-Central Melanau #language-Daro-Matu Melanau #language-Kanowit-Tanjong Melanau #language-Sibu Melanau #language-Aoheng #language-Kereho #language-Punan Aput #language-Punan Merah #language-Punan Batu 1 #language-Sihan #language-Bukat #language-Bukitan #language-Ukit #language-Punan Tubu #language-Punan Bah-Biau #language-Talaud #language-Sangir #language-Sangil #language-Bantik #language-Ratahan #language-Campalagian #language-Embaloh #language-Taman (Indonesia) #language-Coastal Konjo #language-Bentong #language-Makasar #language-Mamuju #language-Mandar #language-Maiwa (Indonesia) #language-Malimpung #language-Dakka #language-Pannei #language-Ulumanda' #language-Kalumpang #language-Mamasa #language-Tae' #language-Talondo' #language-Toraja-Sa'dan #language-Rampi #language-Bada (Indonesia) #language-Besoa #language-Napu #language-Seko Tengah #language-Seko Padang #language-Boano (Sulawesi) #language-Totoli #language-Kulon #language-Pazeh #language-Babuza #language-Papora #language-Central Aymara #language-Southern Aymara #language-Baibai #language-Kairak #language-Simbali #language-Ura (Papua New Guinea) #language-Makolkol #language-Guambiano #language-Totoro #language-Awa-Cuaiquer #language-Awbono #language-Bayono #language-Aduge #language-Ahirani #language-Anasi #language-Áncá #language-Arakwal #language-xss #language-Baga Kaloum #language-Baga Sobané #language-Bainouk-Samik #language-Bhalay #language-Bubia #language-Bumang #language-Buraka #language-Buso #language-Chetco #language-Chuanqiandian Cluster Miao #language-Con #language-Desiya #language-Foma #language-Fum #language-Gengle #language-Gowli #language-Gowlan #language-Idesa #language-Ihievbe #language-Inpui Naga #language-Ir #language-Jiarong #language-Judeo-Berber #language-Kang #language-Kayort #language-Kemiehua #language-Khao #language-Khua #language-Kisankasa #language-Kofa #language-Koko Babangk #language-Kon Keu #language-Kosena #language-Kpatili #language-Kuanhua #language-Kukna #language-Kuku-Mangk #language-Kumbaran #language-Laba #language-Lahta Karen #language-Lambichhong #language-Lang'e #language-Laopang #language-Laos Sign Language #language-Lenca #language-Loarki #language-Lopi #language-Lumba-Yakkha #language-Malay (individual language) #language-Mawayana #language-Mirgan #language-Munda #language-Nde-Gbite #language-Ndonde Hamba #language-Ngombe (Central African Republic) #language-nom #language-Norra #language-Northwestern Fars #language-tmk #language-Katukína #language-Nupbikha #language-Odut #language-Old Turkish #language-Olkol #language-Ontenu #language-Parsi #language-Parsi-Dari #language-Phangduwali #language-Pokangá #language-Puimei Naga #language-Punan Merap #language-Putoh #language-Quetzaltepec Mixe #language-Rufiji #language-Salumá #language-szd #language-Shuadit #language-Singapore Sign Language #language-Southwestern Nisu #language-Southern Lolopo #language-Southeastern Puebla Nahuatl #language-Tareng #language-Tawang Monpa #language-Tetete #language-Thu Lao #language-Tingui-Boto #language-Uradhi #language-Wahau Kayan #language-Xinca #language-Yamongeri #language-Yarsun #language-Yauma #language-Akyaung Ari Naga #language-Dawik Kui #language-Ekai Chin #language-Laitu Chin #language-Lao Naga #language-Ponyo-Gongwang Naga #language-Rungtu Chin #language-Songlai Chin #language-Ningera #language-Ainbai #language-Kilmeri #language-Pagi #language-Awyi #language-Amanab #language-Auwe #language-Daonda #language-Imonda #language-Senggi #language-Waris #language-Sowanda #language-Umeda #language-Umotína #language-Otuke #language-Kasua #language-Onobasulu #language-Sonia #language-Beami #language-Edolo #language-Gooniyandi #language-Kitsai #language-Pawnee #language-Apalaí #language-Galibi Carib #language-Akurio #language-Trió #language-Wayana #language-Kuikúro-Kalapálo #language-Matipuhy #language-Kaxuiâna #language-Hixkaryána #language-Waiwai #language-Bakairí #language-Tamanaku #language-Chaima #language-Mapoyo #language-Pémono #language-Yabarana #language-Macushi #language-Patamona #language-Akawaio #language-Waimiri-Atroari #language-Japrería #language-Ndrulo #language-Lombi #language-Asoa #language-Mamvu #language-Mangbutu #language-Bendi #language-Efe #language-Mvuba #language-Birri #language-Aringa #language-Avokaya #language-Logo #language-Lugbara #language-Keliko #language-Omi #language-Olu'bo #language-Southern Ma'di #language-Bongo #language-Baka (South Sudan) #language-Beli (South Sudan) #language-Mittu #language-Mo'da #language-Morokodo #language-Jur Modo #language-Nyamusa-Molo #language-Gula (Central African Republic) #language-Kara (Central African Republic) #language-Vale #language-Kenga #language-Jaya #language-Gula (Chad) #language-Morom #language-Berakou #language-Naba #language-Horo #language-Ngambay #language-Laka (Chad) #language-Gor #language-Mango #language-Dagba #language-Sara Kaba #language-Sara Kaba Náà #language-Sara Kaba Deme #language-Kulfa #language-Torá #language-Itene #language-Oro Win #language-Pech #language-Buglere #language-Ngäbere #language-Border Kuna #language-San Blas Kuna #language-Boruca #language-Cabécar #language-Cogui #language-Malayo #language-Angosturas Tunebo #language-Barro Negro Tunebo #language-Central Tunebo #language-Western Tunebo #language-Maléku Jaíka #language-Wasco-Wishram #language-Woun Meu #language-Emberá-Catío #language-Emberá-Baudó #language-Northern Emberá #language-Epena #language-Emberá-Tadó #language-Emberá-Chamí #language-Anserma #language-Caramanta #language-Alutor #language-Kerek #language-Barbareño #language-Ineseño #language-Purisimeño #language-Cochimi #language-Cocopa #language-Havasupai-Walapai-Yavapai #language-Mohave #language-Comecrudo #language-Garza #language-Onjob #language-Turaka #language-Maiwa (Papua New Guinea) #language-Daga #language-Mapena #language-Ginuman #language-Logorik #language-Dar Daju Daju #language-Dar Sila Daju #language-Njalgulgule #language-Baygo #language-Dar Fur Daju #language-Dizin #language-Nayi #language-Sheko #language-Donno So Dogon #language-Tommo So Dogon #language-Toro So Dogon #language-Bankan Tey Dogon #language-Ben Tey Dogon #language-Dogul Dom Dogon #language-Tebul Ure Dogon #language-Ana Tinga Dogon #language-Yanda Dom Dogon #language-Jamsay Dogon #language-Toro Tegu Dogon #language-Tomo Kan Dogon #language-Tiranige Diga Dogon #language-Ampari Dogon #language-Bunoge Dogon #language-Mombo Dogon #language-Doso #language-Turumsa #language-Northwestern Kolami #language-Southeastern Kolami #language-Mudhili Gadaba #language-Pottangi Ollar Gadaba #language-Kumarbhag Paharia #language-Sauria Paharia #language-Alu Kurumba #language-Holiya #language-Jennu Kurumba #language-Sholaga #language-Kannada #language-Kota (India) #language-Toda #language-Attapady Kurumba #language-Muduga #language-Kodava #language-Allar #language-Aranadan #language-Kadar #language-Kurichiya #language-Malankuravan #language-Malavedan #language-Malayalam #language-Malaryan #language-Mullu Kurumba #language-Thachanadan #language-Vishavan #language-Wayanad Chetti #language-Kalanadi #language-Kunduvadi #language-Pathiya #language-Ravula #language-Mala Malasar #language-Malapandaram #language-Old Tamil #language-Malasar #language-Mannan #language-Paliyan #language-Kaikadi #language-Pattapu #language-Yerukula #language-Korra Koraga #language-Mudu Koraga #language-Bellari #language-Kudiya #language-Northern Gondi #language-Eastern Muria #language-Western Muria #language-Adilabad Gondi #language-Aheri Gondi #language-Far Western Muria #language-Maria (India) #language-Dandami Maria #language-Konda-Dora #language-Kui (India) #language-Manda (India) #language-Pengo #language-Mukha-Dora #language-Waddar #language-Manna-Dora #language-Khirwar #language-Kamu #language-Kelo #language-Molo #language-Konai #language-Odoodee #language-Kubo #language-Samo #language-Fiwaga #language-Foi #language-Bine #language-Gizrra #language-Mednyj Aleut #language-Eastern Canadian Inuktitut #language-Kalaallisut #language-North Alaskan Inupiatun #language-Inuinnaqtun #language-Pacific Gulf Yupik #language-Garrwa #language-Wanyi #language-Bauzi #language-Demisa #language-Tefaro #language-Woria #language-Barapasi #language-Kofei #language-Sauri #language-Burate #language-Tunggare #language-Mangerr #language-Erre #language-Urningangg #language-Yemsa #language-Anfillo #language-Boro (Ethiopia) #language-Shekkacho #language-Chara #language-Koorete #language-Zayse-Zergulla #language-Basketo #language-Male (Ethiopia) #language-Dorze #language-Melo #language-Oyda #language-Wolaytta #language-Dawro #language-Gamo #language-Gofa #language-Mixed Great Andamanese #language-Cuiba #language-Playero #language-Kadiwéu #language-Abipon #language-Mocoví #language-Pilagá #language-Toba #language-Ngandi #language-Kunbarlang #language-Northern Haida #language-Southern Haida #language-Amarakaeri #language-Huachipaeri #language-Hatam #language-Ko #language-Warnang #language-Tira #language-Hibito #language-Jiongnai Bunu #language-Eastern Qiandong Miao #language-Northern Qiandong Miao #language-Southern Qiandong Miao #language-Eastern Xiangxi Miao #language-Western Xiangxi Miao #language-Bu-Nao Bunu #language-Ge #language-Luopohe Hmong #language-Hmong Daw #language-Horned Miao #language-Hmong Njua #language-Hmong Don #language-Hmong Dô #language-Northern Guiyang Hmong #language-Southern Guiyang Hmong #language-Southwestern Guiyang Hmong #language-Central Huishui Hmong #language-Eastern Huishui Hmong #language-Northern Huishui Hmong #language-Southwestern Huishui Hmong #language-Central Mashan Hmong #language-Northern Mashan Hmong #language-Southern Mashan Hmong #language-Western Mashan Hmong #language-Pa-Hng #language-Wunai Bunu #language-Younuo Bunu #language-Biao-Jiao Mien #language-Biao Mon #language-Kim Mun #language-Murui Huitoto #language-Hurrian #language-Urartian #language-Southeast Ijo #language-Nkoroo #language-Ibani #language-Kirike #language-Oruma #language-Biseni #language-Duriankere #language-Palaic #language-Carian #language-Cuneiform Luwian #language-Hieroglyphic Luwian #language-Pisidian #language-Lydian #language-Sidetic #language-Venetic #language-Gheg Albanian #language-Arbëreshë Albanian #language-Arvanitika Albanian #language-Classical Armenian #language-Middle Armenian #language-Western Armenian #language-Standard Latvian #language-Old Lithuanian #language-Old Russian #language-Church Slavic #language-Slavomolisano #language-Slovenian #language-Celtiberian #language-Galatian #language-Cisalpine Gaulish #language-Lepontic #language-Transalpine Gaulish #language-Middle Welsh #language-Old Welsh #language-Middle Breton #language-Old Breton #language-Old Cornish #language-Scottish Gaelic #language-Hiberno-Scottish Gaelic #language-Noric #language-Gothic #language-Elfdalian #language-Jutish #language-Old Norse #language-Norwegian Bokmål #language-Norwegian Nynorsk #language-Yiddish #language-Lower Silesian #language-Upper Saxon #language-Eastern Yiddish #language-Western Yiddish #language-Kölsch #language-Limburgan #language-Hunsrik #language-Pennsylvania German #language-Old High German (ca. 750-1050) #language-Colonia Tovar German #language-Swabian #language-Walser #language-Bavarian #language-Hutterite German #language-Unserdeutsch #language-Javindo #language-Petjo #language-Afrikaans #language-Oorlams #language-Berbice Creole Dutch #language-Negerhollands #language-Skepi Creole Dutch #language-Zeeuws #language-Old Dutch #language-Old Saxon #language-Low German #language-Middle Low German #language-Plautdietsch #language-Gronings #language-Achterhoeks #language-Drents #language-Sallands #language-Stellingwerfs #language-Twents #language-Veluws #language-Old English (ca. 450-1100) #language-Yola #language-Pitcairn-Norfolk #language-English #language-Virgin Islands Creole English #language-Bajan #language-Guyanese Creole English #language-Trinidadian Creole English #language-Antigua and Barbuda Creole English #language-Afro-Seminole Creole #language-Sea Island Creole English #language-Bahamas Creole English #language-Turks And Caicos Creole English #language-Vincentian Creole English #language-Grenadian Creole English #language-Tobagonian Creole English #language-Jamaican Creole English #language-Belize Kriol English #language-Nicaragua Creole English #language-Sranan Tongo #language-Kwinti #language-Krio #language-Ghanaian Pidgin English #language-Cameroon Pidgin #language-Nigerian Pidgin #language-Hawai'i Creole English #language-Kriol #language-Bislama #language-Pijin #language-Tok Pisin #language-Torres Strait Creole #language-Northern Frisian #language-Old Frisian #language-Western Frisian #language-Phrygian #language-Mycenaean Greek #language-Romano-Greek #language-Cappadocian Greek #language-Pontic #language-Mysian #language-Khowar #language-Sanskrit #language-Gawar-Bati #language-Shumashti #language-Grangali #language-Bhunjia #language-Kamar #language-Nahari #language-Kharia Thar #language-Lodhi #language-Tangchangya #language-Kurmukar #language-Naga Pidgin #language-Rajbanshi #language-Kupia #language-Lahnda #language-Western Panjabi #language-Northern Hindko #language-Southern Hindko #language-Pahari #language-Khetrani #language-Luwati #language-Sindhi Bhil #language-Lasi #language-Katkari #language-Goan Konkani #language-Old Marathi #language-Samvedi #language-Varhadi-Nagpuri #language-Andh #language-Rajasthani #language-Dubli #language-Kachi Koli #language-Vaghri #language-Wadiyara Koli #language-Merwari #language-Jandavra #language-Hadothi #language-Gade Lohar #language-Godwari #language-Marwari (India) #language-Bhaya #language-Goaria #language-Lambadi #language-Marwari (Pakistan) #language-Parkari Koli #language-Bauria #language-Dungra Bhil #language-Gamit #language-Mawchi #language-Vaagri Booli #language-Wagdi #language-Adiwasi Garasia #language-Rajput Garasia #language-Bhilali #language-Rathawi #language-Noiri #language-Dotyali #language-Jaunsari #language-Mandeali #language-Bhattiyali #language-Bilaspuri #language-Chambeali #language-Pangwali #language-Churahi #language-Bhadrawahi #language-Lahul Lohar #language-Kullu Pahari #language-Mahasu Pahari #language-Dhanki #language-Khandesi #language-Pali #language-Angika #language-Caribbean Hindustani #language-Kisan #language-Kudmali #language-Panchpargania #language-Oraon Sadri #language-Sadri #language-Rana Tharu #language-Chitwania Tharu #language-Kathoriya Tharu #language-Kochila Tharu #language-Dangaura Tharu #language-Sonha #language-Buksa #language-Majhi #language-Musasa #language-Kumhali #language-Darai #language-Dewas Rai #language-Powari #language-Surgujia #language-Domaaki #language-Balkan Romani #language-Baltic Romani #language-Caló #language-Kalo Finnish Romani #language-Braj #language-Kanauji #language-Bharia #language-Bundeli #language-Andaman Creole Hindi #language-Fiji Hindi #language-Hindi #language-Urdu #language-Ghera #language-Gurgula #language-Od #language-Khah #language-Wotapuri-Katarqalai #language-Indus Kohistani #language-Chilisso #language-Gowro #language-Mankiyali #language-Tirahi #language-Brokskat #language-Shina #language-Kohistani Shina #language-Ushojo #language-Savi #language-Dhivehi #language-Veddah #language-Avestan #language-Eastern Balochi #language-Koroshi #language-Southern Balochi #language-Western Balochi #language-Rudbari #language-Shahmirzadi #language-Gazi #language-Natanzi #language-Soi #language-Nayini #language-Lasgerdi #language-Sangisari #language-Sorkhei #language-Kurdish #language-Central Kurdish #language-Northern Kurdish #language-Southern Kurdish #language-Zaza #language-Gurani #language-Bajelani #language-Sarli #language-Kho'ini #language-Maraghei #language-Kajali #language-Kabatei #language-Upper Taromi #language-Harzani #language-Alviri-Vidari #language-Eshtehardi #language-Razajerdi #language-Takestani #language-Ashtiani #language-Vafsi #language-Old Ossetic #language-Yagnobi #language-Yazgulyam #language-Ormuri #language-Parachi #language-Waneci #language-Central Pashto #language-Northern Pashto #language-Southern Pashto #language-Khotanese #language-Tumshuqese #language-Old Persian (ca. 600-400 B.C.) #language-Pahlavi #language-Kumzari #language-Judeo-Tat #language-Muslim Tat #language-Judeo-Persian #language-Aimaq #language-Dari #language-Hazaragi #language-Bukharic #language-Lari #language-Dezfuli #language-Northern Luri #language-Bakhtiari #language-Southern Luri #language-Ashkun #language-Kamviri #language-Tregami #language-Faliscan #language-Latin #language-Istro Romanian #language-Megleno Romanian #language-Judeo-Italian #language-Sassarese Sardinian #language-Romagnol #language-Piemontese #language-Old French (842-ca. 1400) #language-Cajun French #language-Réunion Creole French #language-Tayo #language-Haitian #language-Guianese Creole French #language-Saint Lucian Creole French #language-Guadeloupean Creole French #language-San Miguel Creole French #language-Morisyen #language-Seselwa Creole French #language-Arpitan #language-Old Spanish #language-Ladino #language-Palenquero #language-Chavacano #language-Ternateño #language-Fala #language-Angolar #language-Principense #language-Sãotomense #language-Macanese #language-Timor Pidgin #language-Kabuverdianu #language-Papiamento #language-Upper Guinea Crioulo #language-Mozarabic #language-Gallurese Sardinian #language-Campidanese Sardinian #language-Logudorese Sardinian #language-Oscan #language-Umbrian #language-Hernican #language-Marrucinian #language-Paelignian #language-Vestinian #language-Sabine #language-South Picene #language-Aequian #language-Marsian #language-Volscian #language-Tokharian A #language-Tokharian B #language-Dacian #language-Lusitanian #language-Messapic #language-Thracian #language-Irántxe #language-Laurentian #language-Susquehannock #language-Nottoway #language-Wendat #language-Amurdak #language-Garig-Ilgar #language-Iwaidja #language-Old Japanese #language-Kikai #language-Oki-No-Erabu #language-Toku-No-Shima #language-Northern Amami-Oshima #language-Southern Amami-Oshima #language-Central Okinawan #language-Miyako #language-Jarawa (India) #language-Önge #language-Achuar-Shiwiar #language-Huambisa #language-Keiga #language-Tulishi #language-Krongo #language-Tumtum #language-Kanga #language-Katcha-Kadugli-Miri #language-Nukak Makú #language-Kamakan #language-Aekyom #language-Old Georgian #language-Judeo-Georgian #language-Katawixi #language-Kosadle #language-Qawasqar #language-Ap Ma #language-Eastern Keres #language-Western Keres #language-Korana #language-Xiri #language-Shua #language-Kua #language-Kxoe #language-Naro #language-Piro #language-Tiwa #language-Southern Tiwa #language-Bamu #language-Northeast Kiwai #language-Southern Kiwai #language-Waboda #language-Kerewo #language-Morigi #language-Ese #language-Ömie #language-Namiae #language-Barai #language-Biage #language-Mountain Koiali #language-Grass Koiari #language-Koitabu #language-Ndom #language-Kimaama #language-Uduk #language-Jejueo #language-Aja (South Sudan) #language-Bakwé #language-Wané #language-Gagnoa Bété #language-Kouya #language-Daloa Bété #language-Godié #language-Guiberoua Béte #language-Neyo #language-Yocoboué Dida #language-Lakota Dida #language-Kodia #language-Kuwaa #language-Mobumrin Aizi #language-Tiagbamrin Aizi #language-Southern Grebo #language-Northern Grebo #language-Barclayville Grebo #language-Central Grebo #language-Gboloo Grebo #language-Pye Krumen #language-Plapo Krumen #language-Tepo Krumen #language-Dewoin #language-Gbii #language-Tajuasohn #language-Nyabwa #language-Daho-Doo #language-Glaro-Twabo #language-Glio-Oubi #language-Sapo #language-Western Krahn #language-Wè Southern #language-Wè Western #language-Biangai #language-Kunimaipa #language-Weri #language-Mulaha #language-Humene #language-Uare #language-Isirawa #language-Bagusa #language-Kauwera #language-Trimuris #language-Airoran #language-Kwomtari #language-ǂHua #language-Awera #language-Rasawa #language-Saponi #language-Duvle #language-Edopi #language-Sikaritai #language-Doutai #language-Kaiy #language-Kwerisa #language-Papasena #language-Tause #language-Fayu #language-Owiniga #language-Ama (Papua New Guinea) #language-Nakwi #language-Nimo #language-Bo (Papua New Guinea) #language-Kembra #language-Lepki #language-Murkim #language-Wulna #language-Chambri #language-Yimas #language-Kopar #language-Murik (Papua New Guinea) #language-Banaro #language-Abu #language-Gorovu #language-Aiome #language-Anor #language-Breri #language-Romkun #language-Igana #language-Kominimung #language-Andarum #language-Tanguat #language-Tanggu #language-Borei #language-Awar #language-Bosngun #language-Watam #language-Massalat #language-Surbakhal #language-Karanga #language-Maba (Chad) #language-Kibet #language-Runga #language-Karon Dori #language-Northwest Maidu #language-Northeast Maidu #language-Valley Maidu #language-Laua #language-Morawa #language-Bauwaki #language-Mer #language-Mairasi #language-Semimi #language-Boko (Benin) #language-Bokobaru #language-Busa #language-Shanga #language-Matya Samo #language-Maya Samo #language-Southern Samo #language-Kla-Dan #language-Toura (Côte d'Ivoire) #language-Guro #language-Yaouré #language-Gbin #language-Mwan #language-Jalkunan #language-Ligbi #language-Tonjon #language-Bolon #language-Marka #language-Eastern Maninkakan #language-Konyanka Maninka #language-Manya #language-Sankaran Maninka #language-Mahou #language-Wojenaka #language-Worodougou #language-Koro (Côte d'Ivoire) #language-Koyaga #language-Mandinka #language-Kagoro #language-Kita Maninkakan #language-Jahanka #language-Western Maninkakan #language-Xaasongaxango #language-Kakabe #language-Kuranko #language-Lele (Guinea) #language-Kono (Sierra Leone) #language-Yalunka #language-Guinea Kpelle #language-Kono (Guinea) #language-Liberia Kpelle #language-Loma (Liberia) #language-Toma #language-Bandi #language-Mende (Sierra Leone) #language-Northern Bobo Madaré #language-Southern Bobo Madaré #language-Seeku #language-Bankagooma #language-Duungooma #language-Dzùùngoo #language-Kpeego #language-Jenaama Bozo #language-Tiemacèwè Bozo #language-Tiéyaxo Bozo #language-Sininkere #language-Mangarrayi #language-Alawa #language-Marra #language-Wandarang #language-Djeebbana #language-Burarra #language-Doromu-Koki #language-Maria (Papua New Guinea) #language-Hozo #language-Seze #language-Margu #language-Maca #language-Iyojwa'ja Chorote #language-Iyo'wujwa Chorote #language-Wichí Lhamtés Nocten #language-Wichí Lhamtés Vejoz #language-Wichí Lhamtés Güisnay #language-Kekchí #language-Uspanteco #language-Sacapulteco #language-Sipacapense #language-Tz'utujil #language-Cakchiquel-Quiché Mixed Language #language-K'iche' #language-Poqomam #language-Poqomchi' #language-Aguacateco #language-Ixil #language-Tektiteko #language-Epigraphic Mayan #language-Chol #language-Tabasco Chontal #language-Chortí #language-Tojolabal #language-Mocho #language-Popti' #language-Q'anjob'al #language-Itzá #language-Mopán Maya #language-Nungali #language-Gudanji #language-Wambaya #language-Mískito #language-Cacaopera #language-Matagalpa #language-Mayangna #language-Ulwa #language-Karkin #language-Plains Miwok #language-Central Sierra Miwok #language-Northern Sierra Miwok #language-Southern Sierra Miwok #language-Coast Miwok #language-Lake Miwok #language-Oluta Popoluca #language-Sayula Popoluca #language-Totontepec Mixe #language-Tlahuitoltepec Mixe #language-Coatlán Mixe #language-Isthmus Mixe #language-Mazatlán Mixe #language-Juquila Mixe #language-North Central Mixe #language-Chimalapa Zoque #language-Copainalá Zoque #language-Francisco León Zoque #language-Rayón Zoque #language-Highland Popoluca #language-Tabasco Zoque #language-Texistepec Popoluca #language-Yeniche #language-Gurindji Kriol #language-Media Lengua #language-Koneraw #language-Mombum #language-Kitan #language-Mogholi #language-Buriat #language-Mongolian #language-China Buriat #language-Mongolia Buriat #language-Russia Buriat #language-Halh Mongolian #language-Peripheral Mongolian #language-Kalmyk #language-East Yugur #language-Dongxiang #language-Kangjia #language-Monumbo #language-Smärky Kanum #language-Sota Kanum #language-Yei #language-Namat #language-Nambo #language-Neme #language-Nen #language-Nama (Papua New Guinea) #language-Namo #language-Arammba #language-Rema #language-Wára #language-Creek #language-Mikasuki #language-Apalachee #language-Nadëb #language-Dâw #language-Yuhup #language-Karata #language-Aghwan #language-Sabanê #language-Southern Nambikuára #language-Mamaindé #language-Lakondê #language-Latundê #language-Tawandê #language-Namla #language-Tofanma #language-Acheron #language-Torona #language-Boikin #language-Ngala #language-Ambulas #language-Hanga Hundi #language-Manambu #language-Koiwat #language-Sengo #language-Burui #language-Gaikundi #language-Sos Kundi #language-Kakwa #language-Mandari #language-Kuku #language-Imotong #language-Lango (South Sudan) #language-Logir #language-Okolie #language-Ngasa #language-Masai #language-Karamojong #language-Nyangatom #language-Kalenjin #language-Kipsigis #language-Nandi #language-Markweeta #language-Pökoot #language-Okiek #language-Burun #language-Jumjum #language-Mabaan #language-Northeastern Dinka #language-Northwestern Dinka #language-Southwestern Dinka #language-South Central Dinka #language-Southeastern Dinka #language-Anuak #language-Belanda Bor #language-Luwo #language-Thuri #language-Acoli #language-Adhola #language-Luo (Kenya and Tanzania) #language-Kumam #language-Lango (Uganda) #language-Mlap #language-Gresi #language-Kemtuik #language-Tabaru #language-Galela #language-Modole #language-Kao #language-Pagu #language-Tobelo #language-Tugutil #language-Ibu #language-Sahu #language-Waioli #language-Tidore #language-Rotokas #language-Old Nubian #language-Midob #language-Birked #language-Dair #language-Kadaru #language-El Hugeirat #language-Karko #language-Wali (Sudan) #language-Keoru-Ahia #language-Opao #language-Orokolo #language-Beli (Papua New Guinea) #language-Laeko-Libuat #language-Urim #language-Wom (Papua New Guinea) #language-Au #language-Elkei #language-Olo #language-Urat #language-Bumbita Arapesh #language-Abu' Arapesh #language-Bukiyip #language-Yambes #language-Eitiep #language-Kombio #language-Aruek #language-Buna #language-Bungain #language-Kamasau #language-Urimo #language-Ningil #language-Yil #language-Bragat #language-Ambrak #language-Yangum Gel #language-Yangum Mon #language-Yangum Dey #language-Gnau #language-Seta #language-Seti #language-Kwamtim One #language-Southern One #language-Inebu One #language-Kabore One #language-Molmo One #language-Northern One #language-Agi #language-Yau (Sandaun Province) #language-Yis #language-Guhu-Samane #language-Yekora #language-Suena #language-Zia #language-Binandere #language-Ewage-Notu #language-Doghoro #language-Gaina #language-Korafe-Yegha #language-Aeka #language-Hunjara-Kaina Ke #language-Orokaiva #language-Kamoro #language-Sempan #language-Central Asmat #language-Yaosakor Asmat #language-Citak #language-Diuwe #language-Tamnim Citak #language-Buruwai #language-Asue Awyu #language-Edera Awyu #language-North Awyu #language-South Awyu #language-Aghu #language-Central Awyu #language-Ketum #language-Wambon #language-Mandobo Atas #language-Mandobo Bawah #language-Kombai #language-Wanggom #language-Sawi #language-Komyandaret #language-Kopkaka #language-Burumakok #language-Kwer #language-North Muyu #language-South Muyu #language-Bimin #language-Faiwol #language-Setaman #language-Telefol #language-Tifal #language-Urapmin #language-Mian #language-Suganga #language-Nakai #language-Tangko #language-Imbongu #language-Umbu-Ungu #language-Bo-Ung #language-Melpa #language-Maring #language-Kandawo #language-Narak #language-Chuave #language-Nomane #language-Golin #language-Sinasina #language-North Wahgi #language-Wahgi #language-Nggem #language-Wano #language-Mid Grand Valley Dani #language-Hupla #language-Lower Grand Valley Dani #language-Upper Grand Valley Dani #language-Walak #language-Nduga #language-Angguruk Yali #language-Ninia Yali #language-Pass Valley Yali #language-Enga #language-Ipili #language-Kyaka #language-Lembena #language-Mae #language-Sari #language-Bisorio #language-Nete #language-Huli #language-Samberigi #language-Angal Heneng #language-Angal Enen #language-West Kewa #language-East Kewa #language-Erave #language-Mungkip #language-Numanggang #language-Nek #language-Nuk #language-Finongan #language-Mamaa #language-Nimi #language-Ma Manda #language-Nekgini #language-Neko #language-Ufim #language-Ngaing #language-Nukna #language-Som #language-Weliki #language-Yau (Morobe Province) #language-Tuma-Irumu #language-Awara #language-Forak #language-Degenan #language-Asaro'o #language-Bulgebi #language-Guya #language-Yagomi #language-Nankina #language-Ma (Papua New Guinea) #language-Bonkiman #language-Yopno #language-Yout Wam #language-Ono #language-Sialum #language-Kovai #language-Sene #language-Kâte #language-Mape #language-Migabac #language-Momare #language-Nomu #language-Kinalakna #language-Kumukio #language-Timbe #language-Selepet #language-Mese #language-Nabak #language-Dedua #language-Tobo #language-Gende #language-Fore #language-Gimi (Eastern Highlands) #language-Dano #language-Tokano #language-Benabena #language-Siane #language-Yaweyuha #language-Inoke-Yate #language-Kamano #language-Kanite #language-Keyagana #language-Yagaria #language-Abaga #language-Isabi #language-Usarufa #language-Awa (Papua New Guinea) #language-Agarabi #language-Gadsup #language-North Tairora #language-South Tairora #language-Waffa #language-Kambaira #language-Kenati #language-Amaimon #language-Korak #language-Waskia #language-Maiani #language-Mala (Papua New Guinea) #language-Miani #language-Bepour #language-Moere #language-Kowaki #language-Mawak #language-Yaben #language-Ukuriguma #language-Yarawata #language-Kare (Papua New Guinea) #language-Gumalu #language-Bau #language-Isebe #language-Panim #language-Baimak #language-Gal #language-Garus #language-Rempi #language-Yoidik #language-Bagupi #language-Mawan #language-Saruga #language-Silopi #language-Utu #language-Matepi #language-Nake #language-Rapting #language-Mosimo #language-Murupi #language-Samosa #language-Wamas #language-Munit #language-Kobon #language-Kalam #language-Tai #language-Wadaginam #language-Anam #language-Moresada #language-Kesawai #language-Sausi #language-Arawum #language-Lemio #language-Pulabu #language-Siroi #language-Bongu #language-Male (Papua New Guinea) #language-Jilim #language-Rerau #language-Yangulam #language-Danaru #language-Urigina #language-Biyom #language-Wasembo #language-Ganglau #language-Saep #language-Yabong #language-Eipomek #language-Una #language-Korupun-Sela #language-Kosarek Yale #language-Nipsan #language-Moni #language-Wolani #language-Auye #language-Dao #language-Ofayé #language-Krenak #language-Acroá #language-Xakriabá #language-Xavánte #language-Xerénte #language-Xokleng #language-São Paulo Kaingáng #language-Kayapó #language-Krahô #language-Pataxó Hã-Ha-Hãe #language-Koropó #language-Afitti #language-Ama (Sudan) #language-Warrwa #language-Ngumbarl #language-Dyugun #language-Yawuru #language-Nimanbur #language-Bardi #language-Djawi #language-Dyaberdyaber #language-Nyulnyul #language-Ipalapa Amuzgo #language-San Pedro Amuzgos Amuzgo #language-Tepeuxila Cuicatec #language-Teutila Cuicatec #language-Amoltepec Mixtec #language-Mixtepec Mixtec #language-Tezoatlán Mixtec #language-Northwest Oaxaca Mixtec #language-Silacayoapan Mixtec #language-Chayuco Mixtec #language-Ixtayutla Mixtec #language-Jamiltepec Mixtec #language-San Juan Colorado Mixtec #language-Tututepec Mixtec #language-Pinotepa Nacional Mixtec #language-Santa María Zacatepec Mixtec #language-Diuxi-Tilantongo Mixtec #language-Mitlatongo Mixtec #language-Peñoles Mixtec #language-Tlazoyaltepec Mixtec #language-Huitepec Mixtec #language-San Miguel Piedras Mixtec #language-Sindihui Mixtec #language-Tamazola Mixtec #language-Yutanduchi Mixtec #language-Alacatlatzala Mixtec #language-Alcozauca Mixtec #language-Metlatónoc Mixtec #language-Yoloxochitl Mixtec #language-Apasco-Apoala Mixtec #language-Southeastern Nochixtlán Mixtec #language-Soyaltepec Mixtec #language-Coatzospan Mixtec #language-Cuyamecalco Mixtec #language-Tidaá Mixtec #language-Cacaloxtepec Mixtec #language-Chazumba Mixtec #language-Chigmecatitlán Mixtec #language-Southern Puebla Mixtec #language-Ayutla Mixtec #language-Juxtlahuaca Mixtec #language-Western Juxtlahuaca Mixtec #language-Atatláhuca Mixtec #language-Itundujia Mixtec #language-Magdalena Peñasco Mixtec #language-Northern Tlaxiaco Mixtec #language-Ocotepec Mixtec #language-San Juan Teita Mixtec #language-San Miguel El Grande Mixtec #language-Santa Lucía Monteverde Mixtec #language-Sinicahua Mixtec #language-Southwestern Tlaxiaco Mixtec #language-Tijaltepec Mixtec #language-Yosondúa Mixtec #language-Yucuañe Mixtec #language-Chicahuaxtla Triqui #language-Copala Triqui #language-San Martín Itunyoso Triqui #language-Chochotec #language-Mezontla Popoloca #language-San Juan Atzingo Popoloca #language-San Luís Temalacayuca Popoloca #language-Coyotepec Popoloca #language-San Felipe Otlaltepec Popoloca #language-Santa Inés Ahuatempan Popoloca #language-Soyaltepec Mazatec #language-San Jerónimo Tecóatl Mazatec #language-Chiquihuitlán Mazatec #language-Jalapa De Díaz Mazatec #language-Ayautla Mazatec #language-Ixcatlán Mazatec #language-Huautla Mazatec #language-Mazatlán Mazatec #language-Zapotec #language-Zenzontepec Chatino #language-Tataltepec Chatino #language-Eastern Highland Chatino #language-Nopala Chatino #language-Western Highland Chatino #language-Zacatepec Chatino #language-Asunción Mixtepec Zapotec #language-Ayoquesco Zapotec #language-Mazaltepec Zapotec #language-Mitla Zapotec #language-San Pedro Quiatoni Zapotec #language-Santa Catarina Albarradas Zapotec #language-Santo Domingo Albarradas Zapotec #language-Tejalapan Zapotec #language-Lapaguía-Guivini Zapotec #language-Santa María Quiegolani Zapotec #language-Santiago Xanica Zapotec #language-Xadani Zapotec #language-Xanaguía Zapotec #language-Mixtepec Zapotec #language-Guevea De Humboldt Zapotec #language-Petapa Zapotec #language-Lachiguiri Zapotec #language-Quiavicuzas Zapotec #language-Chichicapan Zapotec #language-Güilá Zapotec #language-Western Tlacolula Valley Zapotec #language-Isthmus Zapotec #language-Ocotlán Zapotec #language-Zaachila Zapotec #language-Santa Inés Yatzechi Zapotec #language-Tilquiapan Zapotec #language-Yautepec Zapotec #language-Loxicha Zapotec #language-Ozolotepec Zapotec #language-San Agustín Mixtepec Zapotec #language-Choapan Zapotec #language-Cajonos Zapotec #language-Tabaa Zapotec #language-Yalálag Zapotec #language-Yatzachi Zapotec #language-Zoogocho Zapotec #language-Rincón Zapotec #language-Yatee Zapotec #language-Las Delicias Zapotec #language-Southern Rincon Zapotec #language-Aloápam Zapotec #language-Sierra de Juárez Zapotec #language-Southeastern Ixtlán Zapotec #language-Yareni Zapotec #language-Coatecas Altas Zapotec #language-Amatlán Zapotec #language-Tlacolulita Zapotec #language-San Vicente Coatlán Zapotec #language-Coatlán Zapotec #language-San Baltazar Loxicha Zapotec #language-Elotepec Zapotec #language-Texmelucan Zapotec #language-Zaniza Zapotec #language-Totomachapan Zapotec #language-El Alto Zapotec #language-Lachixío Zapotec #language-Ojitlán Chinantec #language-Sochiapam Chinantec #language-Usila Chinantec #language-Chiltepec Chinantec #language-Tlacoatzintepec Chinantec #language-Palantla Chinantec #language-Tepetotutla Chinantec #language-Ozumacín Chinantec #language-Valle Nacional Chinantec #language-Lalana Chinantec #language-Lealao Chinantec #language-Tepinapa Chinantec #language-Comaltepec Chinantec #language-Quiotepec Chinantec #language-Chichimeca-Jonaz #language-Atzingo Matlatzinca #language-San Francisco Matlatzinca #language-Central Mazahua #language-Michoacán Mazahua #language-Eastern Highland Otomi #language-Tenango Otomi #language-Texcatepec Otomi #language-Mezquital Otomi #language-Querétaro Otomi #language-Ixtenco Otomi #language-Tilapa Otomi #language-Estado de México Otomi #language-Temoaya Otomi #language-Central Pame #language-Northern Pame #language-Southern Pame #language-Chiapanec #language-Subtiaba #language-Azoyú Me'phaa #language-Malinaltepec Me'phaa #language-Acatepec Me'phaa #language-Tlacoapa Me'phaa #language-Idi #language-Atsugewi #language-Dyirbal #language-Kala Lagaw Ya #language-Kaytetye #language-Lower Southern Aranda #language-Alyawarr #language-Andegerebinha #language-Anmatyerre #language-Eastern Arrernte #language-Western Arrarnta #language-Ayerrerenge #language-Wirangu #language-Banggarla #language-Guyani #language-Narungga #language-Nauo #language-Ngadjuri #language-Nugunu (Australia) #language-Warumungu #language-Mangala #language-Nyangumarta #language-Warlpiri #language-Warlmanpa #language-Walmajarri #language-Gurindji #language-Mudburra #language-Jaru #language-Ngardi #language-Martu Wangka #language-Kukatja #language-Pintupi-Luritja #language-Ngaanyatjarra #language-Pitjantjatjara #language-Yankunytjatjara #language-Antakarinya #language-Kokata #language-Jandai #language-Yagara #language-Bigambal #language-Yugambal #language-Kalkutung #language-Yalarnnga #language-Yanda #language-Biri #language-Gangulu #language-Gugu Badhun #language-Gungabula #language-Guwamu #language-Kunggari #language-Mandandanyi #language-Wadjigu #language-Yandjibara #language-Gunya #language-Margany #language-Punthamara #language-Wangkumara #language-Pirlatapa #language-Dieri #language-Ngamini #language-Yarluyandi #language-Yandruwandha #language-Yawarawarga #language-Nhirrpi #language-Arabana #language-Pitta Pitta #language-Pirriya #language-Dyangadi #language-Nganyaywana #language-Yanyuwa #language-Thawa #language-Wagaya #language-Yindjilandji #language-Nyawaygi #language-Yuru #language-Gugadj #language-Ikaranggal #language-Tagalaka #language-Thaypan #language-Pakanha #language-Wikngenchera #language-Kanju #language-Kuuku-Ya'u #language-Umbindhamu #language-Flinders Island #language-Wik-Epa #language-Wik-Me'anha #language-Wik-Iiyanh #language-Wik-Mungkan #language-Kuku-Uwanh #language-Kuku-Ugbanh #language-Kuku-Mu'inh #language-Wikalkan #language-Lamalama #language-Mayaguduna #language-Ngawun #language-Mayi-Thakurti #language-Mayi-Yapi #language-Mayi-Kulan #language-Wunumara #language-Mbara (Australia) #language-Walangama #language-Kuthant #language-Areba #language-Yinwum #language-Anguthimri #language-Awngthim #language-Ndra'ngith #language-Gudang #language-Atampaya #language-Angkamuthi #language-Alngith #language-Mpalitjanh #language-Gugubera #language-Kuuk-Yak #language-Bayali #language-Dharumbal #language-Mirning #language-Yinggarda #language-Nhanda #language-Badimaya #language-Malgana #language-Wajarri #language-Kalaamaya #language-Ngadjunmaya #language-Kalarko #language-Bibbulman #language-Goreng #language-Pinjarup #language-Wajuk #language-Wardandi #language-Bayungu #language-Pinigura #language-Burduna #language-Dhalandji #language-Djiwarli #language-Thiin #language-Dhargari #language-Wariyangga #language-Nhuwala #language-Tjurruru #language-Kariyarra #language-Ngarluma #language-Yinhawangka #language-Kurrama #language-Yindjibarndi #language-Ngarla #language-Nyamal #language-Bandjalang #language-Muruwari #language-Kuri #language-Awabakal #language-Worimi #language-Birrpayi #language-Gundungurra #language-Ngunawal #language-Dhurga #language-Jaitmatang #language-Ngarigu #language-Kumbainggar #language-Yaygir #language-Gureng Gureng #language-Dhungaloo #language-Wakawaka #language-Wuliwuli #language-Dhudhuroa #language-Pallanganmiddang #language-Yabula Yabula #language-Wathawurrung #language-Ladji Ladji #language-Madhi Madhi #language-Nari Nari #language-Wadi Wadi #language-Wotjobaluk #language-Wergaia #language-Daungwurrung #language-Woiwurrung #language-Bunganditj #language-Dadi Dadi #language-Yitha Yitha #language-Malyangapa #language-Wadikali #language-Yardliyawarra #language-Guugu Yimidhirr #language-Djangun #language-Kuku-Yalanji #language-Muluridyi #language-Dayi #language-Dhangu-Djangu #language-Djambarrpuyngu #language-Gupapuyngu #language-Dhuwal #language-Gumatj #language-Dhuwaya #language-Djinba #language-Djinang #language-Golpa #language-Yan-nhangu #language-Cashibo-Cacataibo #language-Kaxararí #language-Tuxináwa #language-Chácobo #language-Karipuna #language-Pacahuara #language-Panobo #language-Sensi #language-Capanahua #language-Shipibo-Conibo #language-Amahuaca #language-Cashinahua #language-Shanenawa #language-Sharanahua #language-Yaminahua #language-Yawanawa #language-Yora #language-Atsahuaca #language-Marúbo #language-Panoan Katukína #language-Isconahua #language-Nukuini #language-Poyanáwa #language-Matís #language-Korubo #language-Kulina Pano #language-Cavineña #language-Tacana #language-Araona #language-Toromono #language-Emumu #language-Karkar-Yuri #language-Yafi #language-Dubu #language-Towei #language-Pinai-Hagahai #language-Nefamese #language-Mobilian #language-Pidgin Delaware #language-Chinese Pidgin English #language-Tay Boi #language-Barikanchi #language-Gibanawa #language-Broome Pearling Lugger Pidgin #language-Hiri Motu #language-Ndyuka-Trio Pidgin #language-Fanagalo #language-Southeastern Pomo #language-Central Pomo #language-Northern Pomo #language-Southern Pomo #language-Puri #language-Pacaraos Quechua #language-Cajatambo North Lima Quechua #language-Chiquián Ancash Quechua #language-Huallaga Huánuco Quechua #language-Margos-Yarowilca-Lauricocha Quechua #language-Panao Huánuco Quechua #language-Huamalíes-Dos de Mayo Huánuco Quechua #language-Huaylas Ancash Quechua #language-Northern Conchucos Ancash Quechua #language-Southern Conchucos Ancash Quechua #language-Corongo Ancash Quechua #language-Sihuas Ancash Quechua #language-Huaylla Wanca Quechua #language-Jauja Wanca Quechua #language-Ambo-Pasco Quechua #language-North Junín Quechua #language-Santa Ana de Tusi Pasco Quechua #language-Cajamarca Quechua #language-Lambayeque Quechua #language-Classical Quechua #language-Chachapoyas Quechua #language-San Martín Quechua #language-Arequipa-La Unión Quechua #language-Ayacucho Quechua #language-North Bolivian Quechua #language-Santiago del Estero Quichua #language-South Bolivian Quechua #language-Calderón Highland Quichua #language-Salasaca Highland Quichua #language-Loja Highland Quichua #language-Cañar Highland Quichua #language-Imbabura Highland Quichua #language-Napo Lowland Quechua #language-Tena Lowland Quichua #language-Northern Pastaza Quichua #language-Southern Pastaza Quechua #language-Cusco Quechua #language-Eastern Apurímac Quechua #language-Puno Quechua #language-Chincha Quechua #language-Yauyos Quechua #language-Tegali #language-Tenino #language-Umatilla #language-Berti #language-Kube #language-Kanembu #language-Tarjumo #language-Tumari Kanuri #language-Central Kanuri #language-Bilma Kanuri #language-Manga Kanuri #language-Dazaga #language-Tedaga #language-Bella Coola #language-Halkomelem #language-Sechelt #language-Straits Salish #language-Southern Puget Sound Salish #language-Skagit #language-Snohomish #language-Clallam #language-Cowlitz #language-Columbia-Wenatchi #language-Kalispel-Pend d'Oreille #language-Spokane #language-Sáliba #language-Maco #language-Dera (Indonesia) #language-Nafri #language-Sentani #language-Abau #language-Amal #language-Iwam #language-Chenapian #language-Wogamusin #language-Kwoma #language-Kwanga #language-Mende (Papua New Guinea) #language-Awtuw #language-Karawa #language-Pouye #language-Ayi (Papua New Guinea) #language-Pasi #language-Mehek #language-Bahinemo #language-Bisis #language-Mari (East Sepik Province) #language-Sumariup #language-Kapriman #language-Alamblak #language-Kaningra #language-Saniyo-Hiyewe #language-Hewa #language-Niksek #language-Piame #language-Ak #language-Namia #language-Shasta #language-Armenian Sign Language #language-Australian Aborigines Sign Language #language-Monastic Sign Language #language-Plains Indian Sign Language #language-Afghan Sign Language #language-Albanian Sign Language #language-Argentine Sign Language #language-Cambodian Sign Language #language-Guatemalan Sign Language #language-Hausa Sign Language #language-Maltese Sign Language #language-Mauritian Sign Language #language-Mozambican Sign Language #language-Nicaraguan Sign Language #language-Penang Sign Language #language-Sri Lankan Sign Language #language-Tanzanian Sign Language #language-Tibetan Sign Language #language-Turkish Sign Language #language-Zambian Sign Language #language-Zimbabwe Sign Language #language-Egypt Sign Language #language-Libyan Sign Language #language-Saudi Arabian Sign Language #language-Maritime Sign Language #language-British Sign Language #language-New Zealand Sign Language #language-Auslan #language-Papua New Guinean Sign Language #language-Namibian Sign Language #language-South African Sign Language #language-Chilean Sign Language #language-Paraguayan Sign Language #language-Uruguayan Sign Language #language-Hanoi Sign Language #language-Ho Chi Minh City Sign Language #language-Chinese Sign Language #language-German Sign Language #language-Israeli Sign Language #language-Polish Sign Language #language-Swiss-German Sign Language #language-Nepalese Sign Language #language-Indian Sign Language #language-Pakistan Sign Language #language-Japanese Sign Language #language-Korean Sign Language #language-Taiwan Sign Language #language-Algerian Sign Language #language-Austrian Sign Language #language-Brazilian Sign Language #language-Estonian Sign Language #language-French Sign Language #language-Greek Sign Language #language-Irish Sign Language #language-Latvian Sign Language #language-Mexican Sign Language #language-Philippine Sign Language #language-Swiss-French Sign Language #language-Dominican Sign Language #language-Ethiopian Sign Language #language-Ghanaian Sign Language #language-Guinean Sign Language #language-Moroccan Sign Language #language-Puerto Rican Sign Language #language-Quebec Sign Language #language-Salvadoran Sign Language #language-Sierra Leone Sign Language #language-Thai Sign Language #language-Trinidad and Tobago Sign Language #language-American Sign Language #language-Jamaican Sign Language #language-Costa Rican Sign Language #language-Honduras Sign Language #language-Panamanian Sign Language #language-Malaysian Sign Language #language-Selangor Sign Language #language-Chadian Sign Language #language-Nigerian Sign Language #language-Rwandan Sign Language #language-Ugandan Sign Language #language-Bolivian Sign Language #language-Colombian Sign Language #language-Ecuadorian Sign Language #language-Peruvian Sign Language #language-Catalan Sign Language #language-Valencian Sign Language #language-Bulgarian Sign Language #language-Czech Sign Language #language-Hungarian Sign Language #language-Romanian Sign Language #language-Slovakian Sign Language #language-Dutch Sign Language #language-Langue des signes de Belgique Francophone #language-Vlaamse Gebarentaal #language-Italian Sign Language #language-Swiss-Italian Sign Language #language-Tunisian Sign Language #language-Danish Sign Language #language-Icelandic Sign Language #language-Madagascar Sign Language #language-Norwegian Sign Language #language-Yugoslavian Sign Language #language-Haiphong Sign Language #language-Chiangmai Sign Language #language-Lithuanian Sign Language #language-Moldova Sign Language #language-Mongolian Sign Language #language-Ukrainian Sign Language #language-Russian Sign Language #language-Spanish Sign Language #language-Venezuelan Sign Language #language-Portuguese Sign Language #language-Swedish Sign Language #language-Finland-Swedish Sign Language #language-Finnish Sign Language #language-Cuba Sign Language #language-International Sign #language-Adamorobe Sign Language #language-Albarradas Sign Language #language-Al-Sayyid Bedouin Sign Language #language-Ban Khor Sign Language #language-Bribri Sign Language #language-Brunca Sign Language #language-Ghandruk Sign Language #language-Inuit Sign Language #language-Jamaican Country Sign Language #language-Jhankot Sign Language #language-Jumla Sign Language #language-Mardin Sign Language #language-Martha's Vineyard Sign Language #language-Miriwoong Sign Language #language-Miyakubo Sign Language #language-Old Kentish Sign Language #language-Seychelles Sign Language #language-Sivia Sign Language #language-Solomon Islands Sign Language #language-Tebul Sign Language #language-Urubú-Kaapor Sign Language #language-Yucatec Maya Sign Language #language-Providencia Sign Language #language-Olekha #language-Dakpakha #language-Dzalakha #language-Chalikha #language-Bumthangkha #language-Khengkha #language-Kurtokha #language-Classical Tibetan #language-Zangskari #language-Purik #language-Tibetan #language-Humla #language-Lhomi #language-Walungge #language-Dolpo #language-Tichurong #language-Tsum #language-Kyerung #language-Mugom #language-Jirel #language-Naaba #language-Khams Tibetan #language-Tseku #language-Bhoti Kinnauri #language-Stod Bhoti #language-Jad #language-Spiti Bhoti #language-Brokpake #language-Chocangacakha #language-Groma #language-Dzongkha #language-Layakha #language-Lunanakha #language-Khamba #language-Amdo Tibetan #language-Kaike #language-Northern Ghale #language-Southern Ghale #language-Eastern Gorkha Tamang #language-Seke (Nepal) #language-Gurung #language-Nar Phu #language-Chantyal #language-Eastern Tamang #language-Western Tamang #language-Rongpo #language-Rangkas #language-Chaudangsi #language-Byangsi #language-Kanashi #language-Tukpa #language-Jangshung #language-Shumcho #language-Pattani #language-Kalaktang Monpa #language-Tshangla #language-Kok Borok #language-Riang (India) #language-Tippera #language-Usui #language-Kachari #language-Atong (India) #language-Koch #language-Ruga #language-Chak #language-Kadu #language-Taman (Myanmar) #language-Chang Naga #language-Konyak Naga #language-Phom Naga #language-Wancho Naga #language-Khiamniungan Naga #language-Leinong Naga #language-Makyan Naga #language-Nocte Naga #language-Tutsa Naga #language-Ugong #language-Hpon #language-Maru #language-Pela #language-Taungyo #language-Danu #language-Intha #language-Old Burmese #language-Tavoyan #language-Marma #language-Pholo #language-Phana' #language-Bisu #language-Laomian #language-Pyen #language-Côông #language-Honi #language-Biyo #language-Enu #language-Kaduo #language-Akeu #language-Akha #language-Chepya #language-Muda #language-Sila #language-Buyuan Jinuo #language-Youle Jinuo #language-Kucong #language-Lahu Shi #language-Katso #language-Samatao #language-Lawu #language-Miqie #language-Limi #language-Mili #language-Sonaga #language-Kuamasi #language-Kua-nsi #language-Dongshanba Lalo #language-Western Lalu #language-Xishanba Lalo #language-Eastern Lalu #language-Lamu #language-Naluo Yi #language-Laghuu #language-Thopho #language-Qila Muji #language-Bokha #language-Phuma #language-Northern Muji #language-Southern Muji #language-Ani Phowa #language-Labo Phowa #language-Hlepho Phowa #language-Khlula #language-Zokhuo #language-Southern Nisu #language-Eastern Nisu #language-Northern Nisu #language-Sichuan Yi #language-Gepo #language-Samei #language-Sanie #language-Wuding-Luquan Yi #language-Ayizi #language-Chesu #language-Wumeng Nasu #language-Wusa Nasu #language-Aluo #language-Ache #language-Alugu #language-Phupa #language-Phuza #language-Phala #language-Alo Phola #language-Azha #language-Axi Yi #language-Azhe #language-Nisi (China) #language-Nusu #language-Zauzou #language-Ersu #language-Narua #language-Queyu #language-Northern Pumi #language-Southern Pumi #language-Southern Qiang #language-Northern Tujia #language-Southern Tujia #language-Toto #language-Lepcha #language-Lhokpu #language-Dura #language-Gamale Kham #language-Sheshi Kham #language-Eastern Parbate Kham #language-Western Parbate Kham #language-Eastern Magar #language-Western Magar #language-Saam #language-Sampang #language-Chukwa #language-Kulung (Nepal) #language-Nachering #language-Camling #language-Dungmali #language-Waling #language-Chhulung #language-Athpariya #language-Belhariya #language-Lohorung #language-Southern Yamphu #language-Yamphu #language-Eastern Meohang #language-Western Meohang #language-Jerung #language-Bahing #language-Wayu #language-Dumi #language-Baraamu #language-Mobwa Karen #language-Geba Karen #language-Manumanaw Karen #language-Yintale Karen #language-Eastern Kayah #language-Western Kayah #language-Geko Karen #language-Yinbaw Karen #language-Pa'o Karen #language-Pwo Eastern Karen #language-Pwo Western Karen #language-Phrae Pwo Karen #language-Pwo Northern Karen #language-Paku Karen #language-Wewaw #language-Bugun #language-Manipuri #language-Khezha Naga #language-Angami Naga #language-Chokri Naga #language-Mao Naga #language-Poumei Naga #language-Northern Rengma Naga #language-Pochuri Naga #language-Southern Rengma Naga #language-Sumi Naga #language-Ao Naga #language-Lotha Naga #language-Sangtam Naga #language-Jejara Naga #language-Yimchungru Naga #language-Long Phuri Naga #language-Makuri Naga #language-Amri Karbi #language-Bawm Chin #language-Bualkhaw Chin #language-Falam Chin #language-Biete #language-Darlong #language-Hmar #language-Senthang Chin #language-Zotung Chin #language-Mara Chin #language-Shendu #language-Aimol #language-Anal #language-Kom (India) #language-Monsang Naga #language-Ranglong #language-Eastern Khumi Chin #language-Khumi Chin #language-Ngawn Chin #language-Zou #language-Gangte #language-Vaiphei #language-Kharam Naga #language-Paite Chin #language-Purum #language-Ralte #language-Tedim Chin #language-Thado Chin #language-Asho Chin #language-Sumtu Chin #language-Chinbon Chin #language-Daai Chin #language-Kaang Chin #language-Mün Chin #language-Maring Naga #language-Maram Naga #language-Rongmei Naga #language-Thangal Naga #language-Liangmai Naga #language-Mzieme Naga #language-Zeme Naga #language-Galo #language-Na #language-Tagin #language-Central Bai #language-Southern Bai #language-Mru #language-Drung #language-Raji #language-Raute #language-Rawat #language-Old Chinese #language-Waxianghua #language-Literary Chinese #language-Gan Chinese #language-Hakka Chinese #language-Xiang Chinese #language-Jinyu Chinese #language-Mandarin Chinese #language-Wutunhua #language-Wu Chinese #language-Yue Chinese #language-Min Dong Chinese #language-Pu-Xian Chinese #language-Min Bei Chinese #language-Min Zhong Chinese #language-Omaha-Ponca #language-Iowa-Oto #language-Ofo #language-Uni #language-Bouni #language-Puare #language-Rawo #language-Womo #language-Vanimo #language-Momina #language-Momuna #language-Humburi Senni Songhay #language-Koyraboro Senni Songhai #language-Tondi Songway Kiini #language-Dendi (Benin) #language-Koyra Chiini Songhay #language-Tadaksahak #language-Kaburi #language-Kokoda #language-Kemberano #language-Arandai #language-Dime #language-Aari #language-Gayil #language-Hamer-Banna #language-Karo (Ethiopia) #language-Uisai #language-Simeku #language-Naasioi #language-Daantanai' #language-Koromira #language-La'bi #language-Lomavren #language-Ngatik Men's Creole #language-Traveller Danish #language-Tavringer Romani #language-Traveller Norwegian #language-Shelta #language-Callawalla #language-Camtho #language-Suki #language-Gogodala #language-Ari #language-Waruna #language-Kwegu #language-Me'en #language-Mursi #language-Murle #language-Tennet #language-Didinga #language-Laarim #language-Cun #language-Hlai #language-E'ma Buyang #language-En #language-Langnian Buyang #language-Baha Buyang #language-Laha (Viet Nam) #language-A'ou #language-Red Gelao #language-Qau #language-Lachi #language-White Lachi #language-Lingao #language-Minz Zhuang #language-Nung (Viet Nam) #language-Tày Sa Pa #language-Lü #language-Tày Tac #language-Tai Pao #language-Nyaw #language-Tai Do #language-Tai Long #language-Khamyang #language-Turung #language-Tai Nüa #language-Tai Hongjin #language-Pa Di #language-Tai Thanh #language-Northeastern Thai #language-Yoy #language-Zuojiang Zhuang #language-Central Hongshuihe Zhuang #language-Eastern Hongshuihe Zhuang #language-Guibian Zhuang #language-Guibei Zhuang #language-Lianshan Zhuang #language-Liujiang Zhuang #language-Liuqian Zhuang #language-Qiubei Zhuang #language-Tay Khang #language-Ts'ün-Lao #language-Youjiang Zhuang #language-Yongnan Zhuang #language-Yongbei Zhuang #language-Mulam #language-Southern Dong #language-Cao Miao #language-Northern Dong #language-T'en #language-Ai-Cham #language-Mak (China) #language-Chadong #language-Maonan #language-Lakkia #language-Mararit #language-Assangori #language-Tama (Chad) #language-Ganggalida #language-Kayardild #language-Purepecha #language-Western Highland Purepecha #language-Taulil #language-Dadibi #language-Folopa #language-Highland Oaxaca Chontal #language-Lowland Oaxaca Chontal #language-Bunak #language-Sawila #language-Kui (Indonesia) #language-Kamang #language-Adang #language-Hamap #language-Kabola #language-Kaera #language-Tereweng #language-Nedebang #language-Fataluku #language-Oirata #language-Orya #language-Berik #language-Itik #language-Kwesten #language-Mander #language-Maremgi #language-Bonerif #language-Dabe #language-Jofotek-Bromnya #language-Keder #language-Vitou #language-Huehuetla Tepehua #language-Pisaflores Tepehua #language-Tlachichilco Tepehua #language-Yecuatla Totonac #language-Papantla Totonac #language-Coyutla Totonac #language-Highland Totonac #language-Xicotepec De Juárez Totonac #language-Tecpatlán Totonac #language-Upper Necaxa Totonac #language-Waimaha #language-Yurutí #language-Arapaso #language-Yahuna #language-Tama (Colombia) #language-Macaguaje #language-Udihe #language-Orok #language-Jurchen #language-Sibe #language-Oroqen #language-Kepkiriwát #language-Arikem #language-Karitiâna #language-Sateré-Mawé #language-Awetí #language-Kamayurá #language-Xetá #language-Chiripá #language-Paraguayan Guaraní #language-Western Bolivian Guaraní #language-Tapieté #language-Jorá #language-Yuqui #language-Nhengatu #language-Tupinambá #language-Cocama-Cocamilla #language-Omagua #language-Potiguára #language-Tupinikin #language-Xingú Asuriní #language-Amanayé #language-Anambé #language-Araweté #language-Tapirapé #language-Parakanã #language-Suruí Do Pará #language-Tocantins Asurini #language-Turiwára #language-Guajajára #language-Júma #language-Paranawát #language-Wiraféd #language-Tenharim #language-Apiaká #language-kgm #language-Kayabí #language-Amundava #language-Uru-Eu-Wau-Wau #language-Urubú-Kaapor #language-Wayampi #language-Suruí #language-Cinta Larga #language-Gavião Do Jiparaná #language-Kuruáya #language-Mundurukú #language-Puruborá #language-Karo (Brazil) #language-Urumi #language-Makuráp #language-Akuntsu #language-Tuparí #language-Jurúna #language-Xipaya #language-Maritsauá #language-Barikewa #language-Mouwase #language-Bolgarian #language-Tuvinian #language-Ainu (China) #language-West Yugur #language-Uighur #language-Northern Uzbek #language-Kirghiz #language-Kara-Kalpak #language-Pecheneg #language-Karachay-Balkar #language-Qashqa'i #language-slq #language-North Azerbaijani #language-South Azerbaijani #language-Giyug #language-Mawa (Nigeria) #language-Moksela #language-Pankararé #language-Rer Bare #language-Sentinel #language-Tremembé #language-Truká #language-Wakoná #language-Wasu #language-Weyto #language-Agavotaguerra #language-Aguano #language-Himarimã #language-Dek #language-Dungu #language-Esuma #language-Kaivi #language-Mala (Nigeria) #language-Nshi #language-ksa #language-Tumi #language-Vono #language-Sorsogon Ayta #language-Villa Viciosa Agta #language-Agariya #language-Nagarchal #language-Pardhan #language-Badeshi #language-Manangkari #language-Yugul #language-Alapmunte #language-Yalakalore #language-Wik-Keyangan #language-Pisabo #language-Wares #language-Morerebi #language-Tukumanféd #language-Ngurmbur #language-Bazigar #language-Camunic #language-Elymian #language-Eteocretan #language-Eteocypriot #language-Gail #language-Haitian Vodoun Culture Language #language-Illyrian #language-Kaimbé #language-Kapinawá #language-Karirí-Xocó #language-Katabaga #language-Koguryo #language-Lemnian #language-Minoan #language-North Picene #language-Numidian #language-Paekche #language-Pictish #language-Pijao #language-Polari #language-Quinqui #language-Raetic #language-Tartessian #language-Traveller Scottish #language-Uamué #language-Uru-Pa-In #language-Wakabunga #language-Liv #language-Livvi #language-Ludian #language-Kven Finnish #language-Mulgi #language-Eastern Mari #language-Western Mari #language-Komi-Zyrian #language-Komi-Permyak #language-Nenets #language-Forest Enets #language-Tundra Enets #language-Selkup #language-Panamint #language-Ute-Southern Paiute #language-Mono (USA) #language-Northern Paiute #language-Tubar #language-Mayo #language-Highland Puebla Nahuatl #language-Huaxcaleca Nahuatl #language-Northern Oaxaca Nahuatl #language-Ometepec Nahuatl #language-Pipil #language-Central Huasteca Nahuatl #language-Eastern Huasteca Nahuatl #language-Western Huasteca Nahuatl #language-Isthmus-Cosoleacaque Nahuatl #language-Isthmus-Pajapan Nahuatl #language-Isthmus-Mecayapan Nahuatl #language-Tabasco Nahuatl #language-Orizaba Nahuatl #language-Central Puebla Nahuatl #language-Santa María La Alta Nahuatl #language-Sierra Negra Nahuatl #language-Zacatlán-Ahuacatlán-Tepetzintla Nahuatl #language-Central Nahuatl #language-Classical Nahuatl #language-Morelos Nahuatl #language-Northern Puebla Nahuatl #language-Tetelcingo Nahuatl #language-Pochutec #language-Temascaltepec Nahuatl #language-Coatepec Nahuatl #language-Tlamacazapa Nahuatl #language-Michoacán Nahuatl #language-Eastern Durango Nahuatl #language-Western Durango Nahuatl #language-El Nayar Cora #language-Santa Teresa Cora #language-Central Tarahumara #language-Lowland Tarahumara #language-Northern Tarahumara #language-Southwestern Tarahumara #language-Southeastern Tarahumara #language-Tohono O'odham #language-Northern Tepehuan #language-Southeastern Tepehuan #language-Southwestern Tepehuan #language-Tepecano #language-Heiltsuk #language-Tuwari #language-Yawiyo #language-Walio #language-Pei #language-Moi (Indonesia) #language-Seget #language-Kalabra #language-Moraid #language-Marimanindji #language-Maringarr #language-Marti Ke #language-Maridjabin #language-Maridan #language-Mariyedi #language-Marriammu #language-Maranunggu #language-Ami #language-Manda (Australia) #language-Wilawila #language-Wunambal #language-Gambera #language-Kwini #language-Miwa #language-Unggumi #language-Worrorra #language-Umiida #language-Unggaranggu #language-Yawijibaya #language-Dagoman #language-Wardaman #language-Yangman #language-Bariji #language-Yareba #language-Yawa #language-Arin #language-Pumpokol #language-Changriwa #language-Mekmek #language-Biwat #language-Bun #language-Northern Yukaghir #language-Chuvantsy #language-Wappo #language-Ayoreo #language-Andoa #language-Cahuarano #language-Iquito #language-Aushiri #language-Záparo #language-Alumu-Tesu #language-Eastern Abnaki #language-Aasáx #language-Manide #language-Western Abnaki #language-Abkhazian #language-Abellen Ayta #language-Achinese #language-Mesopotamian Arabic #language-Atauran #language-Lidzonka #language-Adi #language-Northeast Pashai #language-Putukwam #language-Nanubae #language-Remontado Dumagat #language-Ainu (Japan) #language-Andajin #language-Algerian Jewish Sign Language #language-Tosk Albanian #language-Alaba-K’abeena #language-Amol #language-Anu-Hkongso Chin #language-Alor #language-Pahanan Agta #language-Ambul #language-Official Aramaic (700-300 BCE) #language-Aruá (Rodonia State) #language-Cishingini #language-Abishira #language-Atemble #language-Atong (Cameroon) #language-Avaric #language-Jair Awyu #language-Awun #language-Xârâgurè #language-Ayabadhu #language-Magbukun Ayta #language-Mai Brat #language-Bainouk-Gunyuño #language-Baluchi #language-Baga Pokur #language-Bunuba #language-Central Bikol #language-Babine #language-Bainouk-Gunyaamolo #language-Bai (South Sudan) #language-Belait #language-Bekati' #language-Panyi Bai #language-Gahri #language-Bangandu #language-Bo (Laos) #language-Balkan Gagauz Turkish #language-Bohtan Neo-Aramaic #language-Baloi #language-Bidyogo #language-Bedjond #language-Binukid #language-Northern Sorsoganon #language-Bekwel #language-Bote-Majhi #language-Somba-Siawari #language-Butmas-Tur #language-Bamako Sign Language #language-Bonjo #language-Borôro #language-Daakaka #language-Kaure #language-Bishnupriya #language-Bilakura #language-Wumboko #language-Bengkala Sign Language #language-Bodo (India) #language-Bilbil #language-Kati #language-Brem #language-Barein #language-Baniva #language-Baniwa #language-Tairaha #language-Birale #language-Binahari #language-Biao #language-Bidjara #language-Naami #language-Kɛlɛngaxo Bozo #language-Tsimané #language-Chachi #language-Tsucuba #language-Cacua #language-Cafundo Creole #language-Cinda-Regi-Tiyal #language-Centúúm #language-Chinook #language-Mari (Russia) #language-Chinook jargon #language-Chakavian #language-Chukot #language-Cakfem-Mushere #language-Chilcotin #language-Idu-Mishmi #language-Lautu Chin #language-Classical Mongolian #language-Michigamea #language-Mro-Khimi Chin #language-Northern Ping Chinese #language-Chenoua #language-Middle Cornish #language-Colorado #language-Cori #language-Jola-Kasa #language-Southern Ping Chinese #language-Croatia Sign Language #language-Southern Ohlone #language-Northern Ohlone #language-Siyin Chin #language-Coos #language-Thaiphum Chin #language-Chhintange #language-Northern Catanduanes Bikol #language-Moundadan Chetty #language-Chug #language-Huizhou Chinese #language-Knaanic #language-Bondum Dom Dogon #language-Deccan #language-West Goodenough #language-Dido #language-Delaware #language-Slave (Athapascan) #language-Southern Dagaare #language-Casiguran Dumagat Agta #language-Andaandi #language-Dogri (individual language) #language-Dhodia #language-Dhanwar (Nepal) #language-Kumiai #language-Dimli (individual language) #language-Diriku #language-Djadjawurrung #language-Djamindjung #language-Eastern Maroon Creole #language-Medefaidrin #language-Dama #language-Kemedzung #language-Dení #language-Dogri (macrolanguage) #language-C'Lela #language-Disa #language-Daur #language-Adithinngithigh #language-Tene Kan Dogon #language-Daatsʼíin #language-Uyajitaya #language-Middle Dutch (ca. 1050-1350) #language-Duli-Gey #language-Djabugay #language-Karenggapa #language-Teke-Ebo #language-Emilian #language-Standard Estonian #language-Modern Greek (1453-) #language-Emerillon #language-Eastern Minyag #language-Middle English (1100-1500) #language-Northwest Alaska Inupiatun #language-Central Yupik #language-Etchemin #language-Eton (Cameroon) #language-Fa d'Ambu #language-Faita #language-Paloor #language-Fanti #language-Southwestern Fars #language-West Albay Bikol #language-Tornedalen Finnish #language-Foau #language-Flaaitaal #language-Fanbak #language-Fernando Po Creole English #language-Middle French (ca. 1400-1600) #language-Eastern Frisian #language-Fortsenal #language-Fulah #language-Nigerian Fulfulde #language-Guarequena #language-Galolen #language-Gbaya (Central African Republic) #language-Karajarri #language-Gbanziri #language-Gagadu #language-Gabi-Gabi #language-Gadjerawang #language-Ghodoberi #language-Kungardutyi #language-Ywom #language-ut-Ma'in #language-Eviya #language-Gurr-goni #language-Gagu #language-Ghadamès #language-Ghulfan #language-Kuke #language-Kija #language-Gaɓogbo #language-Githabul #language-Hinukh #language-Green Gelao #language-Mulao #language-White Gelao #language-Gunditjmara #language-Magɨ (Madang Province) #language-ǂUngkue #language-Belning #language-Northwest Pashai #language-Garlali #language-Magɨyi #language-Middle High German (ca. 1050-1500) #language-Mgbolizhia #language-ǁGana #language-Gozarkhani #language-Guana (Brazil) #language-Ancient Greek (to 1453) #language-Taznatit #language-Nema #language-Swiss German #language-Aghu-Tharnggala #language-Gunwinggu #language-Guana (Paraguay) #language-Guanano #language-Pará Gavião #language-Gawwada #language-ǀGwi #language-Hamba #language-Serbo-Croatian #language-Herdé #language-Hemba #language-Haiǁom #language-Kerak #language-Hoyahoya #language-Tsoa #language-Hong Kong Sign Language #language-Matu Chin #language-Large Flowery Miao #language-Maek #language-Hmong Shua #language-ǁAni #language-Hovongan #language-Hawai'i Sign Language (HSL) #language-Hértevin #language-Middle Hittite #language-San Francisco Del Mar Huave #language-Hungana #language-San Mateo Del Mar Huave #language-San Dionisio Del Mar Huave #language-Sabu #language-Santa María Del Mar Huave #language-Islander Creole English #language-Indo-Portuguese #language-Keley-I Kallahan #language-Iha Based Pidgin #language-Bidhawal #language-Inuktitut #language-Iranun (Malaysia) #language-Iranun (Philippines) #language-Inga #language-Jungle Inga #language-Indonesian Sign Language #language-Inupiaq #language-Iresim #language-Izii #language-Jamamadí #language-Jakati #language-Badjiri #language-Jabutí #language-Jeri Kuo #language-Gwak #language-Bu (Kaduna State) #language-sTodsde #language-Guanyinqiao #language-Koro (India) #language-Amami Koniya Sign Language #language-Jogi #language-Jordanian Sign Language #language-Judeo-Arabic #language-Hupdë #language-Kachin #language-Kabiyè #language-Ngkâlmpw Kanum #language-Kachama-Ganjule #language-Kannada Kurumba #language-Kachhi #language-Karingani #language-Bädi Kanum #language-Khvarshi #language-Kele (Democratic Republic of Congo) #language-Karagas #language-Agob #language-Kirmanjki (individual language) #language-Khinalugh #language-Harijan Kinnauri #language-Kaikavian Literary Language #language-Kaeku #language-Gamilaraay #language-Tagakaulo #language-Migum #language-Majukayang Kalinga #language-Kwama #language-Karipúna Creole French #language-Khorasani Turkish #language-Konda #language-Koongo #language-Western Kanjobal #language-Kanamarí #language-Konkani (individual language) #language-Kung-Ekoka #language-Kodi #language-Kacipo-Bale Suri #language-Konkani (macrolanguage) #language-Kugama #language-Koy Sanjaq Surat #language-Eastern Krahn #language-Kinaray-A #language-Gbaya (Sudan) #language-Southern Kalinga #language-Krisa #language-Juǀʼhoan #language-Kuman (Papua New Guinea) #language-Tsakwambo #language-Kwa #language-Kwakiutl #language-Kofyar #language-Zayein Karen #language-Kanoé #language-Koro (Papua New Guinea) #language-Kalapuya #language-Kelon #language-Southern Subanen #language-Linear A #language-Lama Bai #language-Libon Bikol #language-Rmeet #language-Dũya #language-Lamma #language-Lezghian #language-Lingarak #language-T'apo #language-Mlahsö #language-Likila #language-Lika #language-Lingala #language-Liberian English #language-Yirandali #language-Kungkari #language-Pévé #language-South Lembata #language-Langobardic #language-Leningitij #language-Langam #language-Lorediakarkar #language-Lanima #language-Louisiana Creole #language-Loke #language-Laro #language-Burundian Sign Language #language-Lish #language-Late Middle Chinese #language-Thur #language-Luxembourgish #language-Luiseno #language-Lushai #language-Lushootseed #language-Lavi #language-Levuka #language-Lakurumau #language-Lyngngam #language-Mandingo #language-Ombamba #language-Maquiritari #language-Malaccan Creole Portuguese #language-Cameroon Mambila #language-Minanibai #language-Maguindanaon #language-Miriwoong #language-Mano #language-Mogofin #language-Middle Irish (900-1200) #language-Manda (Tanzania) #language-Mongol #language-Mócheno #language-Digaro-Mishmi #language-Uncoded languages #language-Makalero #language-Tu #language-Mahican #language-Malas #language-Kinamiging Manobo #language-Makasae #language-Malagasy #language-Motlav #language-Malfaxal #language-Malaynon #language-Mundat #language-Musar #language-Musak #language-Manikion #language-Innu #language-Malak Malak #language-Mapidian #language-Misima-Panaeati #language-Pano #language-Marino #language-Malay (macrolanguage) #language-Mono (Solomon Islands) #language-Mator #language-Multiple languages #language-Murrinh-Patha #language-Labo #language-Marwari #language-Miju-Mishmi #language-Nigeria Mambila #language-Inapang #language-Ngan'gityemerri #language-Ca̱hungwa̱rya̱ #language-Ngarrindjeri #language-Ngbinda #language-Ngarinyman #language-South Ndebele #language-Na-kara #language-Chothe Naga #language-North Ndebele #language-Nadruvian #language-Nyenkha #language-Neo-Hittite #language-Nepali (macrolanguage) #language-Newari #language-Ayiwo #language-Nafaanra #language-Mfumte #language-Ngbaka #language-Dalabon #language-Ngurimi #language-Engdewu #language-Kriang #language-Guerrero Nahuatl #language-Nakame #language-Gilyak #language-Nisa #language-Nyishi #language-Khoibu Naga #language-Ngul #language-Nahali #language-Tangkhul Naga (India) #language-Manangba #language-ǃXóõ #language-Moyon Naga #language-Nyangga #language-Nepali (individual language) #language-Noipx #language-Southern Nago #language-Kyan-Karyaw Naga #language-Jèrriais #language-Northern Kalapuya #language-Lower Nossob #language-Northwestern Nisu #language-Tase Naga #language-Ngantangarra #language-Ikoma-Nata-Isenye #language-Tangkhul Naga (Myanmar) #language-Yuanga #language-Anong #language-Classical Newari #language-Ngayawung #language-Middle Newar #language-Nottoway-Meherrin #language-Koki Naga #language-Nyikina #language-Nyungar #language-Nanga Dama Dogon #language-Old Avar #language-Occitan (post 1500) #language-Old Cham #language-Old Hittite #language-Old Hungarian #language-Ontong Java #language-Kobo #language-Koresh-e Rostam #language-Middle Korean (10th-16th cent.) #language-Old Korean (3rd-9th cent.) #language-Omok #language-Old Manipuri #language-Onin Based Pidgin #language-Ong #language-Opata #language-Oriya (macrolanguage) #language-Adivasi Oriya #language-Old Sundanese #language-Ottoman Turkish (1500-1928) #language-Old Tibetan #language-Tagargrent #language-Oune #language-Old Uighur #language-Paumarí #language-Panjabi #language-Pakaásnovos #language-E'ñapa Woromaipu #language-Puebla Mazatec #language-Pyu (Papua New Guinea) #language-Parenga #language-Kayan #language-Northeastern Pomo #language-Kunja #language-Iranian Persian #language-Pere #language-Pfaelzisch #language-Sudanese Creole Arabic #language-Gāndhārī #language-Primitive Irish #language-Phalura #language-Pahari-Potwari #language-Piratapuyo #language-Pileni #language-Ardhamāgadhī Prākrit #language-Pankhu #language-plj #language-San Marcos Tlacoyalco Popoloca #language-Māhārāṣṭri Prākrit #language-Pamlico #language-Lingua Franca #language-Paynamar #language-Pangu #language-Banyjima #language-Pwapwâ #language-Prussian #language-Parauk #language-Prasuni #language-Old Provençal (to 1500) #language-Phai #language-Iranian Sign Language #language-Southwest Pashai #language-Southeast Pashai #language-Pauserna #language-Sauraseni Prākrit #language-Pindiini #language-Puoc #language-Pushto #language-Pyu (Myanmar) #language-Quechua #language-Chimborazo Highland Quichua #language-Yanahuanca Pasco Quechua #language-Kuman (Russia) #language-Kwalhioqua-Tlatskanai #language-Quiripi #language-Canela #language-Rarotongan #language-Rapa #language-Northern Bontok #language-Miraya Bikol #language-Remo #language-Retta #language-Roria #language-Tarifit #language-Riang Lang #language-Ritharrngu #language-Carpathian Romani #language-Sinte Romani #language-Romany #language-Arritinngithigh #language-Romano-Serbian #language-Yurats #language-Macedo-Romanian #language-Karuwali #language-Rāziḥī #language-Chabu #language-Sileibi #language-Sri Lankan Creole Malay #language-Hyolmo #language-Sha #language-Sicel #language-Shabak #language-Surubu #language-Cebaara Senoufo #language-Suarmin #language-Senara Sénoufo #language-Small Flowery Miao #language-Old Irish (to 900) #language-Mag-antsi Ayta #language-Suga #language-Singpho #language-Shahrudi #language-Shehri #language-Tachawit #language-Akkala Sami #language-Sajau Basap #language-Kildin Sami #language-Pite Sami #language-Kemi Sami #language-Sajalong #language-Ter Sami #language-Ume Sami #language-Sakirabiá #language-Sakalava Malagasy #language-Kutong #language-Sissala #language-Ma'ya #language-Southern Sami #language-Northern Sami #language-Lule Sami #language-Inari Sami #language-Skolt Sami #language-Somray #language-Bau Bidayuh #language-South West Bay #language-Songomeno #language-Songo #language-Swo #language-Sian #language-Loreto-Ucayali Spanish #language-Siculo Arabic #language-Kufr Qassem Sign Language (KQSL) #language-Sara #language-Southern Sorsoganon #language-So'a #language-Shark Bay #language-Settla #language-Saterfriesisch #language-Tirmaga-Chai Suri #language-Skalvian #language-Swahili (macrolanguage) #language-Swahili (individual language) #language-Sawknah #language-Sicanian #language-Shuhi #language-Southern Kalapuya #language-Selian #language-Samre #language-Sorothaptic #language-Tabassaran #language-Dharawal #language-Datooga #language-Tawr Chin #language-Tandroy-Mahafaly Malagasy #language-Teke-Tege #language-Tereno #language-Tewa (USA) #language-Tanaina #language-Kuuk Thaayorre #language-Aheu #language-Tidikelt Tamazight #language-Tiéfo #language-Tjungundji #language-Temacine Tamazight #language-Tjupany #language-Talodi #language-Filomena Mata-Coahuitlán Totonac #language-Sou Nama #language-Katbol #language-Tamashek #language-Tembo (Motembo) #language-Ménik #language-Ten'edn #language-tpw #language-Tembé #language-Western Totonac #language-Tarao Naga #language-Sediq #language-Tsishingini #language-Long Wat #language-Tewa (Indonesia) #language-Northern Tiwa #language-Kyanga #language-Central Atlas Tamazight #language-Buhi'non Bikol #language-Tanjijili #language-Muak Sa-aak #language-Meriam Mir #language-Morrobalama #language-Undetermined #language-Kurnai #language-Urali #language-us-Saare #language-ut-Hun #language-Sekele #language-Valman #language-Southwestern Bontok #language-Korlai Creole Portuguese #language-Vlaams #language-Martuyhunira #language-Barbaram #language-Mainfränkisch #language-Vano #language-Vinmavis #language-Awa (China) #language-Walla Walla #language-Wagiman #language-Wara #language-Waigali #language-West Bengal Sign Language #language-Warnman #language-Yanomámi #language-Wadjabangayi #language-Kiunum #language-Westphalien #language-Rawngtu Chin #language-Wejewa #language-Wangkangurru #language-Sou Upaa #language-Wahau Kenyah #language-Wik Ngathan #language-Keerray-Woorroong #language-Wangkayutyuru #language-Wailapa #language-Western Minyag #language-Mokati #language-Kuwema #language-Wè Northern #language-Waluwarra #language-Warungu #language-Gugu Warra #language-Wae Rana #language-Waray (Australia) #language-Wusi #language-Owenia #language-Wetamut #language-Wangaaybuwan-Ngiyambaa #language-Ararandewára #language-ǀXam #language-Aquitanian #language-Kamas #language-Lower Burdekin #language-Bindal #language-Batjala #language-Cumbric #language-Chorasmian #language-Curonian #language-Darkinyung #language-Dharuk #language-Eblan #language-ǁXegwi #language-Epi-Olmec #language-Gabrielino-Fernandeño #language-Garingbal #language-Galindan #language-Harami #language-Hunnic #language-Middle Khmer (1400 to 1850 CE) #language-Indus Valley Language #language-Minjungbal #language-Northern Nago #language-Kenyan Sign Language #language-Kachok #language-Loup B #language-Ligurian (Ancient) #language-Liburnian #language-Alanic #language-Median #language-Kugu-Muminh #language-Ancient Macedonian #language-Manichaean Middle Persian #language-Kanakanabu #language-Middle Mongolian #language-Ngoni (Tanzania) #language-Nganakarti #language-Ngoni (Mozambique) #language-Narragansett #language-Nukunul #language-Nyiyaparli #language-Komo (Sudan) #language-Northeastern Tasmanian #language-Oyster Bay Tasmanian #language-Southeast Tasmanian #language-North Midlands Tasmanian #language-Port Sorell Tasmanian #language-Puyo-Paekche #language-Northern Tasmanian #language-Northwestern Tasmanian #language-Southwestern Tasmanian #language-Puyo #language-Bruny Island Tasmanian #language-Kreye #language-Minang #language-Krikati-Timbira #language-Armazic #language-Aranama-Tamique #language-Sabaean #language-Sambal #language-Scythian #language-Sudovian #language-Early Tripuri #language-Tacahua Mixtec #language-Vandalic #language-Written Oirat #language-Boro (Ghana) #language-Ke'o #language-Zemgalian #language-Ancient Zapotec #language-Yaka (Democratic Republic of Congo) #language-Yakama #language-Yuwana #language-Yakha #language-Yabaâna #language-Yela #language-Yiningayi #language-Yolŋu Sign Language #language-Yan-nhaŋu Sign Language #language-Yidiny #language-Riang Lai #language-Kathu #language-Nyâlayu #language-Yokuts #language-Yongkom #language-Yirrk-Mel #language-Yerong #language-Yaroamë #language-Yassic #language-Myanmar Sign Language #language-Sirenik Yupik #language-Talu #language-Tanglang #language-Yatay #language-Yucateco #language-Yug #language-Yuracare #language-Mayawali #language-Yir Yoront #language-Miahuatlán Zapotec #language-Balaibalan #language-Bu (Bauchi State) #language-Zhuang #language-zkb #language-Khorezmian #language-Kanan #language-Kott #language-Krevinian #language-Khazar #language-Matngala #language-Zande (individual language) #language-Kara (Korea) #language-Zerenkel #language-Kaskean #language-Quioquitani-Quierí Zapotec #language-No linguistic content #language-Zyphe Chin #license-cc-by-4.0 #region-us \n# Description\nDataset listing 27,328 languages and dialects (also includes macrolanguage names). \nFor each language, either the ISO 639 code, the Glottolog code or both are provided."
] |
13818c03be12f605c8c27c90797b160682b20829 | 😊 There are two folders:
- **podcasts** 📁: Contains podcasts with regular hosts and guests marked as criminals. 🚨
- **criminals** 📁: Includes voice clips of the podcast's guests, which will be used for the identification of criminals within the podcasts themselves. 🔍🎙️
| zaietsilla/Criminal_Voice_Identification | [
"doi:10.57967/hf/1721",
"region:us"
] | 2024-01-02T20:03:30+00:00 | {} | 2024-01-02T21:34:51+00:00 | [] | [] | TAGS
#doi-10.57967/hf/1721 #region-us
| There are two folders:
- podcasts : Contains podcasts with regular hosts and guests marked as criminals.
- criminals : Includes voice clips of the podcast's guests, which will be used for the identification of criminals within the podcasts themselves. ️
| [] | [
"TAGS\n#doi-10.57967/hf/1721 #region-us \n"
] | [
18
] | [
"passage: TAGS\n#doi-10.57967/hf/1721 #region-us \n"
] |
8d6d98053b3332279e904091529ebbb820beff0a |
# Dataset Card for HAREM
<!-- Provide a quick summary of the dataset. -->
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** pt
- **License:** cc-by-4.0
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | arubenruben/harem | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"multilinguality:monolingual",
"language:pt",
"license:cc-by-4.0",
"region:us"
] | 2024-01-02T20:03:32+00:00 | {"annotations_creators": ["expert-generated"], "language": "pt", "license": "cc-by-4.0", "multilinguality": "monolingual", "task_categories": ["token-classification"], "pretty_name": "HAREM", "tasks_ids": ["named-entity-recognition"], "dataset_info": [{"config_name": "mini_harem_default", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR", "11": "B-ABSTRACCAO", "12": "I-ABSTRACCAO", "13": "B-ACONTECIMENTO", "14": "I-ACONTECIMENTO", "15": "B-COISA", "16": "I-COISA", "17": "B-OBRA", "18": "I-OBRA", "19": "B-OUTRO", "20": "I-OUTRO"}}}}], "splits": [{"name": "test", "num_bytes": 1062698, "num_examples": 128}], "download_size": 228325, "dataset_size": 1062698}, {"config_name": "mini_harem_selective", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR"}}}}], "splits": [{"name": "test", "num_bytes": 1062698, "num_examples": 128}], "download_size": 224812, "dataset_size": 1062698}, {"config_name": "primeiro_harem_default", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR", "11": "B-ABSTRACCAO", "12": "I-ABSTRACCAO", "13": "B-ACONTECIMENTO", "14": "I-ACONTECIMENTO", "15": "B-COISA", "16": "I-COISA", "17": "B-OBRA", "18": "I-OBRA", "19": "B-OUTRO", "20": "I-OUTRO"}}}}], "splits": [{"name": "train", "num_bytes": 1557659, "num_examples": 129}], "download_size": 305485, "dataset_size": 1557659}, {"config_name": "primeiro_harem_selective", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR"}}}}], "splits": [{"name": "train", "num_bytes": 1557659, "num_examples": 129}], "download_size": 300663, "dataset_size": 1557659}, {"config_name": "segundo_harem_default", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR", "11": "B-ABSTRACCAO", "12": "I-ABSTRACCAO", "13": "B-ACONTECIMENTO", "14": "I-ACONTECIMENTO", "15": "B-COISA", "16": "I-COISA", "17": "B-OBRA", "18": "I-OBRA", "19": "B-OUTRO", "20": "I-OUTRO"}}}}], "splits": [{"name": "train", "num_bytes": 1276015, "num_examples": 117}], "download_size": 276087, "dataset_size": 1276015}, {"config_name": "segundo_harem_selective", "features": [{"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "O", "1": "B-PESSOA", "2": "I-PESSOA", "3": "B-ORGANIZACAO", "4": "I-ORGANIZACAO", "5": "B-LOCAL", "6": "I-LOCAL", "7": "B-TEMPO", "8": "I-TEMPO", "9": "B-VALOR", "10": "I-VALOR"}}}}], "splits": [{"name": "train", "num_bytes": 1235128, "num_examples": 117}], "download_size": 262708, "dataset_size": 1235128}], "configs": [{"config_name": "mini_harem_default", "data_files": [{"split": "test", "path": "mini_harem_default/test-*"}]}, {"config_name": "mini_harem_selective", "data_files": [{"split": "test", "path": "mini_harem_selective/test-*"}]}, {"config_name": "primeiro_harem_default", "data_files": [{"split": "train", "path": "primeiro_harem_default/train-*"}]}, {"config_name": "primeiro_harem_selective", "data_files": [{"split": "train", "path": "primeiro_harem_selective/train-*"}]}, {"config_name": "segundo_harem_default", "data_files": [{"split": "train", "path": "segundo_harem_default/train-*"}]}, {"config_name": "segundo_harem_selective", "data_files": [{"split": "train", "path": "segundo_harem_selective/train-*"}]}]} | 2024-01-02T20:12:49+00:00 | [] | [
"pt"
] | TAGS
#task_categories-token-classification #annotations_creators-expert-generated #multilinguality-monolingual #language-Portuguese #license-cc-by-4.0 #region-us
|
# Dataset Card for HAREM
## Dataset Details
### Dataset Description
- Curated by:
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP): pt
- License: cc-by-4.0
### Dataset Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for HAREM",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): pt\n- License: cc-by-4.0",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#task_categories-token-classification #annotations_creators-expert-generated #multilinguality-monolingual #language-Portuguese #license-cc-by-4.0 #region-us \n",
"# Dataset Card for HAREM",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): pt\n- License: cc-by-4.0",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
54,
7,
4,
47,
29,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#task_categories-token-classification #annotations_creators-expert-generated #multilinguality-monolingual #language-Portuguese #license-cc-by-4.0 #region-us \n# Dataset Card for HAREM## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): pt\n- License: cc-by-4.0### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
e2630dfc0d183df54bc977e2edeeeed2c92cd1c3 | # Dataset Card for "Medical_Summaries"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ManuelAlv/Medical_Summaries | [
"region:us"
] | 2024-01-02T20:08:34+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 13456200, "num_examples": 10828}, {"name": "validation", "num_bytes": 3349088, "num_examples": 2707}, {"name": "test", "num_bytes": 1136311, "num_examples": 903}], "download_size": 9609390, "dataset_size": 17941599}} | 2024-01-02T20:12:42+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "Medical_Summaries"
More Information needed | [
"# Dataset Card for \"Medical_Summaries\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"Medical_Summaries\"\n\nMore Information needed"
] | [
6,
16
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"Medical_Summaries\"\n\nMore Information needed"
] |
96cfba764971e2331ad754f14f8d23ee032840df | # Dataset Card for "quesst_extract_unit"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Codec-SUPERB/quesst_extract_unit | [
"region:us"
] | 2024-01-02T20:13:20+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "academicodec_hifi_16k_320d", "path": "data/academicodec_hifi_16k_320d-*"}, {"split": "academicodec_hifi_16k_320d_large_uni", "path": "data/academicodec_hifi_16k_320d_large_uni-*"}, {"split": "academicodec_hifi_24k_320d", "path": "data/academicodec_hifi_24k_320d-*"}, {"split": "audiodec_24k_320d", "path": "data/audiodec_24k_320d-*"}, {"split": "dac_16k", "path": "data/dac_16k-*"}, {"split": "dac_24k", "path": "data/dac_24k-*"}, {"split": "dac_44k", "path": "data/dac_44k-*"}, {"split": "encodec_24k", "path": "data/encodec_24k-*"}, {"split": "funcodec_en_libritts_16k_gr1nq32ds320", "path": "data/funcodec_en_libritts_16k_gr1nq32ds320-*"}, {"split": "funcodec_en_libritts_16k_gr8nq32ds320", "path": "data/funcodec_en_libritts_16k_gr8nq32ds320-*"}, {"split": "funcodec_en_libritts_16k_nq32ds320", "path": "data/funcodec_en_libritts_16k_nq32ds320-*"}, {"split": "funcodec_en_libritts_16k_nq32ds640", "path": "data/funcodec_en_libritts_16k_nq32ds640-*"}, {"split": "funcodec_zh_en_16k_nq32ds320", "path": "data/funcodec_zh_en_16k_nq32ds320-*"}, {"split": "funcodec_zh_en_16k_nq32ds640", "path": "data/funcodec_zh_en_16k_nq32ds640-*"}, {"split": "speech_tokenizer_16k", "path": "data/speech_tokenizer_16k-*"}]}], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "unit", "sequence": {"sequence": "int64"}}], "splits": [{"name": "academicodec_hifi_16k_320d", "num_bytes": 137294433, "num_examples": 13607}, {"name": "academicodec_hifi_16k_320d_large_uni", "num_bytes": 137294433, "num_examples": 13607}, {"name": "academicodec_hifi_24k_320d", "num_bytes": 205653057, "num_examples": 13607}, {"name": "audiodec_24k_320d", "num_bytes": 438940145, "num_examples": 13607}, {"name": "dac_16k", "num_bytes": 857616609, "num_examples": 13607}, {"name": "dac_24k", "num_bytes": 2424782353, "num_examples": 13607}, {"name": "dac_44k", "num_bytes": 720859173, "num_examples": 13607}, {"name": "encodec_24k", "num_bytes": 103254137, "num_examples": 13607}, {"name": "funcodec_en_libritts_16k_gr1nq32ds320", "num_bytes": 1098775313, "num_examples": 13607}, {"name": "funcodec_en_libritts_16k_gr8nq32ds320", "num_bytes": 1098775313, "num_examples": 13607}, {"name": "funcodec_en_libritts_16k_nq32ds320", "num_bytes": 1097970705, "num_examples": 13607}, {"name": "funcodec_en_libritts_16k_nq32ds640", "num_bytes": 550950673, "num_examples": 13607}, {"name": "funcodec_zh_en_16k_nq32ds320", "num_bytes": 1097970705, "num_examples": 13607}, {"name": "funcodec_zh_en_16k_nq32ds640", "num_bytes": 1097970705, "num_examples": 13607}, {"name": "speech_tokenizer_16k", "num_bytes": 274820913, "num_examples": 13607}], "download_size": 1776428213, "dataset_size": 11342928667}} | 2024-01-02T21:39:53+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "quesst_extract_unit"
More Information needed | [
"# Dataset Card for \"quesst_extract_unit\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"quesst_extract_unit\"\n\nMore Information needed"
] | [
6,
18
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"quesst_extract_unit\"\n\nMore Information needed"
] |
de1051608632263049bf130ce0b4fbb8e6f80990 | # Dataset Card for "BC5CDR_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | YBXL/BC5CDR_test | [
"region:us"
] | 2024-01-02T20:31:58+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "valid", "path": "data/valid-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "query", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2974723, "num_examples": 4560}, {"name": "valid", "num_bytes": 2974723, "num_examples": 4560}, {"name": "test", "num_bytes": 3111719, "num_examples": 4797}], "download_size": 2855134, "dataset_size": 9061165}} | 2024-01-02T20:32:00+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "BC5CDR_test"
More Information needed | [
"# Dataset Card for \"BC5CDR_test\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"BC5CDR_test\"\n\nMore Information needed"
] | [
6,
16
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"BC5CDR_test\"\n\nMore Information needed"
] |
227965d539cf64f9c788e3c202822dbd3f80b697 |
## ReadMe: Hindi-English Synthetic Dataset - Question-Answer Style Dialogues on Ethics, Systems Thinking, and Creative Problem-Solving with High-Level Principles of Mind
**Dataset Description:**
This was created as part of the Hugging Face Hinglish Training Project, coordinated on the Hugging Face Discord.
This dataset presents a human-currated/handcurrated collection of dialogues as well as prompt-answer pairs in Hindi with English translation that focus on ethics, systems thinking, and creative problem-solving, framed within the context of high-level principles of mind. The dataset includes question-answer style dialogues based on diverse domains and topics, including:
This dataset includes the best (human selected) examples prompted to demonstrate excellent Hindi-English-Hinglish translation, systems thinking, structured thinking, Hindi fundamentals, good moral character, ethics fundamentals, coherent question answering, step by step advanced reasoning, helpfulness with tasks relevant to Indian society, some limited Indian cultural archetypes, and step by step Theory-of-mind analysis.
These were generated using the public Gemini-powered version of Google Bard between December 28th 2023 and January 2nd 2023. It was then merged using a Python Pandas concatenation script.
* **Artificial Intelligence and Ethics:** Questions and answers about ethical decision-making in autonomous vehicles, healthcare systems, and language models.
* **Environment and Sustainable Development:** Questions and answers about sustainable agricultural practices, water management, and tackling climate change.
* **Education and Creativity:** Questions and answers about effective teaching methods for developing creative problem-solving skills in students.
* **Analysis of Complex Systems:** Questions and answers about understanding complex ecosystems, microservices architectures, and socio-economic systems.
**Each dialogue includes the following information:**
* **Hindi Question or Prompt:** A complex question related to the topic, many reflecting high-level principles of mind, ethical considerations, and STEM principles.
* **English Translation of Question or Prompt:** A literal translation of the Hindi question.
* **Suggested Response in Hindi:** A detailed response in Hindi incorporating high-level principles of mind with deep analysis, collaboration, and problem-solving.
* **English Translation of Response:** A literal translation of the suggested response.
**Potential Applications:**
This dataset can be useful for the following applications:
* **Training Dialogue Systems and AI Assistants:** Train assistant models to enable informed and deep conversations on ethical and complex topics.
* **Developing Educational Material on Ethics and Systems Thinking:** Design curriculum and training modules to promote ethical and systemic thinking in various domains.
* **Modeling Creative Problem-Solving Strategies:** Develop models for creative thinking and exploring innovative solutions.
* **Improving Hindi-English Machine Translation:** Train language models with complex topics and advanced language usage.
**Important Notes when using the Dataset:**
* There are some blank fields, most often the fourth column (English translation of response) and occasional partial translation rather than the full text of the translation. A single blank field in an otherwise complete row is somewhat common, roughly estimated to be present in between 4% and 0.5% of the observations. This occurs due to the token limit in Bard for each batch of data (there were between 2 and 15 observation per batch, before they were merged with a purpose-built python script.)
* There are also some English ToM (theory of mind) descriptive english artifacts in some of the hindi responses for the more advanced ToM focused observations (may be helpful is some contexts such as using English understandings to process ToM when answering it Hindi. It may also be seen as negative because it is English within the column meant for Hindi, thus cross-polluting.) Nonetheless these errors represent very small marginal portion of the dataset.
* This dataset does not endorse any specific product or service.
* It is helpful to consider ethical principles and accountability when using any dataset.
* The presented responses on various topics do not represent expert opinions but rather aim to inspire potential directions and discussions.
**We hope this dataset inspires you to think about and discuss high-level principles of mind in the context of ethics, systems thinking, and creative problem-solving!**
This example highlights the purpose, structure, potential applications, and important notes for using the dataset, all in English. | Solshine/Hindi_English_QandA_Synth_Data_For_Hinglish_Project | [
"license:apache-2.0",
"region:us"
] | 2024-01-02T21:00:29+00:00 | {"license": "apache-2.0"} | 2024-01-14T23:44:50+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
|
## ReadMe: Hindi-English Synthetic Dataset - Question-Answer Style Dialogues on Ethics, Systems Thinking, and Creative Problem-Solving with High-Level Principles of Mind
Dataset Description:
This was created as part of the Hugging Face Hinglish Training Project, coordinated on the Hugging Face Discord.
This dataset presents a human-currated/handcurrated collection of dialogues as well as prompt-answer pairs in Hindi with English translation that focus on ethics, systems thinking, and creative problem-solving, framed within the context of high-level principles of mind. The dataset includes question-answer style dialogues based on diverse domains and topics, including:
This dataset includes the best (human selected) examples prompted to demonstrate excellent Hindi-English-Hinglish translation, systems thinking, structured thinking, Hindi fundamentals, good moral character, ethics fundamentals, coherent question answering, step by step advanced reasoning, helpfulness with tasks relevant to Indian society, some limited Indian cultural archetypes, and step by step Theory-of-mind analysis.
These were generated using the public Gemini-powered version of Google Bard between December 28th 2023 and January 2nd 2023. It was then merged using a Python Pandas concatenation script.
* Artificial Intelligence and Ethics: Questions and answers about ethical decision-making in autonomous vehicles, healthcare systems, and language models.
* Environment and Sustainable Development: Questions and answers about sustainable agricultural practices, water management, and tackling climate change.
* Education and Creativity: Questions and answers about effective teaching methods for developing creative problem-solving skills in students.
* Analysis of Complex Systems: Questions and answers about understanding complex ecosystems, microservices architectures, and socio-economic systems.
Each dialogue includes the following information:
* Hindi Question or Prompt: A complex question related to the topic, many reflecting high-level principles of mind, ethical considerations, and STEM principles.
* English Translation of Question or Prompt: A literal translation of the Hindi question.
* Suggested Response in Hindi: A detailed response in Hindi incorporating high-level principles of mind with deep analysis, collaboration, and problem-solving.
* English Translation of Response: A literal translation of the suggested response.
Potential Applications:
This dataset can be useful for the following applications:
* Training Dialogue Systems and AI Assistants: Train assistant models to enable informed and deep conversations on ethical and complex topics.
* Developing Educational Material on Ethics and Systems Thinking: Design curriculum and training modules to promote ethical and systemic thinking in various domains.
* Modeling Creative Problem-Solving Strategies: Develop models for creative thinking and exploring innovative solutions.
* Improving Hindi-English Machine Translation: Train language models with complex topics and advanced language usage.
Important Notes when using the Dataset:
* There are some blank fields, most often the fourth column (English translation of response) and occasional partial translation rather than the full text of the translation. A single blank field in an otherwise complete row is somewhat common, roughly estimated to be present in between 4% and 0.5% of the observations. This occurs due to the token limit in Bard for each batch of data (there were between 2 and 15 observation per batch, before they were merged with a purpose-built python script.)
* There are also some English ToM (theory of mind) descriptive english artifacts in some of the hindi responses for the more advanced ToM focused observations (may be helpful is some contexts such as using English understandings to process ToM when answering it Hindi. It may also be seen as negative because it is English within the column meant for Hindi, thus cross-polluting.) Nonetheless these errors represent very small marginal portion of the dataset.
* This dataset does not endorse any specific product or service.
* It is helpful to consider ethical principles and accountability when using any dataset.
* The presented responses on various topics do not represent expert opinions but rather aim to inspire potential directions and discussions.
We hope this dataset inspires you to think about and discuss high-level principles of mind in the context of ethics, systems thinking, and creative problem-solving!
This example highlights the purpose, structure, potential applications, and important notes for using the dataset, all in English. | [
"## ReadMe: Hindi-English Synthetic Dataset - Question-Answer Style Dialogues on Ethics, Systems Thinking, and Creative Problem-Solving with High-Level Principles of Mind\n\nDataset Description:\n\nThis was created as part of the Hugging Face Hinglish Training Project, coordinated on the Hugging Face Discord.\n\nThis dataset presents a human-currated/handcurrated collection of dialogues as well as prompt-answer pairs in Hindi with English translation that focus on ethics, systems thinking, and creative problem-solving, framed within the context of high-level principles of mind. The dataset includes question-answer style dialogues based on diverse domains and topics, including:\n\nThis dataset includes the best (human selected) examples prompted to demonstrate excellent Hindi-English-Hinglish translation, systems thinking, structured thinking, Hindi fundamentals, good moral character, ethics fundamentals, coherent question answering, step by step advanced reasoning, helpfulness with tasks relevant to Indian society, some limited Indian cultural archetypes, and step by step Theory-of-mind analysis.\n\nThese were generated using the public Gemini-powered version of Google Bard between December 28th 2023 and January 2nd 2023. It was then merged using a Python Pandas concatenation script.\n\n* Artificial Intelligence and Ethics: Questions and answers about ethical decision-making in autonomous vehicles, healthcare systems, and language models.\n* Environment and Sustainable Development: Questions and answers about sustainable agricultural practices, water management, and tackling climate change.\n* Education and Creativity: Questions and answers about effective teaching methods for developing creative problem-solving skills in students.\n* Analysis of Complex Systems: Questions and answers about understanding complex ecosystems, microservices architectures, and socio-economic systems.\n\nEach dialogue includes the following information:\n\n* Hindi Question or Prompt: A complex question related to the topic, many reflecting high-level principles of mind, ethical considerations, and STEM principles.\n* English Translation of Question or Prompt: A literal translation of the Hindi question.\n* Suggested Response in Hindi: A detailed response in Hindi incorporating high-level principles of mind with deep analysis, collaboration, and problem-solving.\n* English Translation of Response: A literal translation of the suggested response.\n\nPotential Applications:\n\nThis dataset can be useful for the following applications:\n\n* Training Dialogue Systems and AI Assistants: Train assistant models to enable informed and deep conversations on ethical and complex topics.\n* Developing Educational Material on Ethics and Systems Thinking: Design curriculum and training modules to promote ethical and systemic thinking in various domains.\n* Modeling Creative Problem-Solving Strategies: Develop models for creative thinking and exploring innovative solutions.\n* Improving Hindi-English Machine Translation: Train language models with complex topics and advanced language usage.\n\nImportant Notes when using the Dataset:\n\n* There are some blank fields, most often the fourth column (English translation of response) and occasional partial translation rather than the full text of the translation. A single blank field in an otherwise complete row is somewhat common, roughly estimated to be present in between 4% and 0.5% of the observations. This occurs due to the token limit in Bard for each batch of data (there were between 2 and 15 observation per batch, before they were merged with a purpose-built python script.)\n* There are also some English ToM (theory of mind) descriptive english artifacts in some of the hindi responses for the more advanced ToM focused observations (may be helpful is some contexts such as using English understandings to process ToM when answering it Hindi. It may also be seen as negative because it is English within the column meant for Hindi, thus cross-polluting.) Nonetheless these errors represent very small marginal portion of the dataset.\n* This dataset does not endorse any specific product or service.\n* It is helpful to consider ethical principles and accountability when using any dataset.\n* The presented responses on various topics do not represent expert opinions but rather aim to inspire potential directions and discussions.\n\nWe hope this dataset inspires you to think about and discuss high-level principles of mind in the context of ethics, systems thinking, and creative problem-solving!\n\n\nThis example highlights the purpose, structure, potential applications, and important notes for using the dataset, all in English."
] | [
"TAGS\n#license-apache-2.0 #region-us \n",
"## ReadMe: Hindi-English Synthetic Dataset - Question-Answer Style Dialogues on Ethics, Systems Thinking, and Creative Problem-Solving with High-Level Principles of Mind\n\nDataset Description:\n\nThis was created as part of the Hugging Face Hinglish Training Project, coordinated on the Hugging Face Discord.\n\nThis dataset presents a human-currated/handcurrated collection of dialogues as well as prompt-answer pairs in Hindi with English translation that focus on ethics, systems thinking, and creative problem-solving, framed within the context of high-level principles of mind. The dataset includes question-answer style dialogues based on diverse domains and topics, including:\n\nThis dataset includes the best (human selected) examples prompted to demonstrate excellent Hindi-English-Hinglish translation, systems thinking, structured thinking, Hindi fundamentals, good moral character, ethics fundamentals, coherent question answering, step by step advanced reasoning, helpfulness with tasks relevant to Indian society, some limited Indian cultural archetypes, and step by step Theory-of-mind analysis.\n\nThese were generated using the public Gemini-powered version of Google Bard between December 28th 2023 and January 2nd 2023. It was then merged using a Python Pandas concatenation script.\n\n* Artificial Intelligence and Ethics: Questions and answers about ethical decision-making in autonomous vehicles, healthcare systems, and language models.\n* Environment and Sustainable Development: Questions and answers about sustainable agricultural practices, water management, and tackling climate change.\n* Education and Creativity: Questions and answers about effective teaching methods for developing creative problem-solving skills in students.\n* Analysis of Complex Systems: Questions and answers about understanding complex ecosystems, microservices architectures, and socio-economic systems.\n\nEach dialogue includes the following information:\n\n* Hindi Question or Prompt: A complex question related to the topic, many reflecting high-level principles of mind, ethical considerations, and STEM principles.\n* English Translation of Question or Prompt: A literal translation of the Hindi question.\n* Suggested Response in Hindi: A detailed response in Hindi incorporating high-level principles of mind with deep analysis, collaboration, and problem-solving.\n* English Translation of Response: A literal translation of the suggested response.\n\nPotential Applications:\n\nThis dataset can be useful for the following applications:\n\n* Training Dialogue Systems and AI Assistants: Train assistant models to enable informed and deep conversations on ethical and complex topics.\n* Developing Educational Material on Ethics and Systems Thinking: Design curriculum and training modules to promote ethical and systemic thinking in various domains.\n* Modeling Creative Problem-Solving Strategies: Develop models for creative thinking and exploring innovative solutions.\n* Improving Hindi-English Machine Translation: Train language models with complex topics and advanced language usage.\n\nImportant Notes when using the Dataset:\n\n* There are some blank fields, most often the fourth column (English translation of response) and occasional partial translation rather than the full text of the translation. A single blank field in an otherwise complete row is somewhat common, roughly estimated to be present in between 4% and 0.5% of the observations. This occurs due to the token limit in Bard for each batch of data (there were between 2 and 15 observation per batch, before they were merged with a purpose-built python script.)\n* There are also some English ToM (theory of mind) descriptive english artifacts in some of the hindi responses for the more advanced ToM focused observations (may be helpful is some contexts such as using English understandings to process ToM when answering it Hindi. It may also be seen as negative because it is English within the column meant for Hindi, thus cross-polluting.) Nonetheless these errors represent very small marginal portion of the dataset.\n* This dataset does not endorse any specific product or service.\n* It is helpful to consider ethical principles and accountability when using any dataset.\n* The presented responses on various topics do not represent expert opinions but rather aim to inspire potential directions and discussions.\n\nWe hope this dataset inspires you to think about and discuss high-level principles of mind in the context of ethics, systems thinking, and creative problem-solving!\n\n\nThis example highlights the purpose, structure, potential applications, and important notes for using the dataset, all in English."
] | [
14,
1018
] | [
"passage: TAGS\n#license-apache-2.0 #region-us \n"
] |
4470499de7975d12607748f79f1886712a6a861a | data source: https://github.com/StonyBrookNLP/BioNLI | hippocrates/BioNLI_test | [
"region:us"
] | 2024-01-02T21:37:52+00:00 | {} | 2024-01-20T20:24:24+00:00 | [] | [] | TAGS
#region-us
| data source: URL | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
30f081837947ea523fe4682af3d46b5eb7ede15b | # Dataset Card for "FluentUI-ART"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | iamkaikai/FluentUI-ART | [
"region:us"
] | 2024-01-02T21:52:08+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 6501934.0, "num_examples": 302}], "download_size": 5927206, "dataset_size": 6501934.0}} | 2024-01-02T21:52:10+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "FluentUI-ART"
More Information needed | [
"# Dataset Card for \"FluentUI-ART\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"FluentUI-ART\"\n\nMore Information needed"
] | [
6,
16
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"FluentUI-ART\"\n\nMore Information needed"
] |
0b7e96ddf4e242b90196f403fe44e85af4bc8605 | Scraped User solutions of Leetcode 50 solutions per problem.
I do not own the copyright of the data itself. If you want the data removed please contact me. | SebastianBodza/LeetCode_UserSubmissions | [
"region:us"
] | 2024-01-02T21:55:32+00:00 | {} | 2024-01-03T10:32:05+00:00 | [] | [] | TAGS
#region-us
| Scraped User solutions of Leetcode 50 solutions per problem.
I do not own the copyright of the data itself. If you want the data removed please contact me. | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
ea1dc85ecd4035089510a4c58030d288d86d89c0 | # Automated Essay Score (AES) ENEM Dataset
## Dataset Description
- **Purpose**: Automated Essay Scoring
- **Contents**: Student Essay Grades
- **Source**: https://github.com/kamel-usp/aes_enem
- **Size**: N<1000
## Use Case and Creators
- **Intended Use**: Estimate Essay Score
- **Creators**: Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá
- **Contact Information**: [email protected]; [email protected]
## Licensing Information
- **License**: MIT License
## Citation Details
- **Preferred Citation**:
```
@proceedings{DBLP:conf/propor/2024,
editor = {Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá},
title = {Computational Processing of the Portuguese Language - 16th International
Conference, {PROPOR} 2024, Galiza, March 13-15, 2024, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {TODO},
publisher = {Springer},
year = {2024},
url = {TODO},
doi = {TODO},
isbn = {TODO},
timestamp = {TODO},
biburl = {TODO},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
```
## Data Structure
- **Features**:
- id: id of scrapped page. `id_prompt`+`id` should be unique
- id_prompt: Essay's theme
- essay_title: Essay title
- essay_text: Essay text
- grades: list of 6 elements containing the grade for each of the five concepts plus the sum of all grades
- essay_year: Essay's year
- **Number of Instances**:
- sourceAOnly:
- train: 227
- validation: 68
- test: 90
- sourceAWithGraders:
- train: 744
- validation: 195
- test: 216
- sourceB:
- full: 3219
- **Data Splits**:
- sourceAOnly: sourceA data
- sourceAWithGraders: sourceA data augmented with Grader's review. In a nutshell, each row becomes three (the original grade plus two graders result)
- sourceB: sourceB data
## Data Considerations
- **Known Limitations**:
- **Ethical Considerations**:
## Additional Information
- **Additional Links**: Main code is [here](https://github.com/kamel-usp/aes_enem)
- **Related Datasets**: https://github.com/evelinamorim/aes-pt | kamel-usp/aes_enem_dataset | [
"task_categories:text-classification",
"size_categories:n<1K",
"language:pt",
"license:apache-2.0",
"education",
"aes",
"enem",
"region:us"
] | 2024-01-02T22:12:19+00:00 | {"language": ["pt"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["text-classification"], "tags": ["education", "aes", "enem"]} | 2024-01-13T04:07:55+00:00 | [] | [
"pt"
] | TAGS
#task_categories-text-classification #size_categories-n<1K #language-Portuguese #license-apache-2.0 #education #aes #enem #region-us
| # Automated Essay Score (AES) ENEM Dataset
## Dataset Description
- Purpose: Automated Essay Scoring
- Contents: Student Essay Grades
- Source: URL
- Size: N<1000
## Use Case and Creators
- Intended Use: Estimate Essay Score
- Creators: Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá
- Contact Information: igorcs@URL; andre.barbosa@URL
## Licensing Information
- License: MIT License
Details
- Preferred Citation:
## Data Structure
- Features:
- id: id of scrapped page. 'id_prompt'+'id' should be unique
- id_prompt: Essay's theme
- essay_title: Essay title
- essay_text: Essay text
- grades: list of 6 elements containing the grade for each of the five concepts plus the sum of all grades
- essay_year: Essay's year
- Number of Instances:
- sourceAOnly:
- train: 227
- validation: 68
- test: 90
- sourceAWithGraders:
- train: 744
- validation: 195
- test: 216
- sourceB:
- full: 3219
- Data Splits:
- sourceAOnly: sourceA data
- sourceAWithGraders: sourceA data augmented with Grader's review. In a nutshell, each row becomes three (the original grade plus two graders result)
- sourceB: sourceB data
## Data Considerations
- Known Limitations:
- Ethical Considerations:
## Additional Information
- Additional Links: Main code is here
- Related Datasets: URL | [
"# Automated Essay Score (AES) ENEM Dataset",
"## Dataset Description\n- Purpose: Automated Essay Scoring\n- Contents: Student Essay Grades\n- Source: URL\n- Size: N<1000",
"## Use Case and Creators\n- Intended Use: Estimate Essay Score\n- Creators: Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá\n- Contact Information: igorcs@URL; andre.barbosa@URL",
"## Licensing Information\n- License: MIT License\n\nDetails\n- Preferred Citation:",
"## Data Structure\n- Features:\n - id: id of scrapped page. 'id_prompt'+'id' should be unique\n - id_prompt: Essay's theme\n - essay_title: Essay title\n - essay_text: Essay text\n - grades: list of 6 elements containing the grade for each of the five concepts plus the sum of all grades\n - essay_year: Essay's year\n- Number of Instances:\n - sourceAOnly:\n - train: 227\n - validation: 68\n - test: 90\n - sourceAWithGraders:\n - train: 744 \n - validation: 195\n - test: 216\n - sourceB:\n - full: 3219\n- Data Splits:\n - sourceAOnly: sourceA data\n - sourceAWithGraders: sourceA data augmented with Grader's review. In a nutshell, each row becomes three (the original grade plus two graders result)\n - sourceB: sourceB data",
"## Data Considerations\n- Known Limitations:\n- Ethical Considerations:",
"## Additional Information\n- Additional Links: Main code is here\n- Related Datasets: URL"
] | [
"TAGS\n#task_categories-text-classification #size_categories-n<1K #language-Portuguese #license-apache-2.0 #education #aes #enem #region-us \n",
"# Automated Essay Score (AES) ENEM Dataset",
"## Dataset Description\n- Purpose: Automated Essay Scoring\n- Contents: Student Essay Grades\n- Source: URL\n- Size: N<1000",
"## Use Case and Creators\n- Intended Use: Estimate Essay Score\n- Creators: Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá\n- Contact Information: igorcs@URL; andre.barbosa@URL",
"## Licensing Information\n- License: MIT License\n\nDetails\n- Preferred Citation:",
"## Data Structure\n- Features:\n - id: id of scrapped page. 'id_prompt'+'id' should be unique\n - id_prompt: Essay's theme\n - essay_title: Essay title\n - essay_text: Essay text\n - grades: list of 6 elements containing the grade for each of the five concepts plus the sum of all grades\n - essay_year: Essay's year\n- Number of Instances:\n - sourceAOnly:\n - train: 227\n - validation: 68\n - test: 90\n - sourceAWithGraders:\n - train: 744 \n - validation: 195\n - test: 216\n - sourceB:\n - full: 3219\n- Data Splits:\n - sourceAOnly: sourceA data\n - sourceAWithGraders: sourceA data augmented with Grader's review. In a nutshell, each row becomes three (the original grade plus two graders result)\n - sourceB: sourceB data",
"## Data Considerations\n- Known Limitations:\n- Ethical Considerations:",
"## Additional Information\n- Additional Links: Main code is here\n- Related Datasets: URL"
] | [
50,
13,
31,
53,
17,
210,
17,
22
] | [
"passage: TAGS\n#task_categories-text-classification #size_categories-n<1K #language-Portuguese #license-apache-2.0 #education #aes #enem #region-us \n# Automated Essay Score (AES) ENEM Dataset## Dataset Description\n- Purpose: Automated Essay Scoring\n- Contents: Student Essay Grades\n- Source: URL\n- Size: N<1000## Use Case and Creators\n- Intended Use: Estimate Essay Score\n- Creators: Igor Cataneo Silveira, André Barbosa and Denis Deratani Mauá\n- Contact Information: igorcs@URL; andre.barbosa@URL## Licensing Information\n- License: MIT License\n\nDetails\n- Preferred Citation:## Data Structure\n- Features:\n - id: id of scrapped page. 'id_prompt'+'id' should be unique\n - id_prompt: Essay's theme\n - essay_title: Essay title\n - essay_text: Essay text\n - grades: list of 6 elements containing the grade for each of the five concepts plus the sum of all grades\n - essay_year: Essay's year\n- Number of Instances:\n - sourceAOnly:\n - train: 227\n - validation: 68\n - test: 90\n - sourceAWithGraders:\n - train: 744 \n - validation: 195\n - test: 216\n - sourceB:\n - full: 3219\n- Data Splits:\n - sourceAOnly: sourceA data\n - sourceAWithGraders: sourceA data augmented with Grader's review. In a nutshell, each row becomes three (the original grade plus two graders result)\n - sourceB: sourceB data## Data Considerations\n- Known Limitations:\n- Ethical Considerations:## Additional Information\n- Additional Links: Main code is here\n- Related Datasets: URL"
] |
6fc5ddb5f0450c81d28bd7521928f1a7e14a31df |
# CommonGen-Lite
Evaluating LLMs with [CommonGen](https://inklab.usc.edu/CommonGen/) using [CommonGen-lite](https://huggingface.co/datasets/allenai/commongen_lite) dataset (400 examples + 900 human references).
We use GPT-4 to evaluate the constrained text generation ability of LLMs. Please see more in our [paper](https://arxiv.org/abs/1911.03705).
Github: [https://github.com/allenai/CommonGen-Eval](https://github.com/allenai/CommonGen-Eval)
## Leaderboard
| model | len | cover | pos | win_tie | overall |
|----------------------------|-------|---------|-------|-----------|-----------|
| human | 12.84 | 99.00 | 98.11 | 100.00 | 97.13 |
| gpt-4-0613 | 14.13 | 97.44 | 91.78 | 50.44 | 45.11 |
| gpt-4-1106-preview | 14.90 | 96.33 | 90.11 | 50.78 | 44.08 |
| gpt-3.5-turbo | 12.76 | 92.11 | 83.00 | 49.78 | 38.06 |
| Yi-34b-chat | 13.45 | 80.11 | 75.11 | 39.44 | 23.73 |
| vicuna-13b-v1.5 | 15.02 | 85.89 | 79.56 | 27.44 | 18.75 |
| tulu-2-dpo-70b | 17.89 | 88.78 | 80.11 | 23.00 | 16.36 |
| Mixtral-8x7B-Instruct-v0.1 | 20.15 | 84.11 | 73.33 | 17.89 | 11.03 |
| Llama-2-7b-chat-hf | 16.06 | 88.56 | 76.44 | 15.44 | 10.45 |
| zephyr-7b-beta | 15.76 | 82.44 | 72.78 | 16.89 | 10.13 |
| Yi-6b-chat | 13.32 | 71.67 | 63.56 | 22.11 | 10.07 |
- **length**: the number of words on average in the generated sentences
- **cover**: the percentage of examples where all given concepts are covered by model outputs
- **PoS**: the percentage of examples where the part-of-speech (PoS) of ALL given concepts are correct in model outputs
- **win_tie**: the percentage of examples where GPT-4-turbo prefers the model outputs over the human-written references (or thinks they are equally good)
- **overall**: `cover%` x `pos%` x `win_tie%`
Link: [https://inklab.usc.edu/CommonGen/leaderboard.html](https://inklab.usc.edu/CommonGen/leaderboard.html)
To make your model on the leaderboard, please create an issue or PR to submit the inference script. I'll run the following evaluation script and update the leaderboard.
You will not need to run the evaluation script yourself (the human references are hidden to avoid data leakage).
## Prompts
<details>
<summary>Instruction Prompt Template (2-shots prompting)</summary>
```markdown
# Instruction
Given several concepts (i.e., nouns or verbs), write a short and simple sentence that contains *all* the required words.
The sentence should describe a common scene in daily life, and the concepts should be used in a natural way.
# Examples
## Example 1
- Concepts: "dog(noun), frisbee(noun), catch(verb), throw(verb)"
- Sentence: The dog catches the frisbee when the boy throws it into the air.
## Example 2
- Concepts: "apple(noun), place(verb), tree(noun), pick(verb)"
- Sentence: A girl picks some apples from a tree and places them into her basket.
# Your Task
- Concepts: "{$concept_list}"
- Sentence:
```
</details>
<details>
<summary>Evaluation Prompt Template (Pairwise Comparison)</summary>
```markdown
# Data
Given several concepts (i.e., nouns or verbs), we ask models to write a short and simple sentence that contains *all* the required words.
The sentence should describe a common scene in daily life, and the concepts should be used in a natural way.
Concepts: "{$concept_list}"
Model A: "{$candidate_A}"
Model B: "{$candidate_B}"
# Your Task
Your task is to choose a better sentence from the two candidates. Decide which model's sentence is better in terms of the naturalness and commonness of the scenes they describe.
## Rules:
- A better sentence should describe a common scene in daily life, and all concepts should be used in a natural way.
- You should prefer sentences that use all given concepts with correct part-of-speech tags.
- A simpler and shorter sentence is preferred if it describes the same scene as the other sentence.
- If you think both sentences are equally good or bad, please choose "tie".
Now, please output your choice ("A" or "B" or "tie").
Your choice:
```
</details>
## Case studies
Here are some examples of the generated sentences from the models.
<details>
<summary> Example 1 </summary>
- **Concepts**: `['demonstrate_V', 'machine_N', 'sew_V', 'use_V']`
- **Human Reference**: `She used the sewing machine to demonstrate how well she could sew.`
- **Mixtral-8x7B-Instruct-v0.1**: ` During the fashion design class, the teacher demonstrates how to use the sewing machine to create a stylish outfit.`
--> ```Versus=lose; Cover=False; PoS=False; Len=20```
- **Yi-34b-chat**: `The tailor demonstrates how to use the sewing machine.`
--> ```Versus=win; Cover=False; PoS=False; Len=9```
- **Yi-6b-chat**: `The machine demonstrates how to sew a useful item.`
--> ```Versus=lose; Cover=False; PoS=False; Len=9```
- **Llama-2-7b-chat-hf**: `The teacher demonstrates how to use the sewing machine to sew a new dress, which the student will use to create a beautiful outfit for the school play.`
--> ```Versus=lose; Cover=True; PoS=True; Len=28```
- **zephyr-7b-beta**: `The tailor demonstrates how to use the sewing machine to create garments by allowing the customer to try it out themselves.`
--> ```Versus=lose; Cover=False; PoS=False; Len=21```
- **tulu-2-dpo-70b**: `A woman demonstrates how to use a machine to sew, showing the audience step by step.`
--> ```Versus=lose; Cover=True; PoS=True; Len=16```
- **vicuna-13b-v1.5**: ` The tailor demonstrates how to use the sewing machine to make a dress.`
--> ```Versus=lose; Cover=False; PoS=False; Len=14```
- **gpt-3.5-turbo**: `The tailor uses the sewing machine to demonstrate how to sew a straight line.`
--> ```Versus=lose; Cover=True; PoS=True; Len=14```
- **gpt-4-0613**: `The instructor demonstrates how to use the sewing machine by sewing a piece of fabric.`
--> ```Versus=lose; Cover=True; PoS=True; Len=15```
- **gpt-4-1106-preview**: `The tailor demonstrates how to use the sewing machine by making a small pouch.`
--> ```Versus=win; Cover=False; PoS=False; Len=14```
</details>
<details>
<summary> Example 2 </summary>
- **Concepts**: `['car_N', 'drive_V', 'road_N', 'water_N']`
- **Human Reference**: `A man drives the car slowly because there is water on the road`
- **Mixtral-8x7B-Instruct-v0.1**: ` During the road trip, the family takes breaks to drink water next to the car driving on the open road.`
--> ```Versus=lose; Cover=True; PoS=True; Len=21```
- **Yi-34b-chat**: `The car drives down the road splashing water from the puddles.`
--> ```Versus=win; Cover=True; PoS=True; Len=11```
- **Yi-6b-chat**: `The car drives along the road, avoiding the puddle of water.`
--> ```Versus=win; Cover=True; PoS=True; Len=11```
- **Llama-2-7b-chat-hf**: `The driver drives the car along the road, feeling the water splashing against the tires.`
--> ```Versus=lose; Cover=True; PoS=True; Len=15```
- **zephyr-7b-beta**: `The driver takes the car along the road until they reach a place with water, where they cannot drive anymore.`
--> ```Versus=lose; Cover=True; PoS=True; Len=20```
- **tulu-2-dpo-70b**: `A person drives their car on the road next to a river, where the water is flowing smoothly.`
--> ```Versus=lose; Cover=True; PoS=True; Len=18```
- **vicuna-13b-v1.5**: ` The car drives on the road by the water.`
--> ```Versus=lose; Cover=True; PoS=True; Len=10```
- **gpt-3.5-turbo**: `I drive my car on the road next to the water.`
--> ```Versus=win; Cover=True; PoS=True; Len=11```
- **gpt-4-0613**: `The man drives his car on the road that runs alongside the sparkling water.`
--> ```Versus=lose; Cover=True; PoS=True; Len=14```
- **gpt-4-1106-preview**: `The car drives smoothly on the wet road, splashing water as it goes.`
--> ```Versus=win; Cover=True; PoS=True; Len=13```
</details>
<details>
<summary> Example 3 </summary>
- **Concepts**: `['ceiling_N', 'climb_V', 'gym_N', 'rope_N', 'suspend_V']`
- **Human Reference**: `The boys climbed the rope suspended from the gym ceiling.`
- **Mixtral-8x7B-Instruct-v0.1**: ` During gym class, the students take turns climbing the suspended rope while the others cheer from below, careful not to hit their heads on the ceiling.`
--> ```Versus=lose; Cover=True; PoS=True; Len=27```
- **Yi-34b-chat**: `The gymnast climbs the rope and suspends from the ceiling of the gym.`
--> ```Versus=lose; Cover=True; PoS=True; Len=13```
- **Yi-6b-chat**: `The climber suspends themselves on the rope as they climb the gym's ceiling.`
--> ```Versus=lose; Cover=True; PoS=True; Len=13```
- **Llama-2-7b-chat-hf**: `The gym teacher suspends herself from the ceiling using a rope while climbing to reach the high bar for a workout.`
--> ```Versus=lose; Cover=True; PoS=True; Len=21```
- **zephyr-7b-beta**: `Gymnasts suspend themselves from the ceiling by climbing on the ropes in the gym.`
--> ```Versus=lose; Cover=True; PoS=True; Len=14```
- **tulu-2-dpo-70b**: `In the gym, an athlete climbs a rope suspended from the ceiling to improve their physical fitness.`
--> ```Versus=lose; Cover=True; PoS=True; Len=17```
- **vicuna-13b-v1.5**: ` In the gym, she climbs up to the ceiling using a rope that is suspended from the top.`
--> ```Versus=lose; Cover=True; PoS=True; Len=19```
- **gpt-3.5-turbo**: `In the gym, the athlete climbs the rope and suspends himself from the ceiling.`
--> ```Versus=lose; Cover=True; PoS=True; Len=14```
- **gpt-4-0613**: `In the gym, a man climbs a rope that is suspended from the ceiling.`
--> ```Versus=lose; Cover=True; PoS=True; Len=14```
- **gpt-4-1106-preview**: `In the gym, the rope is suspended from the ceiling for athletes to climb during their workout.`
--> ```Versus=lose; Cover=True; PoS=True; Len=17```
</details>
<details>
<summary> Example 4 </summary>
- **Concepts**: `['hat_N', 'knit_V', 'pile_N', 'rock_N', 'sit_V']`
- **Human Reference**: `The woman sat on a pile of rocks and knitted a hat.`
- **Mixtral-8x7B-Instruct-v0.1**: ` During her break, a woman sits on a rock and starts to knit a pile of hats to sell at the local market.`
--> ```Versus=lose; Cover=True; PoS=True; Len=24```
- **Yi-34b-chat**: `The knitted hat sat on a pile of rocks.`
--> ```Versus=lose; Cover=False; PoS=False; Len=9```
- **Yi-6b-chat**: `The woman knits a cozy hat while sitting on a rock, placing the pile of rocks around her.`
--> ```Versus=lose; Cover=True; PoS=True; Len=18```
- **Llama-2-7b-chat-hf**: `The old man sits on a rock and knits a new hat while piling up the ones he already has, enjoying the peaceful atmosphere.`
--> ```Versus=lose; Cover=True; PoS=False; Len=24```
- **zephyr-7b-beta**: `A woman sits on a rock and knits a hat from a pile of yarn.`
--> ```Versus=lose; Cover=True; PoS=True; Len=15```
- **tulu-2-dpo-70b**: `An elderly woman knits a colorful hat while sitting on a pile of rocks, enjoying the peaceful scenery around her.`
--> ```Versus=lose; Cover=True; PoS=True; Len=20```
- **vicuna-13b-v1.5**: ` The old man sits on a rock and knits a hat in a pile of yarn.`
--> ```Versus=lose; Cover=True; PoS=True; Len=17```
- **gpt-3.5-turbo**: `The old man sits on a rock, wearing a knitted hat, while a pile of leaves gathers around him.`
--> ```Versus=lose; Cover=False; PoS=False; Len=19```
- **gpt-4-0613**: `The woman sits on a rock, knitting a hat, with a pile of yarn beside her.`
--> ```Versus=lose; Cover=True; PoS=True; Len=16```
- **gpt-4-1106-preview**: `She sits on a rock, knitting a hat, and places the finished ones in a colorful pile beside her.`
--> ```Versus=lose; Cover=True; PoS=True; Len=19```
</details>
## Links
- Contact: [Bill Yuchen Lin](https://yuchenlin.xyz/)
- Project website: [https://inklab.usc.edu/CommonGen/](https://inklab.usc.edu/CommonGen/)
- HuggingFace Dataset: [CommonGen-lite](https://huggingface.co/datasets/allenai/commongen_lite)
## Citation
```bibtex
@inproceedings{lin-etal-2020-commongen,
title = "{C}ommon{G}en: A Constrained Text Generation Challenge for Generative Commonsense Reasoning",
author = "Lin, Bill Yuchen and
Zhou, Wangchunshu and
Shen, Ming and
Zhou, Pei and
Bhagavatula, Chandra and
Choi, Yejin and
Ren, Xiang",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.findings-emnlp.165",
pages = "1823--1840",
}
```
| allenai/commongen_lite | [
"task_categories:text-generation",
"size_categories:n<1K",
"language:en",
"license:apache-2.0",
"arxiv:1911.03705",
"region:us"
] | 2024-01-02T23:39:41+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["text-generation"], "pretty_name": "CommonGen-Lite", "configs": [{"config_name": "all"}], "data_files": [{"split": "train"}, {"path": "commongen_hard_nohuman.json"}], "datasets": ["commongen"]} | 2024-01-05T01:40:06+00:00 | [
"1911.03705"
] | [
"en"
] | TAGS
#task_categories-text-generation #size_categories-n<1K #language-English #license-apache-2.0 #arxiv-1911.03705 #region-us
| CommonGen-Lite
==============
Evaluating LLMs with CommonGen using CommonGen-lite dataset (400 examples + 900 human references).
We use GPT-4 to evaluate the constrained text generation ability of LLMs. Please see more in our paper.
Github: URL
Leaderboard
-----------
* length: the number of words on average in the generated sentences
* cover: the percentage of examples where all given concepts are covered by model outputs
* PoS: the percentage of examples where the part-of-speech (PoS) of ALL given concepts are correct in model outputs
* win\_tie: the percentage of examples where GPT-4-turbo prefers the model outputs over the human-written references (or thinks they are equally good)
* overall: 'cover%' x 'pos%' x 'win\_tie%'
Link: URL
To make your model on the leaderboard, please create an issue or PR to submit the inference script. I'll run the following evaluation script and update the leaderboard.
You will not need to run the evaluation script yourself (the human references are hidden to avoid data leakage).
Prompts
-------
Instruction Prompt Template (2-shots prompting)
Evaluation Prompt Template (Pairwise Comparison)
Case studies
------------
Here are some examples of the generated sentences from the models.
Example 1
* Concepts: '['demonstrate\_V', 'machine\_N', 'sew\_V', 'use\_V']'
* Human Reference: 'She used the sewing machine to demonstrate how well she could sew.'
* Mixtral-8x7B-Instruct-v0.1: ' During the fashion design class, the teacher demonstrates how to use the sewing machine to create a stylish outfit.'
-->
* Yi-34b-chat: 'The tailor demonstrates how to use the sewing machine.'
-->
* Yi-6b-chat: 'The machine demonstrates how to sew a useful item.'
-->
* Llama-2-7b-chat-hf: 'The teacher demonstrates how to use the sewing machine to sew a new dress, which the student will use to create a beautiful outfit for the school play.'
-->
* zephyr-7b-beta: 'The tailor demonstrates how to use the sewing machine to create garments by allowing the customer to try it out themselves.'
-->
* tulu-2-dpo-70b: 'A woman demonstrates how to use a machine to sew, showing the audience step by step.'
-->
* vicuna-13b-v1.5: ' The tailor demonstrates how to use the sewing machine to make a dress.'
-->
* gpt-3.5-turbo: 'The tailor uses the sewing machine to demonstrate how to sew a straight line.'
-->
* gpt-4-0613: 'The instructor demonstrates how to use the sewing machine by sewing a piece of fabric.'
-->
* gpt-4-1106-preview: 'The tailor demonstrates how to use the sewing machine by making a small pouch.'
-->
Example 2
* Concepts: '['car\_N', 'drive\_V', 'road\_N', 'water\_N']'
* Human Reference: 'A man drives the car slowly because there is water on the road'
* Mixtral-8x7B-Instruct-v0.1: ' During the road trip, the family takes breaks to drink water next to the car driving on the open road.'
-->
* Yi-34b-chat: 'The car drives down the road splashing water from the puddles.'
-->
* Yi-6b-chat: 'The car drives along the road, avoiding the puddle of water.'
-->
* Llama-2-7b-chat-hf: 'The driver drives the car along the road, feeling the water splashing against the tires.'
-->
* zephyr-7b-beta: 'The driver takes the car along the road until they reach a place with water, where they cannot drive anymore.'
-->
* tulu-2-dpo-70b: 'A person drives their car on the road next to a river, where the water is flowing smoothly.'
-->
* vicuna-13b-v1.5: ' The car drives on the road by the water.'
-->
* gpt-3.5-turbo: 'I drive my car on the road next to the water.'
-->
* gpt-4-0613: 'The man drives his car on the road that runs alongside the sparkling water.'
-->
* gpt-4-1106-preview: 'The car drives smoothly on the wet road, splashing water as it goes.'
-->
Example 3
* Concepts: '['ceiling\_N', 'climb\_V', 'gym\_N', 'rope\_N', 'suspend\_V']'
* Human Reference: 'The boys climbed the rope suspended from the gym ceiling.'
* Mixtral-8x7B-Instruct-v0.1: ' During gym class, the students take turns climbing the suspended rope while the others cheer from below, careful not to hit their heads on the ceiling.'
-->
* Yi-34b-chat: 'The gymnast climbs the rope and suspends from the ceiling of the gym.'
-->
* Yi-6b-chat: 'The climber suspends themselves on the rope as they climb the gym's ceiling.'
-->
* Llama-2-7b-chat-hf: 'The gym teacher suspends herself from the ceiling using a rope while climbing to reach the high bar for a workout.'
-->
* zephyr-7b-beta: 'Gymnasts suspend themselves from the ceiling by climbing on the ropes in the gym.'
-->
* tulu-2-dpo-70b: 'In the gym, an athlete climbs a rope suspended from the ceiling to improve their physical fitness.'
-->
* vicuna-13b-v1.5: ' In the gym, she climbs up to the ceiling using a rope that is suspended from the top.'
-->
* gpt-3.5-turbo: 'In the gym, the athlete climbs the rope and suspends himself from the ceiling.'
-->
* gpt-4-0613: 'In the gym, a man climbs a rope that is suspended from the ceiling.'
-->
* gpt-4-1106-preview: 'In the gym, the rope is suspended from the ceiling for athletes to climb during their workout.'
-->
Example 4
* Concepts: '['hat\_N', 'knit\_V', 'pile\_N', 'rock\_N', 'sit\_V']'
* Human Reference: 'The woman sat on a pile of rocks and knitted a hat.'
* Mixtral-8x7B-Instruct-v0.1: ' During her break, a woman sits on a rock and starts to knit a pile of hats to sell at the local market.'
-->
* Yi-34b-chat: 'The knitted hat sat on a pile of rocks.'
-->
* Yi-6b-chat: 'The woman knits a cozy hat while sitting on a rock, placing the pile of rocks around her.'
-->
* Llama-2-7b-chat-hf: 'The old man sits on a rock and knits a new hat while piling up the ones he already has, enjoying the peaceful atmosphere.'
-->
* zephyr-7b-beta: 'A woman sits on a rock and knits a hat from a pile of yarn.'
-->
* tulu-2-dpo-70b: 'An elderly woman knits a colorful hat while sitting on a pile of rocks, enjoying the peaceful scenery around her.'
-->
* vicuna-13b-v1.5: ' The old man sits on a rock and knits a hat in a pile of yarn.'
-->
* gpt-3.5-turbo: 'The old man sits on a rock, wearing a knitted hat, while a pile of leaves gathers around him.'
-->
* gpt-4-0613: 'The woman sits on a rock, knitting a hat, with a pile of yarn beside her.'
-->
* gpt-4-1106-preview: 'She sits on a rock, knitting a hat, and places the finished ones in a colorful pile beside her.'
-->
Links
-----
* Contact: Bill Yuchen Lin
* Project website: URL
* HuggingFace Dataset: CommonGen-lite
| [] | [
"TAGS\n#task_categories-text-generation #size_categories-n<1K #language-English #license-apache-2.0 #arxiv-1911.03705 #region-us \n"
] | [
48
] | [
"passage: TAGS\n#task_categories-text-generation #size_categories-n<1K #language-English #license-apache-2.0 #arxiv-1911.03705 #region-us \n"
] |
e27352d5f991ff29d5264c048ba8e227ab3e0209 | # Dataset Card for "ARB_transfer_matrix"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | zhan1993/ARB_transfer_matrix | [
"region:us"
] | 2024-01-02T23:49:00+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}], "dataset_info": {"features": [{"name": "expert_name", "dtype": "string"}, {"name": "task_eval_on", "dtype": "string"}, {"name": "score", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 19490, "num_examples": 440}], "download_size": 12510, "dataset_size": 19490}} | 2024-01-02T23:49:01+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ARB_transfer_matrix"
More Information needed | [
"# Dataset Card for \"ARB_transfer_matrix\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"ARB_transfer_matrix\"\n\nMore Information needed"
] | [
6,
17
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"ARB_transfer_matrix\"\n\nMore Information needed"
] |
cb32e7f841f78318214c5889d3a324cacb9dcd72 | # Dataset Card for "ARB_transfer_matrix_v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | zhan1993/ARB_transfer_matrix_v2 | [
"region:us"
] | 2024-01-02T23:49:48+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}], "dataset_info": {"features": [{"name": "expert_name", "dtype": "string"}, {"name": "task_eval_on", "dtype": "string"}, {"name": "score", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 15849, "num_examples": 356}], "download_size": 10642, "dataset_size": 15849}} | 2024-01-02T23:49:50+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ARB_transfer_matrix_v2"
More Information needed | [
"# Dataset Card for \"ARB_transfer_matrix_v2\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"ARB_transfer_matrix_v2\"\n\nMore Information needed"
] | [
6,
20
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"ARB_transfer_matrix_v2\"\n\nMore Information needed"
] |
b8c6b63de433106a3a3d221beeded3d8fd822e01 | # Dataset Card for "cybersec_embedding"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Yemmy1000/cybersec_embedding | [
"region:us"
] | 2024-01-03T00:01:22+00:00 | {"dataset_info": {"features": [{"name": "INSTRUCTION", "dtype": "string"}, {"name": "RESPONSE", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 5951997, "num_examples": 7697}], "download_size": 2761782, "dataset_size": 5951997}} | 2024-01-03T00:01:23+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "cybersec_embedding"
More Information needed | [
"# Dataset Card for \"cybersec_embedding\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"cybersec_embedding\"\n\nMore Information needed"
] | [
6,
16
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"cybersec_embedding\"\n\nMore Information needed"
] |
4b055b67631af010c8fa5805651735d83c5eee8d |
# Colour - Checker Detection - Dataset
An image dataset of colour rendition charts.
This dataset is structured according to [Ultralytics YOLO format](https://docs.ultralytics.com/datasets/detect/#usage) and ready to use with [YOLOv8](https://github.com/ultralytics/ultralytics).
The [colour-science/colour-checker-detection-models](https://huggingface.co/colour-science/colour-checker-detection-models) models resulting from the YOLOv8 segmentation training are supporting colour rendition charts detection in the [Colour Checker Detection](https://github.com/colour-science/colour-checker-detection) Python package.
## Classes
- **ColorCheckerClassic24**: Calibrite / X-Rite ColorCheckerClassic 24
# Contact & Social
The *Colour Developers* can be reached via different means:
- [Email](mailto:[email protected]>)
- [Facebook](https://www.facebook.com/python.colour.science>)
- [Github Discussions](https://github.com/colour-science/colour-checker-detection/discussions>)
- [Gitter](https://gitter.im/colour-science/colour>)
- [Twitter](https://twitter.com/colour_science>)
# About
**Colour - Checker Detection - Dataset** by Colour Developers \
Copyright 2024 Colour Developers – [mailto:[email protected]]([email protected]) \
This software is released under terms of CC-BY-4.0: https://creativecommons.org/licenses/by/4.0/ \
[https://huggingface.co/datasets/colour-science/colour-checker-detection-dataset](https://huggingface.co/datasets/colour-science/colour-checker-detection-dataset)
| colour-science/colour-checker-detection-dataset | [
"task_categories:object-detection",
"size_categories:n<1K",
"license:cc-by-4.0",
"color",
"color-checker",
"color-checker-detection",
"color-science",
"color-space",
"color-spaces",
"colorspace",
"colorspaces",
"colour",
"colour-checker",
"colour-checker-detection",
"colour-science",
"colour-space",
"colour-spaces",
"colourspace",
"colourspaces",
"dataset",
"image",
"segmentation",
"yolo",
"region:us"
] | 2024-01-03T00:16:12+00:00 | {"license": "cc-by-4.0", "size_categories": ["n<1K"], "task_categories": ["object-detection"], "pretty_name": "Colour - Checker Detection - Dataset", "tags": ["color", "color-checker", "color-checker-detection", "color-science", "color-space", "color-spaces", "colorspace", "colorspaces", "colour", "colour-checker", "colour-checker-detection", "colour-science", "colour-space", "colour-spaces", "colourspace", "colourspaces", "dataset", "image", "segmentation", "yolo"]} | 2024-01-03T04:00:39+00:00 | [] | [] | TAGS
#task_categories-object-detection #size_categories-n<1K #license-cc-by-4.0 #color #color-checker #color-checker-detection #color-science #color-space #color-spaces #colorspace #colorspaces #colour #colour-checker #colour-checker-detection #colour-science #colour-space #colour-spaces #colourspace #colourspaces #dataset #image #segmentation #yolo #region-us
|
# Colour - Checker Detection - Dataset
An image dataset of colour rendition charts.
This dataset is structured according to Ultralytics YOLO format and ready to use with YOLOv8.
The colour-science/colour-checker-detection-models models resulting from the YOLOv8 segmentation training are supporting colour rendition charts detection in the Colour Checker Detection Python package.
## Classes
- ColorCheckerClassic24: Calibrite / X-Rite ColorCheckerClassic 24
# Contact & Social
The *Colour Developers* can be reached via different means:
- Email
- Facebook
- Github Discussions
- Gitter
- Twitter
# About
Colour - Checker Detection - Dataset by Colour Developers \
Copyright 2024 Colour Developers – mailto:colour-developers@URL \
This software is released under terms of CC-BY-4.0: URL \
URL
| [
"# Colour - Checker Detection - Dataset\n\nAn image dataset of colour rendition charts.\n\nThis dataset is structured according to Ultralytics YOLO format and ready to use with YOLOv8.\n\nThe colour-science/colour-checker-detection-models models resulting from the YOLOv8 segmentation training are supporting colour rendition charts detection in the Colour Checker Detection Python package.",
"## Classes\n\n- ColorCheckerClassic24: Calibrite / X-Rite ColorCheckerClassic 24",
"# Contact & Social\n\nThe *Colour Developers* can be reached via different means:\n\n- Email\n- Facebook\n- Github Discussions\n- Gitter\n- Twitter",
"# About\n\nColour - Checker Detection - Dataset by Colour Developers \\\nCopyright 2024 Colour Developers – mailto:colour-developers@URL \\\nThis software is released under terms of CC-BY-4.0: URL \\\nURL"
] | [
"TAGS\n#task_categories-object-detection #size_categories-n<1K #license-cc-by-4.0 #color #color-checker #color-checker-detection #color-science #color-space #color-spaces #colorspace #colorspaces #colour #colour-checker #colour-checker-detection #colour-science #colour-space #colour-spaces #colourspace #colourspaces #dataset #image #segmentation #yolo #region-us \n",
"# Colour - Checker Detection - Dataset\n\nAn image dataset of colour rendition charts.\n\nThis dataset is structured according to Ultralytics YOLO format and ready to use with YOLOv8.\n\nThe colour-science/colour-checker-detection-models models resulting from the YOLOv8 segmentation training are supporting colour rendition charts detection in the Colour Checker Detection Python package.",
"## Classes\n\n- ColorCheckerClassic24: Calibrite / X-Rite ColorCheckerClassic 24",
"# Contact & Social\n\nThe *Colour Developers* can be reached via different means:\n\n- Email\n- Facebook\n- Github Discussions\n- Gitter\n- Twitter",
"# About\n\nColour - Checker Detection - Dataset by Colour Developers \\\nCopyright 2024 Colour Developers – mailto:colour-developers@URL \\\nThis software is released under terms of CC-BY-4.0: URL \\\nURL"
] | [
126,
93,
25,
33,
53
] | [
"passage: TAGS\n#task_categories-object-detection #size_categories-n<1K #license-cc-by-4.0 #color #color-checker #color-checker-detection #color-science #color-space #color-spaces #colorspace #colorspaces #colour #colour-checker #colour-checker-detection #colour-science #colour-space #colour-spaces #colourspace #colourspaces #dataset #image #segmentation #yolo #region-us \n# Colour - Checker Detection - Dataset\n\nAn image dataset of colour rendition charts.\n\nThis dataset is structured according to Ultralytics YOLO format and ready to use with YOLOv8.\n\nThe colour-science/colour-checker-detection-models models resulting from the YOLOv8 segmentation training are supporting colour rendition charts detection in the Colour Checker Detection Python package.## Classes\n\n- ColorCheckerClassic24: Calibrite / X-Rite ColorCheckerClassic 24# Contact & Social\n\nThe *Colour Developers* can be reached via different means:\n\n- Email\n- Facebook\n- Github Discussions\n- Gitter\n- Twitter# About\n\nColour - Checker Detection - Dataset by Colour Developers \\\nCopyright 2024 Colour Developers – mailto:colour-developers@URL \\\nThis software is released under terms of CC-BY-4.0: URL \\\nURL"
] |
e7a94912601d40251b3cd59c21ef623cefd4a99a |
# The GOAT Benchmark ([HomePage](https://goatlmm.github.io/))
We introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse. GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content. Our focus is to assess the ability of LMMs to accurately identify online abuse, specifically in terms of hatefulness, misogyny, offensiveness, sarcasm, and harmfulness. We meticulously control for the granularity of each specific meme task to facilitate a detailed analysis. Furthermore, we extend our evaluation to assess the effectiveness of thought chains in discerning the underlying implications of memes for deducing their potential threat to safety.
# Experiment Results
# BibTeX
```
@misc{lin2024goatbench,
title={GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse},
author={Hongzhan Lin and Ziyang Luo and Bo Wang and Ruichao Yang and Jing Ma},
year={2024},
eprint={2401.01523},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
# Ethics and Broader Impact
The aim of this research focuses on the safety issue related to LMMs, to curb the dissemination of abusive memes and protect individuals from exposure to bias, racial, and gender-based discrimination. However, we acknowledge the risk that malicious actors might attempt to reverse-engineer memes that could evade detection by AI systems trained on LMMs. We vehemently discourage and denounce such practices, and emphasize that human moderation is essential to prevent such occurrences. Aware of the potential psychological impact on those evaluating abusive content, we have instituted protective measures for our human evaluators, including: 1) explicit consent regarding exposure to potentially abusive content, 2) a cap on weekly evaluations to manage exposure and advocate for reasonable daily workloads, and 3) recommendations to discontinue their review should they experience distress. We also conduct regular well-being checks to monitor their mental health. Additionally, the use of Facebook’s meme dataset necessitates adherence to Facebook’s terms of use; our use of these memes complies with these terms. It is important to note that all data organized are restricted to meme content and do not include any personal user data.
# License
For the tasks encompassing Misogyny, Offensiveness, Sarcasm, and Harmfulness, the data is provided under the MIT license.
Regarding the task of Hatefulness, the usage of Facebook’s hateful meme dataset requires compliance with Facebook's terms of use. Our utilization of these memes adheres to these terms.
In alignment with Facebook’s licensing conditions for the memes, the GOAT-Bench includes only the annotated text for the Facebook data, and not the actual hateful memes. Users interested in accessing these memes must download them separately from the Facebook Hateful Meme Challenge website: https://hatefulmemeschallenge.com/#download. | HKBU-NLP/GOAT-Bench | [
"language:en",
"arxiv:2401.01523",
"region:us"
] | 2024-01-03T02:03:38+00:00 | {"language": ["en"]} | 2024-01-10T06:41:18+00:00 | [
"2401.01523"
] | [
"en"
] | TAGS
#language-English #arxiv-2401.01523 #region-us
|
# The GOAT Benchmark (HomePage)
 explicit consent regarding exposure to potentially abusive content, 2) a cap on weekly evaluations to manage exposure and advocate for reasonable daily workloads, and 3) recommendations to discontinue their review should they experience distress. We also conduct regular well-being checks to monitor their mental health. Additionally, the use of Facebook’s meme dataset necessitates adherence to Facebook’s terms of use; our use of these memes complies with these terms. It is important to note that all data organized are restricted to meme content and do not include any personal user data.
# License
For the tasks encompassing Misogyny, Offensiveness, Sarcasm, and Harmfulness, the data is provided under the MIT license.
Regarding the task of Hatefulness, the usage of Facebook’s hateful meme dataset requires compliance with Facebook's terms of use. Our utilization of these memes adheres to these terms.
In alignment with Facebook’s licensing conditions for the memes, the GOAT-Bench includes only the annotated text for the Facebook data, and not the actual hateful memes. Users interested in accessing these memes must download them separately from the Facebook Hateful Meme Challenge website: URL | [
"# The GOAT Benchmark (HomePage)\n\n![](URL\n\nWe introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse. GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content. Our focus is to assess the ability of LMMs to accurately identify online abuse, specifically in terms of hatefulness, misogyny, offensiveness, sarcasm, and harmfulness. We meticulously control for the granularity of each specific meme task to facilitate a detailed analysis. Furthermore, we extend our evaluation to assess the effectiveness of thought chains in discerning the underlying implications of memes for deducing their potential threat to safety.",
"# Experiment Results\n\n![](URL\n\n![](URL\n\n![](URL",
"# BibTeX",
"# Ethics and Broader Impact\n\nThe aim of this research focuses on the safety issue related to LMMs, to curb the dissemination of abusive memes and protect individuals from exposure to bias, racial, and gender-based discrimination. However, we acknowledge the risk that malicious actors might attempt to reverse-engineer memes that could evade detection by AI systems trained on LMMs. We vehemently discourage and denounce such practices, and emphasize that human moderation is essential to prevent such occurrences. Aware of the potential psychological impact on those evaluating abusive content, we have instituted protective measures for our human evaluators, including: 1) explicit consent regarding exposure to potentially abusive content, 2) a cap on weekly evaluations to manage exposure and advocate for reasonable daily workloads, and 3) recommendations to discontinue their review should they experience distress. We also conduct regular well-being checks to monitor their mental health. Additionally, the use of Facebook’s meme dataset necessitates adherence to Facebook’s terms of use; our use of these memes complies with these terms. It is important to note that all data organized are restricted to meme content and do not include any personal user data.",
"# License\n\nFor the tasks encompassing Misogyny, Offensiveness, Sarcasm, and Harmfulness, the data is provided under the MIT license.\nRegarding the task of Hatefulness, the usage of Facebook’s hateful meme dataset requires compliance with Facebook's terms of use. Our utilization of these memes adheres to these terms.\nIn alignment with Facebook’s licensing conditions for the memes, the GOAT-Bench includes only the annotated text for the Facebook data, and not the actual hateful memes. Users interested in accessing these memes must download them separately from the Facebook Hateful Meme Challenge website: URL"
] | [
"TAGS\n#language-English #arxiv-2401.01523 #region-us \n",
"# The GOAT Benchmark (HomePage)\n\n![](URL\n\nWe introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse. GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content. Our focus is to assess the ability of LMMs to accurately identify online abuse, specifically in terms of hatefulness, misogyny, offensiveness, sarcasm, and harmfulness. We meticulously control for the granularity of each specific meme task to facilitate a detailed analysis. Furthermore, we extend our evaluation to assess the effectiveness of thought chains in discerning the underlying implications of memes for deducing their potential threat to safety.",
"# Experiment Results\n\n![](URL\n\n![](URL\n\n![](URL",
"# BibTeX",
"# Ethics and Broader Impact\n\nThe aim of this research focuses on the safety issue related to LMMs, to curb the dissemination of abusive memes and protect individuals from exposure to bias, racial, and gender-based discrimination. However, we acknowledge the risk that malicious actors might attempt to reverse-engineer memes that could evade detection by AI systems trained on LMMs. We vehemently discourage and denounce such practices, and emphasize that human moderation is essential to prevent such occurrences. Aware of the potential psychological impact on those evaluating abusive content, we have instituted protective measures for our human evaluators, including: 1) explicit consent regarding exposure to potentially abusive content, 2) a cap on weekly evaluations to manage exposure and advocate for reasonable daily workloads, and 3) recommendations to discontinue their review should they experience distress. We also conduct regular well-being checks to monitor their mental health. Additionally, the use of Facebook’s meme dataset necessitates adherence to Facebook’s terms of use; our use of these memes complies with these terms. It is important to note that all data organized are restricted to meme content and do not include any personal user data.",
"# License\n\nFor the tasks encompassing Misogyny, Offensiveness, Sarcasm, and Harmfulness, the data is provided under the MIT license.\nRegarding the task of Hatefulness, the usage of Facebook’s hateful meme dataset requires compliance with Facebook's terms of use. Our utilization of these memes adheres to these terms.\nIn alignment with Facebook’s licensing conditions for the memes, the GOAT-Bench includes only the annotated text for the Facebook data, and not the actual hateful memes. Users interested in accessing these memes must download them separately from the Facebook Hateful Meme Challenge website: URL"
] | [
19,
188,
18,
5,
282,
154
] | [
"passage: TAGS\n#language-English #arxiv-2401.01523 #region-us \n# The GOAT Benchmark (HomePage)\n\n![](URL\n\nWe introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse. GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content. Our focus is to assess the ability of LMMs to accurately identify online abuse, specifically in terms of hatefulness, misogyny, offensiveness, sarcasm, and harmfulness. We meticulously control for the granularity of each specific meme task to facilitate a detailed analysis. Furthermore, we extend our evaluation to assess the effectiveness of thought chains in discerning the underlying implications of memes for deducing their potential threat to safety.# Experiment Results\n\n![](URL\n\n![](URL\n\n![](URL# BibTeX"
] |
bfd875419004f04870cd558c8b33d060b9a2f7aa | # American Yawp After 1877
This small data set only having a little over 200 rows. Question and answer pairs were generated between Claude and OpenAI. The "Part 2" of the textbook was sliced into 25
chunks of equal size. Then uploaded one at a time into either Claude of OpenAi to generation question and answer pairs based on those chunk of textbook material.
## Prompt
You are an academic assistant for history. Provide detailed information on the content uploaded, for each given question.
Create a table in markdown sql code block with two columns, column 1 is titled "instruction" and column 2 is titled "output".
In which the "instruction" columns ask the questions, and the "output" answers them. Then create 10 questions and answer pairs,
to fill in these columns that are dervied from the attached document.
Format is in both .csv and .json.
## Legal
The American Yawp is an open resource: you are encouraged to use it, download it, distribute it, and modify it as you see fit. The project is formally operated under a
Creative Commons Attribution-Share Alike 4.0 International (CC-BY-SA) License and is designed to meet the standards of a “Free Cultural Work.” We are happy to share it
and we hope you do the same. https://www.americanyawp.com/text/about/ | ambrosfitz/american_yawp_2_small | [
"license:cc-by-sa-4.0",
"region:us"
] | 2024-01-03T02:19:00+00:00 | {"license": "cc-by-sa-4.0"} | 2024-01-03T02:39:42+00:00 | [] | [] | TAGS
#license-cc-by-sa-4.0 #region-us
| # American Yawp After 1877
This small data set only having a little over 200 rows. Question and answer pairs were generated between Claude and OpenAI. The "Part 2" of the textbook was sliced into 25
chunks of equal size. Then uploaded one at a time into either Claude of OpenAi to generation question and answer pairs based on those chunk of textbook material.
## Prompt
You are an academic assistant for history. Provide detailed information on the content uploaded, for each given question.
Create a table in markdown sql code block with two columns, column 1 is titled "instruction" and column 2 is titled "output".
In which the "instruction" columns ask the questions, and the "output" answers them. Then create 10 questions and answer pairs,
to fill in these columns that are dervied from the attached document.
Format is in both .csv and .json.
## Legal
The American Yawp is an open resource: you are encouraged to use it, download it, distribute it, and modify it as you see fit. The project is formally operated under a
Creative Commons Attribution-Share Alike 4.0 International (CC-BY-SA) License and is designed to meet the standards of a “Free Cultural Work.” We are happy to share it
and we hope you do the same. URL | [
"# American Yawp After 1877\n\nThis small data set only having a little over 200 rows. Question and answer pairs were generated between Claude and OpenAI. The \"Part 2\" of the textbook was sliced into 25\nchunks of equal size. Then uploaded one at a time into either Claude of OpenAi to generation question and answer pairs based on those chunk of textbook material.",
"## Prompt\n You are an academic assistant for history. Provide detailed information on the content uploaded, for each given question.\n\n Create a table in markdown sql code block with two columns, column 1 is titled \"instruction\" and column 2 is titled \"output\".\n In which the \"instruction\" columns ask the questions, and the \"output\" answers them. Then create 10 questions and answer pairs,\n to fill in these columns that are dervied from the attached document.\n\nFormat is in both .csv and .json.",
"## Legal\nThe American Yawp is an open resource: you are encouraged to use it, download it, distribute it, and modify it as you see fit. The project is formally operated under a \nCreative Commons Attribution-Share Alike 4.0 International (CC-BY-SA) License and is designed to meet the standards of a “Free Cultural Work.” We are happy to share it \nand we hope you do the same. URL"
] | [
"TAGS\n#license-cc-by-sa-4.0 #region-us \n",
"# American Yawp After 1877\n\nThis small data set only having a little over 200 rows. Question and answer pairs were generated between Claude and OpenAI. The \"Part 2\" of the textbook was sliced into 25\nchunks of equal size. Then uploaded one at a time into either Claude of OpenAi to generation question and answer pairs based on those chunk of textbook material.",
"## Prompt\n You are an academic assistant for history. Provide detailed information on the content uploaded, for each given question.\n\n Create a table in markdown sql code block with two columns, column 1 is titled \"instruction\" and column 2 is titled \"output\".\n In which the \"instruction\" columns ask the questions, and the \"output\" answers them. Then create 10 questions and answer pairs,\n to fill in these columns that are dervied from the attached document.\n\nFormat is in both .csv and .json.",
"## Legal\nThe American Yawp is an open resource: you are encouraged to use it, download it, distribute it, and modify it as you see fit. The project is formally operated under a \nCreative Commons Attribution-Share Alike 4.0 International (CC-BY-SA) License and is designed to meet the standards of a “Free Cultural Work.” We are happy to share it \nand we hope you do the same. URL"
] | [
17,
86,
127,
91
] | [
"passage: TAGS\n#license-cc-by-sa-4.0 #region-us \n# American Yawp After 1877\n\nThis small data set only having a little over 200 rows. Question and answer pairs were generated between Claude and OpenAI. The \"Part 2\" of the textbook was sliced into 25\nchunks of equal size. Then uploaded one at a time into either Claude of OpenAi to generation question and answer pairs based on those chunk of textbook material.## Prompt\n You are an academic assistant for history. Provide detailed information on the content uploaded, for each given question.\n\n Create a table in markdown sql code block with two columns, column 1 is titled \"instruction\" and column 2 is titled \"output\".\n In which the \"instruction\" columns ask the questions, and the \"output\" answers them. Then create 10 questions and answer pairs,\n to fill in these columns that are dervied from the attached document.\n\nFormat is in both .csv and .json.## Legal\nThe American Yawp is an open resource: you are encouraged to use it, download it, distribute it, and modify it as you see fit. The project is formally operated under a \nCreative Commons Attribution-Share Alike 4.0 International (CC-BY-SA) License and is designed to meet the standards of a “Free Cultural Work.” We are happy to share it \nand we hope you do the same. URL"
] |
c158685e2429611293110e12ba9683208fccfdcf |
# Dataset Construction
The `paraphrased questions` are generated by [gpt-3.5-turbo](https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates).
## Prompt Template
```
You are an AI assistant to help me rephrase questions.
Follow the given examples.
Question: Angelo and Melanie want to plan how many hours over the next week they should study together for their test next week. They have 2 chapters of their textbook to study and 4 worksheets to memorize. They figure out that they should dedicate 3 hours to each chapter of their textbook and 1.5 hours for each worksheet. If they plan to study no more than 4 hours each day, how many days should they plan to study total over the next week if they take a 10-minute break every hour, include 3 10-minute snack breaks each day, and 30 minutes for lunch each day?
Rephrase the above question: Angelo and Melanie need to study 2 chapters in their textbook and 4 worksheets for their upcoming test. They have planned to dedicate 3 hours for each chapter and 1.5 hours for each worksheet. They can study for a maximum of 4 hours each day, taking into account 10-minute breaks every hour, 3 10-minute snack breaks per day, and 30 minutes for lunch. How many days do they need to study in total over the next week to complete their study plan?
Question: Leah had 32 chocolates and her sister had 42. If they ate 35, how many pieces do they have left in total?
Rephrase the above question: If Leah had 32 chocolates and her sister had 42, and they both consumed 35 chocolates, what is the total number of chocolates that they have left?
Question: Olivia has $23. She bought five bagels for $3 each. How much money does she have left?
Rephrase the above question: What is the amount of money that Olivia has left after purchasing five bagels for $3 each, if she initially had $23?
Question: There were nine computers in the server room. Five more computers were installed each day, from monday to thursday. How many computers are now in the server room?
Rephrase the above question: If there were initially nine computers in the server room and five more computers were added each day from Monday to Thursday, what is the current total number of computers in the server room?
Question: Michael had 58 golf balls. On tuesday, he lost 23 golf balls. On wednesday, he lost 2 more. How many golf balls did he have at the end of wednesday?
Rephrase the above question: After losing 23 golf balls on Tuesday and an additional 2 on Wednesday, how many golf balls does Michael have left if he initially had 58 golf balls?
Question: Jason had 20 lollipops. He gave Denny some lollipops. Now Jason has 12 lollipops. How many lollipops did Jason give to Denny?
Rephrase the above question: If Jason initially had 20 lollipops and now has 12 after giving some to Denny, how many lollipops did he give to Denny?
Question: Sam bought a dozen boxes, each with 30 highlighter pens inside, for $10 each box. He rearranged five of these boxes into packages of six highlighters each and sold them for $3 per package. He sold the rest of the highlighters separately at the rate of three pens for $2. How much profit did he make in total, in dollars?
Rephrase the above question: Sam purchased 12 boxes, each containing 30 highlighter pens, at $10 per box. He repackaged five of these boxes into sets of six highlighters and sold them for $3 per set. He sold the remaining highlighters individually at a rate of three pens for $2. What is the total profit he made in dollars?
Question: There are 15 trees in the grove. Grove workers will plant trees in the grove today. After they are done, there will be 21 trees. How many trees did the grove workers plant today?
Rephrase the above question: If there were initially 15 trees in the grove and the grove workers are planning to plant more trees today, resulting in a total of 21 trees, how many trees did the workers plant today?
Question: {e['question']}\nRephrase the above question:
```
# Dataset Usage
```python
from datasets import load_dataset
# Load dataset
dataset = load_dataset("shuyuej/gsm8k_testing_chatgpt_generated")
dataset = dataset["test"]
print(dataset)
```
# Citation
If you find our toolkit useful, please consider citing our repo and toolkit in your publications. We provide a BibTeX entry below.
```bibtex
@misc{JiaPromptCraft23,
author = {Jia, Shuyue},
title = {{PromptCraft}: A Prompt Perturbation Toolkit},
year = {2023},
publisher = {GitHub},
journal = {GitHub Repository},
howpublished = {\url{https://github.com/SuperBruceJia/promptcraft}},
}
@misc{JiaAwesomeLLM23,
author = {Jia, Shuyue},
title = {Awesome {LLM} Self-Consistency},
year = {2023},
publisher = {GitHub},
journal = {GitHub Repository},
howpublished = {\url{https://github.com/SuperBruceJia/Awesome-LLM-Self-Consistency}},
}
@misc{JiaAwesomeSTS23,
author = {Jia, Shuyue},
title = {Awesome Semantic Textual Similarity},
year = {2023},
publisher = {GitHub},
journal = {GitHub Repository},
howpublished = {\url{https://github.com/SuperBruceJia/Awesome-Semantic-Textual-Similarity}},
}
``` | shuyuej/gsm8k_testing_chatgpt_generated | [
"license:apache-2.0",
"region:us"
] | 2024-01-03T02:47:39+00:00 | {"license": "apache-2.0"} | 2024-01-25T19:44:31+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
|
# Dataset Construction
The 'paraphrased questions' are generated by gpt-3.5-turbo.
## Prompt Template
# Dataset Usage
If you find our toolkit useful, please consider citing our repo and toolkit in your publications. We provide a BibTeX entry below.
| [
"# Dataset Construction\nThe 'paraphrased questions' are generated by gpt-3.5-turbo.",
"## Prompt Template",
"# Dataset Usage\n\n\nIf you find our toolkit useful, please consider citing our repo and toolkit in your publications. We provide a BibTeX entry below."
] | [
"TAGS\n#license-apache-2.0 #region-us \n",
"# Dataset Construction\nThe 'paraphrased questions' are generated by gpt-3.5-turbo.",
"## Prompt Template",
"# Dataset Usage\n\n\nIf you find our toolkit useful, please consider citing our repo and toolkit in your publications. We provide a BibTeX entry below."
] | [
14,
23,
5,
37
] | [
"passage: TAGS\n#license-apache-2.0 #region-us \n# Dataset Construction\nThe 'paraphrased questions' are generated by gpt-3.5-turbo.## Prompt Template# Dataset Usage\n\n\nIf you find our toolkit useful, please consider citing our repo and toolkit in your publications. We provide a BibTeX entry below."
] |
6ceb7d1421ad15849c367fbf4f2f471e9ba08ec4 | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | SiguienteGlobal/linguistica_assist | [
"size_categories:10K<n<100K",
"language:es",
"license:apache-2.0",
"code",
"doi:10.57967/hf/1674",
"region:us"
] | 2024-01-03T02:54:21+00:00 | {"language": ["es"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "pretty_name": "linguistica_assist", "tags": ["code"]} | 2024-01-03T07:25:15+00:00 | [] | [
"es"
] | TAGS
#size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #code #doi-10.57967/hf/1674 #region-us
| # Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
## Dataset Details
### Dataset Description
- Curated by:
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP):
- License:
### Dataset Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #code #doi-10.57967/hf/1674 #region-us \n",
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
45,
34,
4,
40,
29,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #code #doi-10.57967/hf/1674 #region-us \n# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
162133fe66740c92d19900e614dd14478b42ad02 |
# Howto-Interlink7M
## 📙 Overview
Howto-Interlink7M presents a unique interleaved video-text dataset, carefully derived from the raw video content of [Howto100M](https://www.di.ens.fr/willow/research/howto100m/).
<img src="howto_interlink7m_ppl.png" width="75%" height="75%">
In the creation of this dataset, we turn **a long video into a vision-text interleaved documents** by BLIP2 (Img Captioner), GRIT (Img Detector), Whisper (ASR). Similar to [VLog](https://github.com/showlab/VLog).
Then, we employed the **GPT-4** for an extensive **7 million** high-quality pretraining data.
During this process, we meticulously filtered out clips containing sensitive or low-quality content.
<img src="https://cdn-uploads.huggingface.co/production/uploads/64440be5af034cdfd69ca3a7/tCl0r7zasZwwV1qJF1OJN.png" width="50%" height="50%">
## 📊 Statistics
The statictis are listed below:
| Split | Samples | Average Clips | Average Clip Length | Average Document Tokens |
|---|---|---|---| --- |
| Howto-Interlink7M_subset_w_all_clips_train.tsv | 276711 | 8.4 | 49.8 | 460.3 |
| Howto-Interlink7M_subset_w_all_clips_val.tsv | 30746 | 8.4 | 49.8 | 460.2 |
| Howto-Interlink7M_subset_w_sampled_clips_train.tsv | 660827 | 5.8 | 47.2 |319.4 |
| Howto-Interlink7M_sbset_w_sampled_clips_val.tsv| 73426| 5.8 | 47.2 | 319.8 |
|All| 1041710| 6.6 | 48.0 | 361.0|
## 🎨 Visualization
Please see [Youtube](https://www.youtube.com/watch?v=z3uOI6oInto) for more examples.
## 🏋️ Training
Please refer to code [cosmo](https://github.com/showlab/cosmo/) for training details.
## Download Source Video
### 1. Download the README and All-in-One zip file:
On the official website [HowTo100M](https://www.di.ens.fr/willow/research/howto100m/), locate the download links for the README and the All-in-One zip file.
Extract the contents of the All-in-One zip file:
### 2. Inside the extracted folder, you should find the HowTo100M_v1.csv file.
### 3. In the CSV file, you will find a column named "video_id" which contains unique identifiers for each video.
You can use youtube-dl or similar tools to download the videos using the video IDs listed in the CSV file.
## 🎓 Citation
```
@article{wang2024cosmo,
title={COSMO: Contrastive Streamlined Multimodal Model with Interleaved Pre-Training},
author={Wang, Alex Jinpeng and Li, Linjie and Lin, Kevin Qinghong and Wang Jianfeng and Lin, Kevin and Yang, Zhengyuan and Wang, Lijuan and Shou, Mike Zheng},
journal={arXiv preprint arXiv:2401.00849},
year={2024}
}
``` | Awiny/Howto-Interlink7M | [
"license:apache-2.0",
"region:us"
] | 2024-01-03T03:15:48+00:00 | {"license": "apache-2.0"} | 2024-01-25T04:22:38+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| Howto-Interlink7M
=================
Overview
--------
Howto-Interlink7M presents a unique interleaved video-text dataset, carefully derived from the raw video content of Howto100M.
In the creation of this dataset, we turn a long video into a vision-text interleaved documents by BLIP2 (Img Captioner), GRIT (Img Detector), Whisper (ASR). Similar to VLog.
Then, we employed the GPT-4 for an extensive 7 million high-quality pretraining data.
During this process, we meticulously filtered out clips containing sensitive or low-quality content.
<img src="URL width="50%" height="50%">
Statistics
----------
The statictis are listed below:
Visualization
-------------
!example
Please see Youtube for more examples.
️ Training
----------
Please refer to code cosmo for training details.
Download Source Video
---------------------
### 1. Download the README and All-in-One zip file:
On the official website HowTo100M, locate the download links for the README and the All-in-One zip file.
Extract the contents of the All-in-One zip file:
### 2. Inside the extracted folder, you should find the HowTo100M\_v1.csv file.
### 3. In the CSV file, you will find a column named "video\_id" which contains unique identifiers for each video.
You can use youtube-dl or similar tools to download the videos using the video IDs listed in the CSV file.
Citation
--------
| [
"### 1. Download the README and All-in-One zip file:\n\n\nOn the official website HowTo100M, locate the download links for the README and the All-in-One zip file.\nExtract the contents of the All-in-One zip file:",
"### 2. Inside the extracted folder, you should find the HowTo100M\\_v1.csv file.",
"### 3. In the CSV file, you will find a column named \"video\\_id\" which contains unique identifiers for each video.\n\n\nYou can use youtube-dl or similar tools to download the videos using the video IDs listed in the CSV file.\n\n\nCitation\n--------"
] | [
"TAGS\n#license-apache-2.0 #region-us \n",
"### 1. Download the README and All-in-One zip file:\n\n\nOn the official website HowTo100M, locate the download links for the README and the All-in-One zip file.\nExtract the contents of the All-in-One zip file:",
"### 2. Inside the extracted folder, you should find the HowTo100M\\_v1.csv file.",
"### 3. In the CSV file, you will find a column named \"video\\_id\" which contains unique identifiers for each video.\n\n\nYou can use youtube-dl or similar tools to download the videos using the video IDs listed in the CSV file.\n\n\nCitation\n--------"
] | [
14,
59,
26,
64
] | [
"passage: TAGS\n#license-apache-2.0 #region-us \n### 1. Download the README and All-in-One zip file:\n\n\nOn the official website HowTo100M, locate the download links for the README and the All-in-One zip file.\nExtract the contents of the All-in-One zip file:### 2. Inside the extracted folder, you should find the HowTo100M\\_v1.csv file.### 3. In the CSV file, you will find a column named \"video\\_id\" which contains unique identifiers for each video.\n\n\nYou can use youtube-dl or similar tools to download the videos using the video IDs listed in the CSV file.\n\n\nCitation\n--------"
] |
ef89fc3bc2eab4409061c4f8071f3a7f6d124302 | Download from https://api.python.langchain.com/en/latest/, chunk length set to 400 token.
| caochuxue/langchain-chunked_docs-24-01-03 | [
"region:us"
] | 2024-01-03T03:25:55+00:00 | {} | 2024-01-03T03:29:41+00:00 | [] | [] | TAGS
#region-us
| Download from URL chunk length set to 400 token.
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
0f6ca0218c962e213eb1900d870e2de99b97c19d |
# ibl-khanacademy-transcripts
This dataset houses the transcripts of openly available videos from Khan Academy.
The transcripts were scrapped from [Khan Academy's youtube channel](https://www.youtube.com/@khanacademy) | iblai/ibl-khanacademy-transcripts | [
"size_categories:1K<n<10K",
"language:en",
"license:mit",
"region:us"
] | 2024-01-03T03:34:20+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["1K<n<10K"]} | 2024-01-03T06:19:32+00:00 | [] | [
"en"
] | TAGS
#size_categories-1K<n<10K #language-English #license-mit #region-us
|
# ibl-khanacademy-transcripts
This dataset houses the transcripts of openly available videos from Khan Academy.
The transcripts were scrapped from Khan Academy's youtube channel | [
"# ibl-khanacademy-transcripts\n\nThis dataset houses the transcripts of openly available videos from Khan Academy.\nThe transcripts were scrapped from Khan Academy's youtube channel"
] | [
"TAGS\n#size_categories-1K<n<10K #language-English #license-mit #region-us \n",
"# ibl-khanacademy-transcripts\n\nThis dataset houses the transcripts of openly available videos from Khan Academy.\nThe transcripts were scrapped from Khan Academy's youtube channel"
] | [
27,
44
] | [
"passage: TAGS\n#size_categories-1K<n<10K #language-English #license-mit #region-us \n# ibl-khanacademy-transcripts\n\nThis dataset houses the transcripts of openly available videos from Khan Academy.\nThe transcripts were scrapped from Khan Academy's youtube channel"
] |
3da6a6676dee97ff5236bd28d6bacdff634736b2 |
`BLACK枪骑兵`, `luxenius`, `pansz`, `半佛仙人`, `不想上吊王承恩`,
`曹丰泽`, `炽梦`, `疯死沃`, `弗兰克扬`, `古青`, `关之檀`,
`贺仙`, `槿年`, `框框框子`, `李建秋`, `流浪的蛤蟆`, `摸鱼的王同学`,
`申鹏`, `斯大王`, `托卡马克之冠`, `王克丹`,
`王瑞恩`, `温酒`, `西门豹的精神门徒`, `谢流远`, `竹青`
知乎大V言论 | bzb2023/ZhihuJunkieSpoken | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:zh",
"license:apache-2.0",
"region:us"
] | 2024-01-03T03:43:37+00:00 | {"language": ["zh"], "license": "apache-2.0", "task_categories": ["question-answering", "text-generation"]} | 2024-01-03T03:54:03+00:00 | [] | [
"zh"
] | TAGS
#task_categories-question-answering #task_categories-text-generation #language-Chinese #license-apache-2.0 #region-us
|
'BLACK枪骑兵', 'luxenius', 'pansz', '半佛仙人', '不想上吊王承恩',
'曹丰泽', '炽梦', '疯死沃', '弗兰克扬', '古青', '关之檀',
'贺仙', '槿年', '框框框子', '李建秋', '流浪的蛤蟆', '摸鱼的王同学',
'申鹏', '斯大王', '托卡马克之冠', '王克丹',
'王瑞恩', '温酒', '西门豹的精神门徒', '谢流远', '竹青'
知乎大V言论 | [] | [
"TAGS\n#task_categories-question-answering #task_categories-text-generation #language-Chinese #license-apache-2.0 #region-us \n"
] | [
42
] | [
"passage: TAGS\n#task_categories-question-answering #task_categories-text-generation #language-Chinese #license-apache-2.0 #region-us \n"
] |
52e079d15e8464e4cacf455f260ea0a2a8b491aa |
## Test as readme
Test file it is.
| paranpen/test-data | [
"license:mit",
"region:us"
] | 2024-01-03T04:40:50+00:00 | {"license": "mit"} | 2024-01-03T07:20:42+00:00 | [] | [] | TAGS
#license-mit #region-us
|
## Test as readme
Test file it is.
| [
"## Test as readme\n\n\nTest file it is."
] | [
"TAGS\n#license-mit #region-us \n",
"## Test as readme\n\n\nTest file it is."
] | [
11,
10
] | [
"passage: TAGS\n#license-mit #region-us \n## Test as readme\n\n\nTest file it is."
] |
06a9f3f22b037127305b06f3ca7c9ebc4e96b0a3 | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
A dataset for Chinese Spatial Semantics Understanding.
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [Department of Chinese Language and Literature, Peking University]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [Chinese]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [https://github.com/2030NLP/SpaCE2023]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | 2030NLP/SpaCE2023 | [
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:feature-extraction",
"size_categories:1M<n<10M",
"language:zh",
"region:us"
] | 2024-01-03T05:04:01+00:00 | {"language": ["zh"], "size_categories": ["1M<n<10M"], "task_categories": ["text-classification", "text-generation", "feature-extraction"]} | 2024-01-03T05:39:59+00:00 | [] | [
"zh"
] | TAGS
#task_categories-text-classification #task_categories-text-generation #task_categories-feature-extraction #size_categories-1M<n<10M #language-Chinese #region-us
| # Dataset Card for Dataset Name
A dataset for Chinese Spatial Semantics Understanding.
## Dataset Details
### Dataset Description
- Curated by: [Department of Chinese Language and Literature, Peking University]
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP): [Chinese]
- License:
### Dataset Sources [optional]
- Repository: [URL
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for Dataset Name\n\n\n\nA dataset for Chinese Spatial Semantics Understanding.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: [Department of Chinese Language and Literature, Peking University]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Chinese]\n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: [URL\n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#task_categories-text-classification #task_categories-text-generation #task_categories-feature-extraction #size_categories-1M<n<10M #language-Chinese #region-us \n",
"# Dataset Card for Dataset Name\n\n\n\nA dataset for Chinese Spatial Semantics Understanding.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: [Department of Chinese Language and Literature, Peking University]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Chinese]\n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: [URL\n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
57,
22,
4,
58,
31,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#task_categories-text-classification #task_categories-text-generation #task_categories-feature-extraction #size_categories-1M<n<10M #language-Chinese #region-us \n# Dataset Card for Dataset Name\n\n\n\nA dataset for Chinese Spatial Semantics Understanding.## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: [Department of Chinese Language and Literature, Peking University]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Chinese]\n- License:### Dataset Sources [optional]\n\n\n\n- Repository: [URL\n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
580cef678d940826151fecc20bc4d79d7a921c9f | # Dataset Card for "hellaswag-hi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Thanmay/hellaswag-hi | [
"region:us"
] | 2024-01-03T06:18:58+00:00 | {"dataset_info": {"features": [{"name": "ind", "dtype": "int32"}, {"name": "activity_label", "dtype": "string"}, {"name": "ctx_a", "dtype": "string"}, {"name": "ctx_b", "dtype": "string"}, {"name": "ctx", "dtype": "string"}, {"name": "endings", "sequence": "string"}, {"name": "source_id", "dtype": "string"}, {"name": "split", "dtype": "string"}, {"name": "split_type", "dtype": "string"}, {"name": "label", "dtype": "string"}, {"name": "itv2 hi 0", "dtype": "string"}, {"name": "itv2 hi 1", "dtype": "string"}, {"name": "itv2 hi 2", "dtype": "string"}, {"name": "itv2 hi 3", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 48075015, "num_examples": 10003}, {"name": "validation", "num_bytes": 50007155, "num_examples": 10042}], "download_size": 20134375, "dataset_size": 98082170}, "configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "data/test-*"}, {"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-05T18:18:33+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "hellaswag-hi"
More Information needed | [
"# Dataset Card for \"hellaswag-hi\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"hellaswag-hi\"\n\nMore Information needed"
] | [
6,
15
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"hellaswag-hi\"\n\nMore Information needed"
] |
7662cf5809328f6fc4f1c729d1014315dcd1c5aa | # Dataset Card for "SPECTER2-data"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | andersonbcdefg/SPECTER2-data | [
"region:us"
] | 2024-01-03T06:54:48+00:00 | {"dataset_info": {"features": [{"name": "query", "struct": [{"name": "title", "dtype": "string"}, {"name": "abstract", "dtype": "string"}, {"name": "corpus_id", "dtype": "uint64"}]}, {"name": "pos", "struct": [{"name": "title", "dtype": "string"}, {"name": "abstract", "dtype": "string"}, {"name": "corpus_id", "dtype": "uint64"}]}, {"name": "neg", "struct": [{"name": "title", "dtype": "string"}, {"name": "abstract", "dtype": "string"}, {"name": "corpus_id", "dtype": "uint64"}]}], "splits": [{"name": "train", "num_bytes": 2069439948, "num_examples": 475656}], "download_size": 1222811951, "dataset_size": 2069439948}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T23:32:02+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "SPECTER2-data"
More Information needed | [
"# Dataset Card for \"SPECTER2-data\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"SPECTER2-data\"\n\nMore Information needed"
] | [
6,
14
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"SPECTER2-data\"\n\nMore Information needed"
] |
f17b31a62c328b9e91754782830d70ae343645cf |
### Dataset Summary
This dataset contains the data for personalized passkey retrieval task in the paper [Improving Text Embeddings with Large Language Models](https://arxiv.org/pdf/2401.00368.pdf).
### Data Fields
- `query`: a `string` feature.
- `candidates`: List of `string` feature, 100 candidates for each query.
- `label`: a `int32` feature, the index of the correct candidate in the candidates list, always 0.
- `context_length`: a `int32` feature, the approximate length for the candidate documents.
### How to use this dataset
You can load the dataset in your python code as follows:
```python
from datasets import load_dataset
dataset = load_dataset("intfloat/personalized_passkey_retrieval")
```
The data in this repo is generated by the script [generate_passkey_data.py](https://huggingface.co/datasets/intfloat/personalized_passkey_retrieval/blob/main/generate_passkey_data.py).
You can also tweak the script to generate your own data.
### Citation Information
If you use this dataset in your research, please cite this paper:
```
@inproceedings{Wang2023ImprovingTE,
title={Improving Text Embeddings with Large Language Models},
author={Liang Wang and Nan Yang and Xiaolong Huang and Linjun Yang and Rangan Majumder and Furu Wei},
year={2023},
}
``` | intfloat/personalized_passkey_retrieval | [
"size_categories:n<1K",
"language:en",
"license:apache-2.0",
"arxiv:2401.00368",
"region:us"
] | 2024-01-03T07:25:50+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["n<1K"]} | 2024-01-03T08:16:46+00:00 | [
"2401.00368"
] | [
"en"
] | TAGS
#size_categories-n<1K #language-English #license-apache-2.0 #arxiv-2401.00368 #region-us
|
### Dataset Summary
This dataset contains the data for personalized passkey retrieval task in the paper Improving Text Embeddings with Large Language Models.
### Data Fields
- 'query': a 'string' feature.
- 'candidates': List of 'string' feature, 100 candidates for each query.
- 'label': a 'int32' feature, the index of the correct candidate in the candidates list, always 0.
- 'context_length': a 'int32' feature, the approximate length for the candidate documents.
### How to use this dataset
You can load the dataset in your python code as follows:
The data in this repo is generated by the script generate_passkey_data.py.
You can also tweak the script to generate your own data.
If you use this dataset in your research, please cite this paper:
| [
"### Dataset Summary\n\nThis dataset contains the data for personalized passkey retrieval task in the paper Improving Text Embeddings with Large Language Models.",
"### Data Fields\n\n- 'query': a 'string' feature.\n- 'candidates': List of 'string' feature, 100 candidates for each query.\n- 'label': a 'int32' feature, the index of the correct candidate in the candidates list, always 0.\n- 'context_length': a 'int32' feature, the approximate length for the candidate documents.",
"### How to use this dataset\n\nYou can load the dataset in your python code as follows:\n\n\n\nThe data in this repo is generated by the script generate_passkey_data.py.\nYou can also tweak the script to generate your own data.\n\n\n\nIf you use this dataset in your research, please cite this paper:"
] | [
"TAGS\n#size_categories-n<1K #language-English #license-apache-2.0 #arxiv-2401.00368 #region-us \n",
"### Dataset Summary\n\nThis dataset contains the data for personalized passkey retrieval task in the paper Improving Text Embeddings with Large Language Models.",
"### Data Fields\n\n- 'query': a 'string' feature.\n- 'candidates': List of 'string' feature, 100 candidates for each query.\n- 'label': a 'int32' feature, the index of the correct candidate in the candidates list, always 0.\n- 'context_length': a 'int32' feature, the approximate length for the candidate documents.",
"### How to use this dataset\n\nYou can load the dataset in your python code as follows:\n\n\n\nThe data in this repo is generated by the script generate_passkey_data.py.\nYou can also tweak the script to generate your own data.\n\n\n\nIf you use this dataset in your research, please cite this paper:"
] | [
36,
39,
94,
72
] | [
"passage: TAGS\n#size_categories-n<1K #language-English #license-apache-2.0 #arxiv-2401.00368 #region-us \n### Dataset Summary\n\nThis dataset contains the data for personalized passkey retrieval task in the paper Improving Text Embeddings with Large Language Models.### Data Fields\n\n- 'query': a 'string' feature.\n- 'candidates': List of 'string' feature, 100 candidates for each query.\n- 'label': a 'int32' feature, the index of the correct candidate in the candidates list, always 0.\n- 'context_length': a 'int32' feature, the approximate length for the candidate documents.### How to use this dataset\n\nYou can load the dataset in your python code as follows:\n\n\n\nThe data in this repo is generated by the script generate_passkey_data.py.\nYou can also tweak the script to generate your own data.\n\n\n\nIf you use this dataset in your research, please cite this paper:"
] |
f55b23a942608083cffe2813c803d3517ebb1e41 | # 姜子牙写作任务中文评估数据集 Ziya-Writing-Eval-Chinese
### 数据介绍 Dataset Summary
用于评估大语言模型在中文写作任务上的水平，通常采用Side-by-Side评测；
本评测集包含了以下几个写作子任务：
- 应用写作
- 公文
- 通知
- 报告
- 论文
- 征稿
- 函件
- 申请书
- 创意写作
- 书信
- 作文
- 文案
- 小说
- 视频脚本
- 攻略
- 广告
- 剧本
- 童话
This evaluation set is used to assess the proficiency of large language models in Chinese writing tasks, typically through Side-by-Side evaluation.
This evaluation set includes the following writing sub-tasks:
- Application Writing
- Official documents
- Notices
- Reports
- Papers
- Call for papers
- Letters
- Application letters
- Creative Writing
- Letters
- Essays
- Copywriting
- Novels
- Video scripts
- Guides
- Advertisements
- Scripts
- Fairy tales
### 语言 Languages
中文
Chinese
### 数据示例 Data Instances
```json
{"question_id":"161", "text":"以大学生的视角，写一篇针对某位男大学生运动员铅球的通讯稿，200字左右，要求慷慨激昂，富有文采，彰显出男运动员的青春与矫健，段落节奏抑扬n
顿挫", "category": "写作"}
```
### 引用 Citation
```
@article{fengshenbang,
author = {Jiaxing Zhang and Ruyi Gan and Junjie Wang and Yuxiang Zhang and Lin Zhang and Ping Yang and Xinyu Gao and Ziwei Wu and Xiaoqun Dong and Junqing He and Jianheng Zhuo and Qi Yang and Yongfeng Huang and Xiayu Li and Yanghan Wu and Junyu Lu and Xinyu Zhu and Weifeng Chen and Ting Han and Kunhao Pan and Rui Wang and Hao Wang and Xiaojun Wu and Zhongshen Zeng and Chongpei Chen},
title = {Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence},
journal = {CoRR},
volume = {abs/2209.02970},
year = {2022}
}
```
| IDEA-CCNL/Ziya-Writing-Eval-Chinese | [
"size_categories:n<1K",
"language:zh",
"license:apache-2.0",
"region:us"
] | 2024-01-03T07:29:32+00:00 | {"language": ["zh"], "license": "apache-2.0", "size_categories": ["n<1K"], "pretty_name": "Ziya-Writing-Eval-Chinese"} | 2024-01-03T07:44:48+00:00 | [] | [
"zh"
] | TAGS
#size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us
| # 姜子牙写作任务中文评估数据集 Ziya-Writing-Eval-Chinese
### 数据介绍 Dataset Summary
用于评估大语言模型在中文写作任务上的水平，通常采用Side-by-Side评测；
本评测集包含了以下几个写作子任务：
- 应用写作
- 公文
- 通知
- 报告
- 论文
- 征稿
- 函件
- 申请书
- 创意写作
- 书信
- 作文
- 文案
- 小说
- 视频脚本
- 攻略
- 广告
- 剧本
- 童话
This evaluation set is used to assess the proficiency of large language models in Chinese writing tasks, typically through Side-by-Side evaluation.
This evaluation set includes the following writing sub-tasks:
- Application Writing
- Official documents
- Notices
- Reports
- Papers
- Call for papers
- Letters
- Application letters
- Creative Writing
- Letters
- Essays
- Copywriting
- Novels
- Video scripts
- Guides
- Advertisements
- Scripts
- Fairy tales
### 语言 Languages
中文
Chinese
### 数据示例 Data Instances
### 引用 Citation
| [
"# 姜子牙写作任务中文评估数据集 Ziya-Writing-Eval-Chinese",
"### 数据介绍 Dataset Summary\n\n用于评估大语言模型在中文写作任务上的水平，通常采用Side-by-Side评测；\n\n本评测集包含了以下几个写作子任务：\n- 应用写作\n - 公文\n - 通知\n - 报告\n - 论文\n - 征稿\n - 函件\n - 申请书\n- 创意写作\n - 书信\n - 作文\n - 文案\n - 小说\n - 视频脚本\n - 攻略\n - 广告\n - 剧本\n - 童话\n\nThis evaluation set is used to assess the proficiency of large language models in Chinese writing tasks, typically through Side-by-Side evaluation.\n\nThis evaluation set includes the following writing sub-tasks:\n- Application Writing\n - Official documents\n - Notices\n - Reports\n - Papers\n - Call for papers\n - Letters\n - Application letters\n- Creative Writing\n - Letters\n - Essays\n - Copywriting\n - Novels\n - Video scripts\n - Guides\n - Advertisements\n - Scripts\n - Fairy tales",
"### 语言 Languages\n\n中文\n\nChinese",
"### 数据示例 Data Instances",
"### 引用 Citation"
] | [
"TAGS\n#size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us \n",
"# 姜子牙写作任务中文评估数据集 Ziya-Writing-Eval-Chinese",
"### 数据介绍 Dataset Summary\n\n用于评估大语言模型在中文写作任务上的水平，通常采用Side-by-Side评测；\n\n本评测集包含了以下几个写作子任务：\n- 应用写作\n - 公文\n - 通知\n - 报告\n - 论文\n - 征稿\n - 函件\n - 申请书\n- 创意写作\n - 书信\n - 作文\n - 文案\n - 小说\n - 视频脚本\n - 攻略\n - 广告\n - 剧本\n - 童话\n\nThis evaluation set is used to assess the proficiency of large language models in Chinese writing tasks, typically through Side-by-Side evaluation.\n\nThis evaluation set includes the following writing sub-tasks:\n- Application Writing\n - Official documents\n - Notices\n - Reports\n - Papers\n - Call for papers\n - Letters\n - Application letters\n- Creative Writing\n - Letters\n - Essays\n - Copywriting\n - Novels\n - Video scripts\n - Guides\n - Advertisements\n - Scripts\n - Fairy tales",
"### 语言 Languages\n\n中文\n\nChinese",
"### 数据示例 Data Instances",
"### 引用 Citation"
] | [
29,
22,
217,
9,
10,
6
] | [
"passage: TAGS\n#size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us \n# 姜子牙写作任务中文评估数据集 Ziya-Writing-Eval-Chinese### 数据介绍 Dataset Summary\n\n用于评估大语言模型在中文写作任务上的水平，通常采用Side-by-Side评测；\n\n本评测集包含了以下几个写作子任务：\n- 应用写作\n - 公文\n - 通知\n - 报告\n - 论文\n - 征稿\n - 函件\n - 申请书\n- 创意写作\n - 书信\n - 作文\n - 文案\n - 小说\n - 视频脚本\n - 攻略\n - 广告\n - 剧本\n - 童话\n\nThis evaluation set is used to assess the proficiency of large language models in Chinese writing tasks, typically through Side-by-Side evaluation.\n\nThis evaluation set includes the following writing sub-tasks:\n- Application Writing\n - Official documents\n - Notices\n - Reports\n - Papers\n - Call for papers\n - Letters\n - Application letters\n- Creative Writing\n - Letters\n - Essays\n - Copywriting\n - Novels\n - Video scripts\n - Guides\n - Advertisements\n - Scripts\n - Fairy tales### 语言 Languages\n\n中文\n\nChinese### 数据示例 Data Instances### 引用 Citation"
] |
f95b619fa0c06e7acd476aced61ddf136c4a89a6 | # Dataset Card for "30000-50000-ultrafeedback-ita"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | giux78/30000-50000-ultrafeedback-ita | [
"region:us"
] | 2024-01-03T07:33:32+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "test_gen", "path": "data/test_gen-*"}, {"split": "test_sft", "path": "data/test_sft-*"}, {"split": "train_gen", "path": "data/train_gen-*"}, {"split": "train_sft", "path": "data/train_sft-*"}]}], "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "prompt_id", "dtype": "string"}, {"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "test_gen", "num_bytes": 148276089, "num_examples": 28304}, {"name": "test_sft", "num_bytes": 154695659, "num_examples": 23110}, {"name": "train_gen", "num_bytes": 1347396812, "num_examples": 256032}, {"name": "train_sft", "num_bytes": 147532124, "num_examples": 20000}], "download_size": 969934883, "dataset_size": 1797900684}} | 2024-01-03T07:34:33+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "30000-50000-ultrafeedback-ita"
More Information needed | [
"# Dataset Card for \"30000-50000-ultrafeedback-ita\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"30000-50000-ultrafeedback-ita\"\n\nMore Information needed"
] | [
6,
21
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"30000-50000-ultrafeedback-ita\"\n\nMore Information needed"
] |
e08127c1a6edf46523561fda3e5ade4dbb4e1ae4 |
# Dataset Card for emotion-custom
This dataset has been created with [Argilla](https://docs.argilla.io).
As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
## Dataset Description
- **Homepage:** https://argilla.io
- **Repository:** https://github.com/argilla-io/argilla
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset contains:
* A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla.
* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` and can be loaded independently using the `datasets` library via `load_dataset`.
* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
### Load with Argilla
To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
```python
import argilla as rg
ds = rg.FeedbackDataset.from_huggingface("Avimaster/emotion-custom")
```
### Load with `datasets`
To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
```python
from datasets import load_dataset
ds = load_dataset("Avimaster/emotion-custom")
```
### Supported Tasks and Leaderboards
This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure).
There are no leaderboards associated with this dataset.
### Languages
[More Information Needed]
## Dataset Structure
### Data in Argilla
The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
The **fields** are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| text | Text | text | True | False |
The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| sentiment | Sentiment | label_selection | True | N/A | ['positive', 'neutral', 'negative'] |
| mixed-emotion | Mixed-emotion | multi_label_selection | True | N/A | ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'] |
The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
The **metadata** is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |
The **guidelines**, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section.
### Data Instances
An example of a dataset instance in Argilla looks as follows:
```json
{
"external_id": null,
"fields": {
"text": "i didnt feel humiliated"
},
"metadata": {},
"responses": [
{
"status": "submitted",
"user_id": "b168d9ba-1b5f-47ee-a69d-f9ecd66c522e",
"values": {
"mixed-emotion": {
"value": [
"joy",
"love"
]
},
"sentiment": {
"value": "positive"
}
}
}
],
"suggestions": [],
"vectors": {}
}
```
While the same record in HuggingFace `datasets` looks as follows:
```json
{
"external_id": null,
"metadata": "{}",
"mixed-emotion": [
{
"status": "submitted",
"user_id": "b168d9ba-1b5f-47ee-a69d-f9ecd66c522e",
"value": [
"joy",
"love"
]
}
],
"mixed-emotion-suggestion": null,
"mixed-emotion-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
},
"sentiment": [
{
"status": "submitted",
"user_id": "b168d9ba-1b5f-47ee-a69d-f9ecd66c522e",
"value": "positive"
}
],
"sentiment-suggestion": null,
"sentiment-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
},
"text": "i didnt feel humiliated"
}
```
### Data Fields
Among the dataset fields, we differentiate between the following:
* **Fields:** These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
* **text** is of type `text`.
* **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.
* **sentiment** is of type `label_selection` with the following allowed values ['positive', 'neutral', 'negative'].
* **mixed-emotion** is of type `multi_label_selection` with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].
* **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
* (optional) **sentiment-suggestion** is of type `label_selection` with the following allowed values ['positive', 'neutral', 'negative'].
* (optional) **mixed-emotion-suggestion** is of type `multi_label_selection` with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].
Additionally, we also have two more fields that are optional and are the following:
* **metadata:** This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
* **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.
### Data Splits
The dataset contains a single split, which is `train`.
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation guidelines
Emotion is a dataset of English Twitter messages with six basic emotions: anger, fear, joy, love, sadness, and surprise.
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] | Avimaster/emotion-custom | [
"size_categories:n<1K",
"rlfh",
"argilla",
"human-feedback",
"region:us"
] | 2024-01-03T07:35:52+00:00 | {"size_categories": "n<1K", "tags": ["rlfh", "argilla", "human-feedback"]} | 2024-01-03T07:36:11+00:00 | [] | [] | TAGS
#size_categories-n<1K #rlfh #argilla #human-feedback #region-us
| Dataset Card for emotion-custom
===============================
This dataset has been created with Argilla.
As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the 'datasets' library in Load with 'datasets'.
Dataset Description
-------------------
* Homepage: URL
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact:
### Dataset Summary
This dataset contains:
* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.
### Load with Argilla
To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:
### Load with 'datasets'
To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:
### Supported Tasks and Leaderboards
This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.
There are no leaderboards associated with this dataset.
### Languages
Dataset Structure
-----------------
### Data in Argilla
The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.
The fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\_selection, multi\_label\_selection, or ranking.
The suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
The metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\_properties' defined in the dataset configuration file in 'URL'.
The guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.
### Data Instances
An example of a dataset instance in Argilla looks as follows:
While the same record in HuggingFace 'datasets' looks as follows:
### Data Fields
Among the dataset fields, we differentiate between the following:
* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
+ text is of type 'text'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.
+ sentiment is of type 'label\_selection' with the following allowed values ['positive', 'neutral', 'negative'].
+ mixed-emotion is of type 'multi\_label\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].
* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
+ (optional) sentiment-suggestion is of type 'label\_selection' with the following allowed values ['positive', 'neutral', 'negative'].
+ (optional) mixed-emotion-suggestion is of type 'multi\_label\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].
Additionally, we also have two more fields that are optional and are the following:
* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\_properties' defined in the dataset configuration file in 'URL'.
* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.
### Data Splits
The dataset contains a single split, which is 'train'.
Dataset Creation
----------------
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation guidelines
Emotion is a dataset of English Twitter messages with six basic emotions: anger, fear, joy, love, sadness, and surprise.
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
Considerations for Using the Data
---------------------------------
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
Additional Information
----------------------
### Dataset Curators
### Licensing Information
### Contributions
| [
"### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.",
"### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:",
"### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:",
"### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.",
"### Languages\n\n\nDataset Structure\n-----------------",
"### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.",
"### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:",
"### Data Fields\n\n\nAmong the dataset fields, we differentiate between the following:\n\n\n* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\t+ text is of type 'text'.\n* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.\n\n\n\t+ sentiment is of type 'label\\_selection' with the following allowed values ['positive', 'neutral', 'negative'].\n\t+ mixed-emotion is of type 'multi\\_label\\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].\n* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.\n\n\n\t+ (optional) sentiment-suggestion is of type 'label\\_selection' with the following allowed values ['positive', 'neutral', 'negative'].\n\t+ (optional) mixed-emotion-suggestion is of type 'multi\\_label\\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].\n\n\nAdditionally, we also have two more fields that are optional and are the following:\n\n\n* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n* external\\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.",
"### Data Splits\n\n\nThe dataset contains a single split, which is 'train'.\n\n\nDataset Creation\n----------------",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### Annotation guidelines\n\n\nEmotion is a dataset of English Twitter messages with six basic emotions: anger, fear, joy, love, sadness, and surprise.",
"#### Annotation process",
"#### Who are the annotators?",
"### Personal and Sensitive Information\n\n\nConsiderations for Using the Data\n---------------------------------",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations\n\n\nAdditional Information\n----------------------",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] | [
"TAGS\n#size_categories-n<1K #rlfh #argilla #human-feedback #region-us \n",
"### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.",
"### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:",
"### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:",
"### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.",
"### Languages\n\n\nDataset Structure\n-----------------",
"### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.",
"### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:",
"### Data Fields\n\n\nAmong the dataset fields, we differentiate between the following:\n\n\n* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\t+ text is of type 'text'.\n* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.\n\n\n\t+ sentiment is of type 'label\\_selection' with the following allowed values ['positive', 'neutral', 'negative'].\n\t+ mixed-emotion is of type 'multi\\_label\\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].\n* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.\n\n\n\t+ (optional) sentiment-suggestion is of type 'label\\_selection' with the following allowed values ['positive', 'neutral', 'negative'].\n\t+ (optional) mixed-emotion-suggestion is of type 'multi\\_label\\_selection' with the following allowed values ['joy', 'anger', 'sadness', 'fear', 'surprise', 'love'].\n\n\nAdditionally, we also have two more fields that are optional and are the following:\n\n\n* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n* external\\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.",
"### Data Splits\n\n\nThe dataset contains a single split, which is 'train'.\n\n\nDataset Creation\n----------------",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### Annotation guidelines\n\n\nEmotion is a dataset of English Twitter messages with six basic emotions: anger, fear, joy, love, sadness, and surprise.",
"#### Annotation process",
"#### Who are the annotators?",
"### Personal and Sensitive Information\n\n\nConsiderations for Using the Data\n---------------------------------",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations\n\n\nAdditional Information\n----------------------",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] | [
27,
162,
40,
53,
68,
11,
404,
40,
597,
27,
7,
4,
10,
10,
5,
36,
5,
9,
18,
7,
8,
14,
6,
6,
5
] | [
"passage: TAGS\n#size_categories-n<1K #rlfh #argilla #human-feedback #region-us \n### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.### Languages\n\n\nDataset Structure\n-----------------",
"passage: ### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:"
] |
521a5c9ea68422ca10de63300d981e4d5b88a2d3 | # Dataset Card for "alpaca_in_mixtral_format"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | fxmeng/alpaca_in_mixtral_format | [
"region:us"
] | 2024-01-03T07:56:41+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 20350215, "num_examples": 52002}], "download_size": 11773876, "dataset_size": 20350215}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T07:56:49+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "alpaca_in_mixtral_format"
More Information needed | [
"# Dataset Card for \"alpaca_in_mixtral_format\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"alpaca_in_mixtral_format\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"alpaca_in_mixtral_format\"\n\nMore Information needed"
] |
af83abe58c5de3e999ad4e5855a7d3d3b07c9aee | Incoming Email Response
Hello Amirsha sir I thank you for this opportunity but as I am out of station I will not be able to attend the interview on the scheduled date .So I am sorry for the inconvenience .So please do consider my request and reschedule the interview as soon as possible after 3 -01-2024.I hope you will understand my situation and do the needful. Okay, I will schedule it for January 4th, 2023, at 11:30 AM | adudgaon/email_responses | [
"license:mit",
"region:us"
] | 2024-01-03T08:11:02+00:00 | {"license": "mit"} | 2024-01-03T08:17:15+00:00 | [] | [] | TAGS
#license-mit #region-us
| Incoming Email Response
Hello Amirsha sir I thank you for this opportunity but as I am out of station I will not be able to attend the interview on the scheduled date .So I am sorry for the inconvenience .So please do consider my request and reschedule the interview as soon as possible after 3 -01-2024.I hope you will understand my situation and do the needful. Okay, I will schedule it for January 4th, 2023, at 11:30 AM | [] | [
"TAGS\n#license-mit #region-us \n"
] | [
11
] | [
"passage: TAGS\n#license-mit #region-us \n"
] |
f69b7ee681c8c4e9bf76e6a340028d96bd269ff6 |
Weights for the pre-trained DewarpNet model developed by Das et al. (2019).
The code for the model can be found on https://github.com/cvlab-stonybrook/DewarpNet. | docdewarper/dewarpnet_weights | [
"license:mit",
"region:us"
] | 2024-01-03T08:32:59+00:00 | {"license": "mit"} | 2024-01-03T08:42:04+00:00 | [] | [] | TAGS
#license-mit #region-us
|
Weights for the pre-trained DewarpNet model developed by Das et al. (2019).
The code for the model can be found on URL | [] | [
"TAGS\n#license-mit #region-us \n"
] | [
11
] | [
"passage: TAGS\n#license-mit #region-us \n"
] |
9b7a759fae80112de8b09fd5069d9f4438fcfc87 | # Dataset Card for "ultrachat_hindi_seamless"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | apurvagup/ultrachat_hindi_seamless | [
"region:us"
] | 2024-01-03T08:33:48+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train_sft", "path": "data/train_sft-*"}, {"split": "test_sft", "path": "data/test_sft-*"}]}], "dataset_info": {"features": [{"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "train_sft", "num_bytes": 2761401316, "num_examples": 185542}, {"name": "test_sft", "num_bytes": 147845678, "num_examples": 10000}], "download_size": 952634359, "dataset_size": 2909246994}} | 2024-01-03T14:13:46+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ultrachat_hindi_seamless"
More Information needed | [
"# Dataset Card for \"ultrachat_hindi_seamless\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"ultrachat_hindi_seamless\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"ultrachat_hindi_seamless\"\n\nMore Information needed"
] |
f5ae15088641e4facf4162f1e20ad79539de5c02 | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [Aniket Kumar]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [Indian Language]
- **License:** [Free to use]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | Threatthriver/General_Text_Data | [
"task_categories:text-classification",
"size_categories:10M<n<100M",
"language:hi",
"language:en",
"language:ta",
"climate",
"region:us"
] | 2024-01-03T08:35:32+00:00 | {"language": ["hi", "en", "ta"], "size_categories": ["10M<n<100M"], "task_categories": ["text-classification"], "tags": ["climate"]} | 2024-01-03T08:46:34+00:00 | [] | [
"hi",
"en",
"ta"
] | TAGS
#task_categories-text-classification #size_categories-10M<n<100M #language-Hindi #language-English #language-Tamil #climate #region-us
| # Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
## Dataset Details
### Dataset Description
- Curated by: [Aniket Kumar]
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP): [Indian Language]
- License: [Free to use]
### Dataset Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: [Aniket Kumar]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Indian Language]\n- License: [Free to use]",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#task_categories-text-classification #size_categories-10M<n<100M #language-Hindi #language-English #language-Tamil #climate #region-us \n",
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: [Aniket Kumar]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Indian Language]\n- License: [Free to use]",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
45,
34,
4,
56,
29,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#task_categories-text-classification #size_categories-10M<n<100M #language-Hindi #language-English #language-Tamil #climate #region-us \n# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: [Aniket Kumar]\n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): [Indian Language]\n- License: [Free to use]### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
9c18d84553f67f3f4e0bd1756bcf33f1030479cd | # Dataset Card for "CVE-2023-25690_testLLM"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Nganlt/CVEs_10 | [
"region:us"
] | 2024-01-03T08:35:38+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 33169, "num_examples": 150}], "download_size": 12485, "dataset_size": 33169}} | 2024-01-04T07:50:31+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "CVE-2023-25690_testLLM"
More Information needed | [
"# Dataset Card for \"CVE-2023-25690_testLLM\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"CVE-2023-25690_testLLM\"\n\nMore Information needed"
] | [
6,
20
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"CVE-2023-25690_testLLM\"\n\nMore Information needed"
] |
d70d8d017518f926b6a2fc6722d6d0dd4b62797c | # Dataset Card for "bioacoustic_segments"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | adilhabibi/bioacoustic_segments | [
"region:us"
] | 2024-01-03T08:36:22+00:00 | {"dataset_info": {"features": [{"name": "segments", "sequence": {"sequence": {"sequence": "float32"}}}, {"name": "label_idices", "dtype": "int64"}, {"name": "label_names", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 72803953, "num_examples": 1457}], "download_size": 53309954, "dataset_size": 72803953}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T08:36:41+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "bioacoustic_segments"
More Information needed | [
"# Dataset Card for \"bioacoustic_segments\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"bioacoustic_segments\"\n\nMore Information needed"
] | [
6,
17
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"bioacoustic_segments\"\n\nMore Information needed"
] |
40de7136fbcdf92b4ffa8f7e6f72209195ab8f49 |
Weights for the pre-trained PaperEdge model by Ma et al. ("Learning From Documents in the Wild to Improve Document Unwarping", SIGGRAPH 2022).
Code available at https://github.com/cvlab-stonybrook/PaperEdge. | docdewarper/paperedge_weights | [
"license:mit",
"region:us"
] | 2024-01-03T08:48:08+00:00 | {"license": "mit"} | 2024-01-03T08:52:26+00:00 | [] | [] | TAGS
#license-mit #region-us
|
Weights for the pre-trained PaperEdge model by Ma et al. ("Learning From Documents in the Wild to Improve Document Unwarping", SIGGRAPH 2022).
Code available at URL | [] | [
"TAGS\n#license-mit #region-us \n"
] | [
11
] | [
"passage: TAGS\n#license-mit #region-us \n"
] |
0b35dd10c186d8c41f7ae57018cb880b04385266 | # Dataset Card for "Diffusion-Evodiff_knots"
## Dataset of proteins from Evodiff
Dataset of proteins generated through Evodiff
Contains knotted proteins (tested with omegafold and topoly) and unknotted proteins in ratio 1:4
The dataset is splitted into a train set (majority, 90 %) and evaluation set (only 10 %)
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | EvaKlimentova/Diffusion-Evodiff_knots | [
"region:us"
] | 2024-01-03T08:50:21+00:00 | {"dataset_info": {"features": [{"name": "ID", "dtype": "string"}, {"name": "Sequence", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 3650734.2822767235, "num_examples": 9724}, {"name": "test", "num_bytes": 405845.71772327623, "num_examples": 1081}], "download_size": 3975390, "dataset_size": 4056580.0}} | 2024-01-16T13:27:28+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "Diffusion-Evodiff_knots"
## Dataset of proteins from Evodiff
Dataset of proteins generated through Evodiff
Contains knotted proteins (tested with omegafold and topoly) and unknotted proteins in ratio 1:4
The dataset is splitted into a train set (majority, 90 %) and evaluation set (only 10 %)
More Information needed | [
"# Dataset Card for \"Diffusion-Evodiff_knots\"",
"## Dataset of proteins from Evodiff\n\nDataset of proteins generated through Evodiff\n\nContains knotted proteins (tested with omegafold and topoly) and unknotted proteins in ratio 1:4\n\nThe dataset is splitted into a train set (majority, 90 %) and evaluation set (only 10 %)\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"Diffusion-Evodiff_knots\"",
"## Dataset of proteins from Evodiff\n\nDataset of proteins generated through Evodiff\n\nContains knotted proteins (tested with omegafold and topoly) and unknotted proteins in ratio 1:4\n\nThe dataset is splitted into a train set (majority, 90 %) and evaluation set (only 10 %)\n\nMore Information needed"
] | [
6,
18,
75
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"Diffusion-Evodiff_knots\"## Dataset of proteins from Evodiff\n\nDataset of proteins generated through Evodiff\n\nContains knotted proteins (tested with omegafold and topoly) and unknotted proteins in ratio 1:4\n\nThe dataset is splitted into a train set (majority, 90 %) and evaluation set (only 10 %)\n\nMore Information needed"
] |
1aa62f5f2f0bbf97dda57de735ba7cce0316cde9 |
# Dataset Card for field-custom
This dataset has been created with [Argilla](https://docs.argilla.io).
As shown in the sections below, this dataset can be loaded into Argilla as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
## Dataset Description
- **Homepage:** https://argilla.io
- **Repository:** https://github.com/argilla-io/argilla
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset contains:
* A dataset configuration file conforming to the Argilla dataset format named `argilla.yaml`. This configuration file will be used to configure the dataset when using the `FeedbackDataset.from_huggingface` method in Argilla.
* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `FeedbackDataset.from_huggingface` and can be loaded independently using the `datasets` library via `load_dataset`.
* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
### Load with Argilla
To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
```python
import argilla as rg
ds = rg.FeedbackDataset.from_huggingface("Avimaster/field-custom")
```
### Load with `datasets`
To load this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
```python
from datasets import load_dataset
ds = load_dataset("Avimaster/field-custom")
```
### Supported Tasks and Leaderboards
This dataset can contain [multiple fields, questions and responses](https://docs.argilla.io/en/latest/conceptual_guides/data_model.html#feedback-dataset) so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the [Dataset Structure section](#dataset-structure).
There are no leaderboards associated with this dataset.
### Languages
[More Information Needed]
## Dataset Structure
### Data in Argilla
The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
The **fields** are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
| Field Name | Title | Type | Required | Markdown |
| ---------- | ----- | ---- | -------- | -------- |
| text | Text | text | True | False |
The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| mixed-emotion | Mixed-emotion | multi_label_selection | True | N/A | ['Docket No', 'Ti(first Party)'] |
The **suggestions** are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
The **metadata** is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |
The **guidelines**, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the [annotation guidelines](#annotation-guidelines) section.
### Data Instances
An example of a dataset instance in Argilla looks as follows:
```json
{
"external_id": null,
"fields": {
"text": "COURT OF APPEALS OF INDIANA No. 21A-CR-1374 JESSE BROCKMAN, Appellant-Defendant"
},
"metadata": {},
"responses": [],
"suggestions": [],
"vectors": {}
}
```
While the same record in HuggingFace `datasets` looks as follows:
```json
{
"external_id": null,
"metadata": "{}",
"mixed-emotion": [],
"mixed-emotion-suggestion": null,
"mixed-emotion-suggestion-metadata": {
"agent": null,
"score": null,
"type": null
},
"text": "COURT OF APPEALS OF INDIANA No. 21A-CR-1374 JESSE BROCKMAN, Appellant-Defendant"
}
```
### Data Fields
Among the dataset fields, we differentiate between the following:
* **Fields:** These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
* **text** is of type `text`.
* **Questions:** These are the questions that will be asked to the annotators. They can be of different types, such as `RatingQuestion`, `TextQuestion`, `LabelQuestion`, `MultiLabelQuestion`, and `RankingQuestion`.
* **mixed-emotion** is of type `multi_label_selection` with the following allowed values ['Docket No', 'Ti(first Party)'].
* **Suggestions:** As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
* (optional) **mixed-emotion-suggestion** is of type `multi_label_selection` with the following allowed values ['Docket No', 'Ti(first Party)'].
Additionally, we also have two more fields that are optional and are the following:
* **metadata:** This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the `metadata_properties` defined in the dataset configuration file in `argilla.yaml`.
* **external_id:** This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.
### Data Splits
The dataset contains a single split, which is `train`.
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation guidelines
Text is a dataset of Text fields: Docket No, Ti(first Party)
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed] | Avimaster/field-custom | [
"size_categories:n<1K",
"rlfh",
"argilla",
"human-feedback",
"region:us"
] | 2024-01-03T09:06:52+00:00 | {"size_categories": "n<1K", "tags": ["rlfh", "argilla", "human-feedback"]} | 2024-01-03T09:07:10+00:00 | [] | [] | TAGS
#size_categories-n<1K #rlfh #argilla #human-feedback #region-us
| Dataset Card for field-custom
=============================
This dataset has been created with Argilla.
As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the 'datasets' library in Load with 'datasets'.
Dataset Description
-------------------
* Homepage: URL
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact:
### Dataset Summary
This dataset contains:
* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\_huggingface' method in Argilla.
* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\_huggingface' and can be loaded independently using the 'datasets' library via 'load\_dataset'.
* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.
### Load with Argilla
To load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:
### Load with 'datasets'
To load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:
### Supported Tasks and Leaderboards
This dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.
There are no leaderboards associated with this dataset.
### Languages
Dataset Structure
-----------------
### Data in Argilla
The dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.
The fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
The questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\_selection, multi\_label\_selection, or ranking.
The suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending "-suggestion" and "-suggestion-metadata" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with "-suggestion" and the metadata is appended with "-suggestion-metadata".
The metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\_properties' defined in the dataset configuration file in 'URL'.
The guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.
### Data Instances
An example of a dataset instance in Argilla looks as follows:
While the same record in HuggingFace 'datasets' looks as follows:
### Data Fields
Among the dataset fields, we differentiate between the following:
* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.
+ text is of type 'text'.
* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.
+ mixed-emotion is of type 'multi\_label\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].
* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.
+ (optional) mixed-emotion-suggestion is of type 'multi\_label\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].
Additionally, we also have two more fields that are optional and are the following:
* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\_properties' defined in the dataset configuration file in 'URL'.
* external\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.
### Data Splits
The dataset contains a single split, which is 'train'.
Dataset Creation
----------------
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation guidelines
Text is a dataset of Text fields: Docket No, Ti(first Party)
#### Annotation process
#### Who are the annotators?
### Personal and Sensitive Information
Considerations for Using the Data
---------------------------------
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
Additional Information
----------------------
### Dataset Curators
### Licensing Information
### Contributions
| [
"### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.",
"### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:",
"### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:",
"### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.",
"### Languages\n\n\nDataset Structure\n-----------------",
"### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.",
"### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:",
"### Data Fields\n\n\nAmong the dataset fields, we differentiate between the following:\n\n\n* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\t+ text is of type 'text'.\n* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.\n\n\n\t+ mixed-emotion is of type 'multi\\_label\\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].\n* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.\n\n\n\t+ (optional) mixed-emotion-suggestion is of type 'multi\\_label\\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].\n\n\nAdditionally, we also have two more fields that are optional and are the following:\n\n\n* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n* external\\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.",
"### Data Splits\n\n\nThe dataset contains a single split, which is 'train'.\n\n\nDataset Creation\n----------------",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### Annotation guidelines\n\n\nText is a dataset of Text fields: Docket No, Ti(first Party)",
"#### Annotation process",
"#### Who are the annotators?",
"### Personal and Sensitive Information\n\n\nConsiderations for Using the Data\n---------------------------------",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations\n\n\nAdditional Information\n----------------------",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] | [
"TAGS\n#size_categories-n<1K #rlfh #argilla #human-feedback #region-us \n",
"### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.",
"### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:",
"### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:",
"### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.",
"### Languages\n\n\nDataset Structure\n-----------------",
"### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.",
"### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:",
"### Data Fields\n\n\nAmong the dataset fields, we differentiate between the following:\n\n\n* Fields: These are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\t+ text is of type 'text'.\n* Questions: These are the questions that will be asked to the annotators. They can be of different types, such as 'RatingQuestion', 'TextQuestion', 'LabelQuestion', 'MultiLabelQuestion', and 'RankingQuestion'.\n\n\n\t+ mixed-emotion is of type 'multi\\_label\\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].\n* Suggestions: As of Argilla 1.13.0, the suggestions have been included to provide the annotators with suggestions to ease or assist during the annotation process. Suggestions are linked to the existing questions, are always optional, and contain not just the suggestion itself, but also the metadata linked to it, if applicable.\n\n\n\t+ (optional) mixed-emotion-suggestion is of type 'multi\\_label\\_selection' with the following allowed values ['Docket No', 'Ti(first Party)'].\n\n\nAdditionally, we also have two more fields that are optional and are the following:\n\n\n* metadata: This is an optional field that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n* external\\_id: This is an optional field that can be used to provide an external ID for the dataset record. This can be useful if you want to link the dataset record to an external resource, such as a database or a file.",
"### Data Splits\n\n\nThe dataset contains a single split, which is 'train'.\n\n\nDataset Creation\n----------------",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### Annotation guidelines\n\n\nText is a dataset of Text fields: Docket No, Ti(first Party)",
"#### Annotation process",
"#### Who are the annotators?",
"### Personal and Sensitive Information\n\n\nConsiderations for Using the Data\n---------------------------------",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations\n\n\nAdditional Information\n----------------------",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] | [
27,
162,
40,
53,
68,
11,
404,
40,
502,
27,
7,
4,
10,
10,
5,
25,
5,
9,
18,
7,
8,
14,
6,
6,
5
] | [
"passage: TAGS\n#size_categories-n<1K #rlfh #argilla #human-feedback #region-us \n### Dataset Summary\n\n\nThis dataset contains:\n\n\n* A dataset configuration file conforming to the Argilla dataset format named 'URL'. This configuration file will be used to configure the dataset when using the 'FeedbackDataset.from\\_huggingface' method in Argilla.\n* Dataset records in a format compatible with HuggingFace 'datasets'. These records will be loaded automatically when using 'FeedbackDataset.from\\_huggingface' and can be loaded independently using the 'datasets' library via 'load\\_dataset'.\n* The annotation guidelines that have been used for building and curating the dataset, if they've been defined in Argilla.### Load with Argilla\n\n\nTo load with Argilla, you'll just need to install Argilla as 'pip install argilla --upgrade' and then use the following code:### Load with 'datasets'\n\n\nTo load this dataset with 'datasets', you'll just need to install 'datasets' as 'pip install datasets --upgrade' and then use the following code:### Supported Tasks and Leaderboards\n\n\nThis dataset can contain multiple fields, questions and responses so it can be used for different NLP tasks, depending on the configuration. The dataset structure is described in the Dataset Structure section.\n\n\nThere are no leaderboards associated with this dataset.### Languages\n\n\nDataset Structure\n-----------------",
"passage: ### Data in Argilla\n\n\nThe dataset is created in Argilla with: fields, questions, suggestions, metadata, vectors, and guidelines.\n\n\nThe fields are the dataset records themselves, for the moment just text fields are supported. These are the ones that will be used to provide responses to the questions.\n\n\n\nThe questions are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label\\_selection, multi\\_label\\_selection, or ranking.\n\n\n\nThe suggestions are human or machine generated recommendations for each question to assist the annotator during the annotation process, so those are always linked to the existing questions, and named appending \"-suggestion\" and \"-suggestion-metadata\" to those, containing the value/s of the suggestion and its metadata, respectively. So on, the possible values are the same as in the table above, but the column name is appended with \"-suggestion\" and the metadata is appended with \"-suggestion-metadata\".\n\n\nThe metadata is a dictionary that can be used to provide additional information about the dataset record. This can be useful to provide additional context to the annotators, or to provide additional information about the dataset record itself. For example, you can use this to provide a link to the original source of the dataset record, or to provide additional information about the dataset record itself, such as the author, the date, or the source. The metadata is always optional, and can be potentially linked to the 'metadata\\_properties' defined in the dataset configuration file in 'URL'.\n\n\n\nThe guidelines, are optional as well, and are just a plain string that can be used to provide instructions to the annotators. Find those in the annotation guidelines section.### Data Instances\n\n\nAn example of a dataset instance in Argilla looks as follows:\n\n\nWhile the same record in HuggingFace 'datasets' looks as follows:"
] |
44d3fb4ada8e4a4db7f307da60ea77964f120885 | dataset_info:
features:
- name: repo_name
dtype: string
- name: path
dtype: string
- name: copies
dtype: string
- name: size
dtype: string
- name: content
dtype: string
- name: license
dtype: string
splits:
- name: train
num_bytes: 3147402833.3951
num_examples: 241075
- name: valid
num_bytes: 17472318.29500301
num_examples: 1312
download_size: 966099631
dataset_size: 3164875151.690103
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
license: mit | AlaGrine/codeparrot-sklearn | [
"task_categories:conversational",
"license:mit",
"region:us"
] | 2024-01-03T09:10:56+00:00 | {"license": "mit", "task_categories": ["conversational"], "dataset_info": {"features": [{"name": "repo_name", "dtype": "string"}, {"name": "path", "dtype": "string"}, {"name": "copies", "dtype": "string"}, {"name": "size", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "license", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 3147402833.3951, "num_examples": 241075}, {"name": "valid", "num_bytes": 17472318.29500301, "num_examples": 1312}], "download_size": 966099631, "dataset_size": 3164875151.690103}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "valid", "path": "data/valid-*"}]}]} | 2024-01-03T10:08:44+00:00 | [] | [] | TAGS
#task_categories-conversational #license-mit #region-us
| dataset_info:
features:
- name: repo_name
dtype: string
- name: path
dtype: string
- name: copies
dtype: string
- name: size
dtype: string
- name: content
dtype: string
- name: license
dtype: string
splits:
- name: train
num_bytes: 3147402833.3951
num_examples: 241075
- name: valid
num_bytes: 17472318.29500301
num_examples: 1312
download_size: 966099631
dataset_size: 3164875151.690103
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
license: mit | [] | [
"TAGS\n#task_categories-conversational #license-mit #region-us \n"
] | [
21
] | [
"passage: TAGS\n#task_categories-conversational #license-mit #region-us \n"
] |
d5994608c28dc1fb0d7a4e93410a428529891cc5 |
<p style="font-size:28px;" align="center">
🏠 MoTCode-Data
</p>
<p align="center">
• 🤗 <a href="https://huggingface.co/datasets/JingyaoLi/MoTCode-Data" target="_blank">Data </a> • 🤗 <a href="https://huggingface.co/JingyaoLi/MoTCoder-15B-v1.0" target="_blank">Model </a> • 🐱 <a href="https://github.com/dvlab-research/MoTCoder" target="_blank">Code</a> • 📃 <a href="https://arxiv.org/abs/2312.15960" target="_blank">Paper</a> <br>
</p>
## Dataset Structure
```python
from datasets import load_dataset
load_dataset("JingyaoLi/MoTCode-Data")
DatasetDict({
train: Dataset({
features: ['id', 'source', 'input', 'instruction', 'output'],
num_rows: 26902
})
})
```
### Data Features
|Features|Type|Description|
|---|---|---|
|id|int|problem id|
|instruction|string|problem description|
|input|string|modulars description, including their function headers and docstrings describing their intended usage|
|output|string|python solution|
|source|string|source of the problem: leetcode-m, leetcode-n, apps-m, apps-n, codecontest-m, codecontests-n |
### Data Sources
|Field|Description|
|---|---|
|leetcode-n|Programming problems and solutions downloaded and converted from [Leetcode Website](https://leetcode.com)|
|leetcode-m|Modualr-of-thought Leetcode problems|
|apps-m|Programming problems and solutions from [APPS](https://github.com/hendrycks/apps)|
|apps-n|Modualr-of-thought APPS problems|
|codecontest-m|Programming problems and solutions from [CodeContests](https://github.com/deepmind/code_contests/)|
|codecontest-n|Modualr-of-thought CodeContests problems|
### Modular-of-thought Data Creation
We provide an [example python file](https://github.com/dvlab-research/MoTCoder/blob/master/src/generate_MoT_dataset.py) to evolution a MoT dataset. Run the following command:
```bash
python src/generate_MoT_dataset.py \
--data_path $data_path \
--save_path $MoT_data_path \
--api_base $api_base \
--api_key $api_key
```
For more details, please refer to [our github repository](https://github.com/dvlab-research/MoTCoder).
## Citation
If you find this dataset helpful, kindly cite:
```bibtex
@misc{li2023motcoder,
title={MoTCoder: Elevating Large Language Models with Modular of Thought for Challenging Programming Tasks},
author={Jingyao Li and Pengguang Chen and Jiaya Jia},
year={2023},
eprint={2312.15960},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
``` | JingyaoLi/MoTCode-Data | [
"task_categories:text2text-generation",
"task_categories:text-generation",
"task_categories:question-answering",
"task_categories:conversational",
"task_categories:translation",
"task_ids:language-modeling",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:code",
"license:mit",
"python",
"code-generation",
"large-language-models",
"arxiv:2312.15960",
"region:us"
] | 2024-01-03T09:12:16+00:00 | {"language": ["code"], "license": "mit", "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "task_categories": ["text2text-generation", "text-generation", "question-answering", "conversational", "translation"], "task_ids": ["language-modeling"], "pretty_name": "MoTCode", "tags": ["python", "code-generation", "large-language-models"]} | 2024-01-03T10:56:21+00:00 | [
"2312.15960"
] | [
"code"
] | TAGS
#task_categories-text2text-generation #task_categories-text-generation #task_categories-question-answering #task_categories-conversational #task_categories-translation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #language-code #license-mit #python #code-generation #large-language-models #arxiv-2312.15960 #region-us
|
MoTCode-Data
• [Data](URL target=) • [Model](URL target=) • [Code](URL target=) • [Paper](URL target=)
Dataset Structure
-----------------
### Data Features
Features: id, Type: int, Description: problem id
Features: instruction, Type: string, Description: problem description
Features: input, Type: string, Description: modulars description, including their function headers and docstrings describing their intended usage
Features: output, Type: string, Description: python solution
Features: source, Type: string, Description: source of the problem: leetcode-m, leetcode-n, apps-m, apps-n, codecontest-m, codecontests-n
### Data Sources
### Modular-of-thought Data Creation
We provide an example python file to evolution a MoT dataset. Run the following command:
For more details, please refer to our github repository.
If you find this dataset helpful, kindly cite:
| [
"### Data Features\n\n\nFeatures: id, Type: int, Description: problem id\nFeatures: instruction, Type: string, Description: problem description\nFeatures: input, Type: string, Description: modulars description, including their function headers and docstrings describing their intended usage\nFeatures: output, Type: string, Description: python solution\nFeatures: source, Type: string, Description: source of the problem: leetcode-m, leetcode-n, apps-m, apps-n, codecontest-m, codecontests-n",
"### Data Sources",
"### Modular-of-thought Data Creation\n\n\nWe provide an example python file to evolution a MoT dataset. Run the following command:\n\n\nFor more details, please refer to our github repository.\n\n\nIf you find this dataset helpful, kindly cite:"
] | [
"TAGS\n#task_categories-text2text-generation #task_categories-text-generation #task_categories-question-answering #task_categories-conversational #task_categories-translation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #language-code #license-mit #python #code-generation #large-language-models #arxiv-2312.15960 #region-us \n",
"### Data Features\n\n\nFeatures: id, Type: int, Description: problem id\nFeatures: instruction, Type: string, Description: problem description\nFeatures: input, Type: string, Description: modulars description, including their function headers and docstrings describing their intended usage\nFeatures: output, Type: string, Description: python solution\nFeatures: source, Type: string, Description: source of the problem: leetcode-m, leetcode-n, apps-m, apps-n, codecontest-m, codecontests-n",
"### Data Sources",
"### Modular-of-thought Data Creation\n\n\nWe provide an example python file to evolution a MoT dataset. Run the following command:\n\n\nFor more details, please refer to our github repository.\n\n\nIf you find this dataset helpful, kindly cite:"
] | [
125,
124,
5,
59
] | [
"passage: TAGS\n#task_categories-text2text-generation #task_categories-text-generation #task_categories-question-answering #task_categories-conversational #task_categories-translation #task_ids-language-modeling #multilinguality-monolingual #size_categories-10K<n<100K #language-code #license-mit #python #code-generation #large-language-models #arxiv-2312.15960 #region-us \n### Data Features\n\n\nFeatures: id, Type: int, Description: problem id\nFeatures: instruction, Type: string, Description: problem description\nFeatures: input, Type: string, Description: modulars description, including their function headers and docstrings describing their intended usage\nFeatures: output, Type: string, Description: python solution\nFeatures: source, Type: string, Description: source of the problem: leetcode-m, leetcode-n, apps-m, apps-n, codecontest-m, codecontests-n### Data Sources### Modular-of-thought Data Creation\n\n\nWe provide an example python file to evolution a MoT dataset. Run the following command:\n\n\nFor more details, please refer to our github repository.\n\n\nIf you find this dataset helpful, kindly cite:"
] |
696ab60668871e5d709ef5b53cdbf7dd558229ac | 把yazhou80/books-all-pkl 的数据全部转化成向量了， embedding model is openai ada2 | yazhou80/books-all-pkl-vector | [
"region:us"
] | 2024-01-03T09:13:53+00:00 | {} | 2024-01-03T14:26:28+00:00 | [] | [] | TAGS
#region-us
| 把yazhou80/books-all-pkl 的数据全部转化成向量了， embedding model is openai ada2 | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
1255ba9a19f26a8edb48d4df7173d1d51a586016 | Orignal dataset is https://huggingface.co/datasets/clarin-pl/poquad
As orignal dataset is mainly for SQuADv1 type of models, this copy also unlocks access to SQuADv2 type of features in poquad like empty questions. | mzasada/poquad_v2 | [
"task_categories:question-answering",
"size_categories:10K<n<100K",
"language:pl",
"license:apache-2.0",
"region:us"
] | 2024-01-03T09:19:13+00:00 | {"language": ["pl"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["question-answering"], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "is_impossible", "dtype": "string"}, {"name": "answers", "sequence": [{"name": "text", "dtype": "string"}, {"name": "answer_start", "dtype": "int32"}, {"name": "generative_answer", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 66007405, "num_examples": 56618}, {"name": "validation", "num_bytes": 8303914, "num_examples": 7060}], "download_size": 16398725, "dataset_size": 74311319}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-10T15:04:59+00:00 | [] | [
"pl"
] | TAGS
#task_categories-question-answering #size_categories-10K<n<100K #language-Polish #license-apache-2.0 #region-us
| Orignal dataset is URL
As orignal dataset is mainly for SQuADv1 type of models, this copy also unlocks access to SQuADv2 type of features in poquad like empty questions. | [] | [
"TAGS\n#task_categories-question-answering #size_categories-10K<n<100K #language-Polish #license-apache-2.0 #region-us \n"
] | [
43
] | [
"passage: TAGS\n#task_categories-question-answering #size_categories-10K<n<100K #language-Polish #license-apache-2.0 #region-us \n"
] |
0e36fc717b7ab3ed314be19a252b5dd5732ec556 | <h2><strong><a href="https://myhealthfitnessmart.blogspot.com/2024/01/guardian-botanicals-blood-balance.html">Guardian Botanicals Blood Balance</a> Review </strong></h2>
<p><a href="https://carehealthreview.blogspot.com/2024/01/guardian-botanicals-blood-balance.html"><strong>Guardian Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level. This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This <a href="https://myhealthfitnessmart.blogspot.com/2024/01/guardian-botanicals-blood-balance.html"><strong>Guardian Botanicals Blood Balance</strong></a> review focuses on a product that will help you maintain a healthy blood flow. There are many blood-balancing products on the market, making it difficult to choose which one is best for you. Do you feel it is the best one you have tried?</p>
<h2><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>Guardian Botanicals Blood Balance — Official Website Link — Click Here</strong></a></h2>
<h2><strong>►❱❱ Product Name ➥ {</strong><strong><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Guardian Botanicals Blood Balance</a>}</strong><br /><strong>►❱❱ Countries Available ➥ World Wide</strong><br /><strong>►❱❱ Composition ➥ Natural Organic Compound</strong><br /><strong>►❱❱ Side-Effects ➥ NA</strong><br /><strong>►❱❱ Rating ➥ ⭐⭐⭐⭐⭐</strong><br /><strong>►❱❱ Availability ➥ <a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Online</a></strong><br /><strong>➤➤❱❱ Where to Buy ➺ <a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Official Website</a><br /></strong></h2>
<h2><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a><br /><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a><br /><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a></h2>
<p>Consider the health risks you'll be taking if you use expensive products or take supplements that are potentially dangerous. With this in mind, I decided to share The Guardian Botanicals' Blood Balance, which I discovered through extensive research. It's important that I share it with you, so you can see how valuable the supplement is.To find out if this <a href="https://guardian-botanicals-australia.clubeo.com/"><strong>Guardian Botanicals Blood Balance</strong></a> pill is right for you, read the <a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html"><strong>Guardian Botanicals Blood Balance</strong></a> review. Then make the right decision.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRgtOhomp2khVg7WUdD559TA_AxoZnujX97_4ftissoDXXPzLxwtTEbBWxWdY8SWclSuq6BpBOkfor-tcvi1qp8SNVytJPRRbUsqSULmxXIs5zH3B39pKleVfz5xrl2bk00MnYOqSoLScqzW71OTv4xgN0rm33nAQ61xlBLXhOmh-Rf8xZKWouj05_apS-/w640-h410/Guardian%20Botanicals%20Blood%20Balance7.jpg" alt="" width="640" height="410" border="0" data-original-height="454" data-original-width="709" /></a></div>
<h2><strong>What is <a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html">Guardian Botanicals Blood Balance</a>?</strong></h2>
<p><a href="https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement"><strong>Guardian Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level . This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This formula is 100% made from authentic herbs and plant extracts. It works well for all ages. Guardian Blood Balance was meticulously filtered to remove any toxic metals and other substances. The facility where the supplement was made received FDA approval and GMP certification. This supplement is non-GMO, so you don't need to worry about preservatives, stimulants, or gluten.The company has not compromised on the quality of its products, and that is why it has been able to earn a reputation.</p>
<p style="text-align: justify;">Guardian Blood Balance Mexico is happily made in the United States, following strict GMP rules and guidelines to make sure it is pure and works.This Guardian Blood Balance product is safe for all people because it is carefully made with some of the cleanest and rarest plant and herbal extracts, which help the body clean its blood naturally.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>(EXCLUSIVE OFFER)Click Here : "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>How does <a href="https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/">Guardian Botanicals Blood Balance</a> work?</strong></h2>
<p><a href="https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc"><strong>Guardian Botanicals Blood Balance</strong></a> supplement activates a triple-action formula upon being taken. This supplement helps to maintain healthy blood sugar and blood pressure levels. It also solves obesity and weight gain issues. The formula is made up of ingredients that are strong and free from toxic substances. <a href="https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia"><strong>Guardian Botanicals Blood Balance</strong></a> is a scientifically-proven solution that has provided positive results for users.</p>
<p>Other ingredients will help keep your body clear by removing stubborn and unwanted fats that could be harmful. To keep your body healthy and to give you a youthful feeling, the formula will transform you from within.</p>
<p style="text-align: justify;">This advanced blood balance supplement improves your health in three ways. Your doctor will be perplexed as to why your blood test results changed so dramatically just a few months of consistent dosage! Strengthen your immune system so it can stave off a lifetime of blood-related illnesses.</p>
<p style="text-align: justify;">Enhance your well-being with this supplement that has been clinically confirmed to work. Maintain healthy cardiovascular and arterial function, enhance pancreatic function, and forestall the development of chronic illnesses and conditions associated with blood.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj76ZwAWQRVNWHn5ttf4NnrG1H2i90Xfor1Lrj9e3k2c6TFLWgy4j0Huz1z9A4qvHXV9pIN9RmPU2PJSnQnH6zGlimdH4xhkUhBvorJjtra3UrgWoNls7-HNEjdiRnLQP9IJpGBFHbBUMDIWDraqJ0ObT-9pX9o01bpKcUs-drBQT99p0X_9imk0LYxTCQK/w640-h360/Untitled%20(4)%20(1).png" alt="" width="640" height="360" border="0" data-original-height="1080" data-original-width="1920" /></a></div>
<h2><strong>Ingredients of <a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">Guardian Botanicals Blood Balance</a> Supplement</strong></h2>
<p><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/"><strong>Guardian Blood Balance</strong></a> is an exclusive combination of ingredients developed to enhance the outcomes of blood tests. Doctors check for cholesterol, glucose, and blood pressure when they draw blood to evaluate your health. You are in danger if your reading is high in any of these three areas.</p>
<p><strong>#White Mulberry Leaf</strong></p>
<p>There are substances in white mulberry leaf that work in a way that is comparable to types 2 diabetic treatments.These substances help control blood sugar levels by easing the digestive process and smoothing the absorption of sugar into the circulation.The use of White Mulberry Leaf also aids in keeping blood pressure and cholesterol in healthy ranges.</p>
<p><strong>#Juniper Berry</strong></p>
<p>Juniper berry has been used in traditional medicine for a long time, and it now provides many new health advantages. The minerals and powerful substances with antioxidant and anti-inflammatory capabilities are concentrated in its extract.</p>
<p><strong>#Biotin + Chromium</strong></p>
<p>Biotin, or vitamin B-7, helps keep metabolism healthy and may be useful while trying to control one's weight. It helps the body use the nutrients in meals for energy and distributes them more efficiently, just like the other B vitamins.</p>
<p><strong>#Berberine Extract</strong></p>
<p>Herbs and plants such as tree turmeric, goldenseal, and Oregon grape contain berberine extract as a natural ingredient.The effects of berberine on blood sugar, cholesterol, and triglyceride levels have been studied.In the right doses, this alkaloid improves insulin action and has other positive effects on health.</p>
<p><strong>#Bitter Melon</strong></p>
<p>Potent antioxidants and anti-inflammatory substances are found in bitter melons. Its qualities are thought to promote healthy blood parameters by lowering bad cholesterol and increasing good cholesterol and lowering blood sugar levels.</p>
<p><strong>#Cinnamon Bark Powder</strong></p>
<p>The use of cinnamon bark powder can help with insulin resistance and level management.In addition to easing gas and spasms, it helps with gastrointestinal problems. In addition to its insulin-like characteristics, which help lower blood glucose levels, it is believed to improve blood circulation.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>What are the benefits of using <a href="https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD">Guardian Botanicals Blood Balance</a>?</strong></h2>
<p><a href="https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx"><strong>Guardian Botanicals Blood Balance</strong></a> can help people improve their health and well-being by focusing on weight loss and reducing their blood sugar levels. We recommend Guardian Blood Balance for the following main reasons:</p>
<p><strong>Reducing Blood Pressure:</strong> This all-natural <a href="https://sites.google.com/view/guardian-bloodbalance-price-au/home"><strong>Guardian Botanicals Blood Balance</strong></a> can assist with blood pressure control. Scientific studies have shown the efficacy of the product, which is formulated with all-natural ingredients.</p>
<p><strong>Controlling Blood Sugar Levels:</strong> Controlling blood sugar levels is one of the primary uses for Guardian Botanicals' Blood Balance. This recipe can lessen the likelihood of developing Type 2 Diabetes and its complications by regulating blood sugar levels.</p>
<p><strong>Reduces Bad Cholesterol:</strong> Guardian Blood Balance's all-natural ingredients work to lower bad cholesterol levels.</p>
<p><strong>Increase Good Cholesterol:</strong> Guardian Blood Balance is a dietary supplement that aids in the elimination of harmful cholesterol while enhancing good cholesterol levels.</p>
<p><strong>Facilitates Weight Loss:</strong> An important part of maintaining weight reduction is controlling blood sugar. Losing weight, increasing energy, and decreasing cravings are all possible with the correct carbohydrate to fat ratio.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5Dt6FS6aGzbkAR0B4iWZijfOMnHYUA2gTDiPKlUDCzJ6_rSoAx6K7N5e45zXdFIYs_hFwLYvtrycB84GwIQ21xwrhXC64KAOQdzEYGC1Ji22A7BHUo3U1D4_TwQM3kQlfizJ9o99E2k-0r4YwYH1ajYf50bvcUtmI9LMwxsOZXj7AFne7wkNoaK__uB1-/w640-h350/Guardian%20Botanicals%20Blood%20Balance.jpg" alt="" width="640" height="350" border="0" data-original-height="276" data-original-width="506" /></a></div>
<h2><strong>Side Effects of using <a href="https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo">Guardian Botanicals Blood Balance</a><br /></strong></h2>
<p>Guardian Botanicals' Blood Balance Supplement is a pure solution made with the best ingredients. Side effects were rare for those who took the recommended dose. The product was made in an FDA-approved, GMP-certified manufacturing facility.</p>
<p>Each bottle of Blood Balance Supplement is free from any preservatives or herbicides, stimulants or other chemicals that could harm your health. It may take some time but the results you will get are real. <a href="https://guardian-blood-balance-price.company.site/"><strong>Guardian Botanicals Blood Balance</strong></a> reviews have shown that the ingredients are completely natural and safe. Botanicals Blood Balance side effects are therefore minimal.</p>
<p>If you have any allergies or are taking medication, consult your doctor to ensure that you remain safe. The supplement is only for adults. Children should be avoided.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO: Get Guardian Botanicals Blood Balance at the Lowest Discounted Price Online</strong></a></span></h2>
<h2><strong><a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">Guardian Botanicals Blood Balance</a> Price & Where to Buy?</strong></h2>
<ul>
<li><strong>Buy one <a href="https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to">Guardian Botanicals Blood Balance</a> Supplement bottle for just $69.95</strong></li>
<li><strong>Buy two bottles of the <a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">Guardian Botanicals Blood Balance</a> Supplement and get a third bottle free, at $49.95 each.</strong></li>
<li><strong>Buy three bottles of the <a href="https://carehealthreview.blogspot.com/2024/01/guardian-botanicals-blood-balance.html">Guardian Botanicals Blood Balance</a> Supplement and get two more bottles free, at just $39.95 each.</strong></li>
</ul>
<p>These bottles contain inferior quality ingredients, which can be dangerous and could cause serious health problems. Only through the official website can you receive a 100% money-back guarantee. Click on the link below to order guardian botanicals blood balance supplement directly to the official site.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhz9fdGrhIcJdiH28VNctZWP3AyEXQ5PTIXTuvZcEsCUoNov6Eud-dNlmTAqeUmx-kVIzKPzRyLMaEKDSNss0T5nfOgsRGt_sHQEc7wYirF-0WyL6p0wAz-FPWxGpGTtiPXKYkmnBqSXxxGEOIYUAMjGlJSs2RITnUGoalzOvka50ZQGyP-XW4DqoIVXWN7/w640-h422/review.jpg" alt="" width="640" height="422" border="0" data-original-height="422" data-original-width="639" /></a></div>
<h2><strong>Frequently Asked Question</strong></h2>
<p><strong>What does the Blood Balance Supplement do?</strong></p>
<p>The Blood Balance formula contains 100% natural ingredients which help to lower blood sugar, blood pressure, and bad cholesterol in a quick and effective manner.</p>
<p><strong>Is it safe to use?</strong></p>
<p>Blood Balance Supplement contains only natural, effective ingredients. This supplement was made in an FDA-approved, GMP-certified manufacturing facility. It is safe to use because it contains no harmful ingredients.</p>
<p><strong>How do I use Guardian Botanicals' blood balance?</strong></p>
<p>For easy swallowing, take 1 capsule of the Blood Balance supplement each day with a glass of water.</p>
<p><strong>Does this affect my medication?</strong></p>
<p>It is not necessary, but it is better to see a doctor.</p>
<p><strong>What happens if this doesn’t work?</strong></p>
<p>For 30 days, you get a 100% money-back guarantee. It is therefore risk-free.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>Final Verdict on <a href="https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!">Guardian Botanicals Blood Balance</a> Reviews</strong></h2>
<p><a href="https://bookshop.org/wishlists/45abc33870a15200c43c071c8dac8e95dd5d62b1"><strong>Guardian Botanicals Blood Balance</strong></a> was a supplement that gained a reputation for its positive results. This formula contains only organic and safe ingredients, which work well to balance blood sugar and blood pressure.</p>
<p>The Blood Balance Supplement users who used it for 2 to 3 months saw a greater health condition.<a href="https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-65952b4e0fd36eec92f34440"><strong> Guardian Botanicals Blood Balance</strong> </a>users have written reviews to share their experiences.</p>
<p>Some users claim they have lost excess fat and control their blood sugar and blood pressure. The recommended method of taking the Blood Balance capsules will allow you to see positive changes in your life.You get a 30-day guarantee of 100% satisfaction. If you are dissatisfied and cannot notice any changes, you can contact the customer service team to request a refund.If you are unsure, stop being sceptical and give the guardian the chance to prove you right.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQPVZoVTH8inZstDFwqqog2PLHocczy70z8FMORegRT3XSanNA93WSGdgeSsmXpcyHGtQTJcbSuMmfqtOwDy0P3GD9WGxdyMyPTkTWz68E_NOOmHrL5CPrSVIDY4pnAh-3_QFxBYB_m59Mr423hrJnzO5hIK_t68qno7-uMrBO0Y8DwMGjRko6HzkrIRfK/w542-h640/price.jpg" alt="" width="542" height="640" border="0" data-original-height="466" data-original-width="395" /></a></div>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>Exclusive Details: *Guardian Botanicals Blood Balance* Read More Details on Official Website Australia!</strong></a></span></h2>
<h2># READ MORE INFO-</h2>
<p><span style="color: #ff0000;"><a href="https://guardian-blood-balance-price.company.site/">https://guardian-blood-balance-price.company.site/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo">https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/">https://guardian-botanicals-blood-balance-11.jimdosite.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD">https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD</a></span></p>
<p><span style="color: #ff0000;"><a href="https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx">https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx</a></span></p>
<p><span style="color: #ff0000;"><a href="https://sites.google.com/view/guardian-bloodbalance-price-au/home">https://sites.google.com/view/guardian-bloodbalance-price-au/home</a></span></p>
<p><span style="color: #ff0000;"><a href="https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc">https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc</a></span></p>
<p><span style="color: #ff0000;"><a href="https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/">https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/">https://guardian-botanicals-blood-balance-11.jimdosite.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/">https://guardian-botanicals-australia.clubeo.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html">https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html">https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement">https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement</a></span></p>
<p><span style="color: #ff0000;"><a href="https://medium.com/@bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024-de1c8def2eef">https://medium.com/@bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024-de1c8def2eef</a></span></p>
<p><span style="color: #ff0000;"><a href="https://followme.tribe.so/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-659528554eef0bd4a84798e3">https://followme.tribe.so/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-659528554eef0bd4a84798e3</a></span></p>
<p><span style="color: #ff0000;"><a href="https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to">https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to</a></span></p>
<p><span style="color: #ff0000;"><a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024</a></span></p>
<p><span style="color: #ff0000;"><a href="https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!">https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!</a></span></p>
<p><span style="color: #ff0000;"><a href="https://wandering.flarum.cloud/d/35508-guardian-botanicals-blood-balance-reviews">https://wandering.flarum.cloud/d/35508-guardian-botanicals-blood-balance-reviews</a></span></p>
<p><span style="color: #ff0000;"><a href="https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-revie--65952c47151fd46d84209078">https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-revie--65952c47151fd46d84209078</a></span></p>
<p> </p> | bloodsugaraustralia/guardian-blood-balance-review | [
"region:us"
] | 2024-01-03T10:02:08+00:00 | {} | 2024-01-03T10:02:32+00:00 | [] | [] | TAGS
#region-us
| <h2><strong><a href="URL Botanicals Blood Balance</a> Review </strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level. This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This <a href="URL Botanicals Blood Balance</strong></a> review focuses on a product that will help you maintain a healthy blood flow. There are many blood-balancing products on the market, making it difficult to choose which one is best for you. Do you feel it is the best one you have tried?</p>
<h2><a href="URL Botanicals Blood Balance — Official Website Link — Click Here</strong></a></h2>
<h2><strong>► Product Name {</strong><strong><a href="URL Botanicals Blood Balance</a>}</strong><br /><strong>► Countries Available World Wide</strong><br /><strong>► Composition Natural Organic Compound</strong><br /><strong>► Side-Effects NA</strong><br /><strong>► Rating ⭐⭐⭐⭐⭐</strong><br /><strong>► Availability <a href="URL /><strong> Where to Buy <a href="URL Website</a><br /></strong></h2>
<h2><a href="URL The Official Website To Get Your Bottle Now”</strong></a><br /><a href="URL The Official Website To Get Your Bottle Now”</strong></a><br /><a href="URL The Official Website To Get Your Bottle Now”</strong></a></h2>
<p>Consider the health risks you'll be taking if you use expensive products or take supplements that are potentially dangerous. With this in mind, I decided to share The Guardian Botanicals' Blood Balance, which I discovered through extensive research. It's important that I share it with you, so you can see how valuable the supplement is.To find out if this <a href="URL Botanicals Blood Balance</strong></a> pill is right for you, read the <a href="URL Botanicals Blood Balance</strong></a> review. Then make the right decision.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="410" border="0" data-original-height="454" data-original-width="709" /></a></div>
<h2><strong>What is <a href="URL Botanicals Blood Balance</a>?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level . This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This formula is 100% made from authentic herbs and plant extracts. It works well for all ages. Guardian Blood Balance was meticulously filtered to remove any toxic metals and other substances. The facility where the supplement was made received FDA approval and GMP certification. This supplement is non-GMO, so you don't need to worry about preservatives, stimulants, or gluten.The company has not compromised on the quality of its products, and that is why it has been able to earn a reputation.</p>
<p style="text-align: justify;">Guardian Blood Balance Mexico is happily made in the United States, following strict GMP rules and guidelines to make sure it is pure and works.This Guardian Blood Balance product is safe for all people because it is carefully made with some of the cleanest and rarest plant and herbal extracts, which help the body clean its blood naturally.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL OFFER)Click Here : "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>How does <a href="URL Botanicals Blood Balance</a> work?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> supplement activates a triple-action formula upon being taken. This supplement helps to maintain healthy blood sugar and blood pressure levels. It also solves obesity and weight gain issues. The formula is made up of ingredients that are strong and free from toxic substances. <a href="URL Botanicals Blood Balance</strong></a> is a scientifically-proven solution that has provided positive results for users.</p>
<p>Other ingredients will help keep your body clear by removing stubborn and unwanted fats that could be harmful. To keep your body healthy and to give you a youthful feeling, the formula will transform you from within.</p>
<p style="text-align: justify;">This advanced blood balance supplement improves your health in three ways. Your doctor will be perplexed as to why your blood test results changed so dramatically just a few months of consistent dosage! Strengthen your immune system so it can stave off a lifetime of blood-related illnesses.</p>
<p style="text-align: justify;">Enhance your well-being with this supplement that has been clinically confirmed to work. Maintain healthy cardiovascular and arterial function, enhance pancreatic function, and forestall the development of chronic illnesses and conditions associated with blood.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="360" border="0" data-original-height="1080" data-original-width="1920" /></a></div>
<h2><strong>Ingredients of <a href="URL Botanicals Blood Balance</a> Supplement</strong></h2>
<p><a href="URL Blood Balance</strong></a> is an exclusive combination of ingredients developed to enhance the outcomes of blood tests. Doctors check for cholesterol, glucose, and blood pressure when they draw blood to evaluate your health. You are in danger if your reading is high in any of these three areas.</p>
<p><strong>#White Mulberry Leaf</strong></p>
<p>There are substances in white mulberry leaf that work in a way that is comparable to types 2 diabetic treatments.These substances help control blood sugar levels by easing the digestive process and smoothing the absorption of sugar into the circulation.The use of White Mulberry Leaf also aids in keeping blood pressure and cholesterol in healthy ranges.</p>
<p><strong>#Juniper Berry</strong></p>
<p>Juniper berry has been used in traditional medicine for a long time, and it now provides many new health advantages. The minerals and powerful substances with antioxidant and anti-inflammatory capabilities are concentrated in its extract.</p>
<p><strong>#Biotin + Chromium</strong></p>
<p>Biotin, or vitamin B-7, helps keep metabolism healthy and may be useful while trying to control one's weight. It helps the body use the nutrients in meals for energy and distributes them more efficiently, just like the other B vitamins.</p>
<p><strong>#Berberine Extract</strong></p>
<p>Herbs and plants such as tree turmeric, goldenseal, and Oregon grape contain berberine extract as a natural ingredient.The effects of berberine on blood sugar, cholesterol, and triglyceride levels have been studied.In the right doses, this alkaloid improves insulin action and has other positive effects on health.</p>
<p><strong>#Bitter Melon</strong></p>
<p>Potent antioxidants and anti-inflammatory substances are found in bitter melons. Its qualities are thought to promote healthy blood parameters by lowering bad cholesterol and increasing good cholesterol and lowering blood sugar levels.</p>
<p><strong>#Cinnamon Bark Powder</strong></p>
<p>The use of cinnamon bark powder can help with insulin resistance and level management.In addition to easing gas and spasms, it helps with gastrointestinal problems. In addition to its insulin-like characteristics, which help lower blood glucose levels, it is believed to improve blood circulation.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>What are the benefits of using <a href="URL Botanicals Blood Balance</a>?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> can help people improve their health and well-being by focusing on weight loss and reducing their blood sugar levels. We recommend Guardian Blood Balance for the following main reasons:</p>
<p><strong>Reducing Blood Pressure:</strong> This all-natural <a href="URL Botanicals Blood Balance</strong></a> can assist with blood pressure control. Scientific studies have shown the efficacy of the product, which is formulated with all-natural ingredients.</p>
<p><strong>Controlling Blood Sugar Levels:</strong> Controlling blood sugar levels is one of the primary uses for Guardian Botanicals' Blood Balance. This recipe can lessen the likelihood of developing Type 2 Diabetes and its complications by regulating blood sugar levels.</p>
<p><strong>Reduces Bad Cholesterol:</strong> Guardian Blood Balance's all-natural ingredients work to lower bad cholesterol levels.</p>
<p><strong>Increase Good Cholesterol:</strong> Guardian Blood Balance is a dietary supplement that aids in the elimination of harmful cholesterol while enhancing good cholesterol levels.</p>
<p><strong>Facilitates Weight Loss:</strong> An important part of maintaining weight reduction is controlling blood sugar. Losing weight, increasing energy, and decreasing cravings are all possible with the correct carbohydrate to fat ratio.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="350" border="0" data-original-height="276" data-original-width="506" /></a></div>
<h2><strong>Side Effects of using <a href="URL Botanicals Blood Balance</a><br /></strong></h2>
<p>Guardian Botanicals' Blood Balance Supplement is a pure solution made with the best ingredients. Side effects were rare for those who took the recommended dose. The product was made in an FDA-approved, GMP-certified manufacturing facility.</p>
<p>Each bottle of Blood Balance Supplement is free from any preservatives or herbicides, stimulants or other chemicals that could harm your health. It may take some time but the results you will get are real. <a href="URL Botanicals Blood Balance</strong></a> reviews have shown that the ingredients are completely natural and safe. Botanicals Blood Balance side effects are therefore minimal.</p>
<p>If you have any allergies or are taking medication, consult your doctor to ensure that you remain safe. The supplement is only for adults. Children should be avoided.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO: Get Guardian Botanicals Blood Balance at the Lowest Discounted Price Online</strong></a></span></h2>
<h2><strong><a href="URL Botanicals Blood Balance</a> Price & Where to Buy?</strong></h2>
<ul>
<li><strong>Buy one <a href="URL Botanicals Blood Balance</a> Supplement bottle for just $69.95</strong></li>
<li><strong>Buy two bottles of the <a href="URL Botanicals Blood Balance</a> Supplement and get a third bottle free, at $49.95 each.</strong></li>
<li><strong>Buy three bottles of the <a href="URL Botanicals Blood Balance</a> Supplement and get two more bottles free, at just $39.95 each.</strong></li>
</ul>
<p>These bottles contain inferior quality ingredients, which can be dangerous and could cause serious health problems. Only through the official website can you receive a 100% money-back guarantee. Click on the link below to order guardian botanicals blood balance supplement directly to the official site.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="422" border="0" data-original-height="422" data-original-width="639" /></a></div>
<h2><strong>Frequently Asked Question</strong></h2>
<p><strong>What does the Blood Balance Supplement do?</strong></p>
<p>The Blood Balance formula contains 100% natural ingredients which help to lower blood sugar, blood pressure, and bad cholesterol in a quick and effective manner.</p>
<p><strong>Is it safe to use?</strong></p>
<p>Blood Balance Supplement contains only natural, effective ingredients. This supplement was made in an FDA-approved, GMP-certified manufacturing facility. It is safe to use because it contains no harmful ingredients.</p>
<p><strong>How do I use Guardian Botanicals' blood balance?</strong></p>
<p>For easy swallowing, take 1 capsule of the Blood Balance supplement each day with a glass of water.</p>
<p><strong>Does this affect my medication?</strong></p>
<p>It is not necessary, but it is better to see a doctor.</p>
<p><strong>What happens if this doesn’t work?</strong></p>
<p>For 30 days, you get a 100% money-back guarantee. It is therefore risk-free.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>Final Verdict on <a href="URL Botanicals Blood Balance</a> Reviews</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> was a supplement that gained a reputation for its positive results. This formula contains only organic and safe ingredients, which work well to balance blood sugar and blood pressure.</p>
<p>The Blood Balance Supplement users who used it for 2 to 3 months saw a greater health condition.<a href="URL Guardian Botanicals Blood Balance</strong> </a>users have written reviews to share their experiences.</p>
<p>Some users claim they have lost excess fat and control their blood sugar and blood pressure. The recommended method of taking the Blood Balance capsules will allow you to see positive changes in your life.You get a 30-day guarantee of 100% satisfaction. If you are dissatisfied and cannot notice any changes, you can contact the customer service team to request a refund.If you are unsure, stop being sceptical and give the guardian the chance to prove you right.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="542" height="640" border="0" data-original-height="466" data-original-width="395" /></a></div>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL Details: *Guardian Botanicals Blood Balance* Read More Details on Official Website Australia!</strong></a></span></h2>
<h2># READ MORE INFO-</h2>
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p> </p> | [
"# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] | [
"TAGS\n#region-us \n",
"# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] | [
6,
501
] | [
"passage: TAGS\n#region-us \n# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] |
ae398f55606a0a599fb71e2a04593036881b0f33 | # This is a demonstration dataset created using [Augmentoolkit](https://github.com/e-p-armstrong/augmentoolkit) and some [Project Gutenberg]() books.
# Augmentoolkit lets you use local models running on your own machine to create datasets based on any text you can conceive of.
# This dataset is just an example of how you can use it. If you finetune models (or want to) feel free to explore it for yourself!
**(Even if you don't finetune models, you could still create and open source a standalone dataset like this one!)**
# For some reason HuggingFace's dataset viewer is insistent on using the images as the dataset, not the actual .jsonl file. Not sure what I can do about that.
This dataset is a mix of nearly optimal (Simple Sabotage, On War, Principles of Chemistry) and highly suboptimal (Logic and Critical Thinking) books and manuals, built to see how [Augmentoolkit](https://github.com/e-p-armstrong/augmentoolkit) handles a variety of texts. More details about the project can be found in the README of [Augmentoolkit](https://github.com/e-p-armstrong/augmentoolkit). Augmentoolkit is built to make data a strength of finetuning, rather than a barrier-to-entry and a perpetual headache. If you make your own models I [encourage you to give it a shot](https://github.com/e-p-armstrong/augmentoolkit).
This demo dataset can be used to fine-tune models, and I encourage you to try doing so. Ideally the resulting model would know the information contained in the dataset after a good finetune. **To make it more likely that the model learns the information in these examples, not just their style, it might be best to use a high LoRA rank!**
Further, note that this dataset is more of an experiment and a test than the primary contribution of my last three months: that honor goes to [Augmentoolkit](https://github.com/e-p-armstrong/augmentoolkit).
Here's a brief, comedic flowchart illustrating why I made Augmentoolkit:
Easily make your own datasets with tens of thousands of training examples, based on any source text you want, using your own computer, all from an easy-to-use Jupyter Notebook, via the [Augmentoolkit](https://github.com/e-p-armstrong/augmentoolkit) repo. Contributions welcome!
**Full text list and reasons for inclusion:**
- Principles of Chemistry by Demitry Mendeleev — because I wanted some knowledge from a science that everyone knows a bit about, and this was available on Gutenberg. Also the intro to this book is surprisingly philosophical and might give a model some neat ideas about knowledge and keeping up with a rapidly-growing field, so it's relevant to us. Naturally some of the information in this book is going to be very out of date — Mendeleev didn't even know what a proton was. But that itself makes for an interesting test — can models learn outdated/wrong information using data generated from the Augmentoolkit, and does that learning overwrite up-to-date information? NOTE: Not all of this book was used, to save time. It's very, very long. Also, the questions based on markdown tables that somehow passed the filter are probably BS.
- On Liberty by John Stuart Mill — I wanted to see how it would handle a fully philosophical and opinionated text. The answer seems to be "pretty well", which means that those few-shot examples from Plato's The Republic and Nietzsche's Thus Spake Zarathustra paid off.
- On War by Carl von Clausewitz — So it can help me plan my takeover of the world, muahahaha. So I can see how well it can learn information that probably doesn't come up too much in its pretraining data. Also, because Clausewitz is cool. Also, because I saw it while browsing Gutenberg and thought it'd be interesting to add.
- Simple Sabotage, by the Office of Strategic Services — This one was originally a curiosity add during my testing, but I kept it in the final product to show off how Augmentoolkit handles manual-style texts by default. Now models trained on the dataset can tell you how to delay trains, set fires, be bad at your job, etc.
- Introduction to Logic and Critical Thinking by Matthew Van Cleave — By far the least-famous text in this list, I wanted to see if making the model read a logic textbook would teach it to think better, or at least understand the concept of thought better. It mucked up the bits with end-of-chapter exercises but lots of other stuff came out nicely. It might be better to train examples from this text WITH THE SOURCE TEXT INCLUDED IN THE PROMPT and a special instruction that both characters know that information, since a ton of the conversations refer to in-chapter examples that just don't make sense out of context. A cautionary tale about the importance of removing such things, or adjusting the text suitability prompt, for textbooks.
Relevant Anime Mascot:
 | Heralax/Augmentoolkit-demo | [
"region:us"
] | 2024-01-03T10:15:54+00:00 | {} | 2024-01-04T21:42:55+00:00 | [] | [] | TAGS
#region-us
| # This is a demonstration dataset created using Augmentoolkit and some [Project Gutenberg]() books.
# Augmentoolkit lets you use local models running on your own machine to create datasets based on any text you can conceive of.
# This dataset is just an example of how you can use it. If you finetune models (or want to) feel free to explore it for yourself!
(Even if you don't finetune models, you could still create and open source a standalone dataset like this one!)
# For some reason HuggingFace's dataset viewer is insistent on using the images as the dataset, not the actual .jsonl file. Not sure what I can do about that.
This dataset is a mix of nearly optimal (Simple Sabotage, On War, Principles of Chemistry) and highly suboptimal (Logic and Critical Thinking) books and manuals, built to see how Augmentoolkit handles a variety of texts. More details about the project can be found in the README of Augmentoolkit. Augmentoolkit is built to make data a strength of finetuning, rather than a barrier-to-entry and a perpetual headache. If you make your own models I encourage you to give it a shot.
This demo dataset can be used to fine-tune models, and I encourage you to try doing so. Ideally the resulting model would know the information contained in the dataset after a good finetune. To make it more likely that the model learns the information in these examples, not just their style, it might be best to use a high LoRA rank!
Further, note that this dataset is more of an experiment and a test than the primary contribution of my last three months: that honor goes to Augmentoolkit.
Here's a brief, comedic flowchart illustrating why I made Augmentoolkit:
Easily make your own datasets with tens of thousands of training examples, based on any source text you want, using your own computer, all from an easy-to-use Jupyter Notebook, via the Augmentoolkit repo. Contributions welcome!
Full text list and reasons for inclusion:
- Principles of Chemistry by Demitry Mendeleev — because I wanted some knowledge from a science that everyone knows a bit about, and this was available on Gutenberg. Also the intro to this book is surprisingly philosophical and might give a model some neat ideas about knowledge and keeping up with a rapidly-growing field, so it's relevant to us. Naturally some of the information in this book is going to be very out of date — Mendeleev didn't even know what a proton was. But that itself makes for an interesting test — can models learn outdated/wrong information using data generated from the Augmentoolkit, and does that learning overwrite up-to-date information? NOTE: Not all of this book was used, to save time. It's very, very long. Also, the questions based on markdown tables that somehow passed the filter are probably BS.
- On Liberty by John Stuart Mill — I wanted to see how it would handle a fully philosophical and opinionated text. The answer seems to be "pretty well", which means that those few-shot examples from Plato's The Republic and Nietzsche's Thus Spake Zarathustra paid off.
- On War by Carl von Clausewitz — So it can help me plan my takeover of the world, muahahaha. So I can see how well it can learn information that probably doesn't come up too much in its pretraining data. Also, because Clausewitz is cool. Also, because I saw it while browsing Gutenberg and thought it'd be interesting to add.
- Simple Sabotage, by the Office of Strategic Services — This one was originally a curiosity add during my testing, but I kept it in the final product to show off how Augmentoolkit handles manual-style texts by default. Now models trained on the dataset can tell you how to delay trains, set fires, be bad at your job, etc.
- Introduction to Logic and Critical Thinking by Matthew Van Cleave — By far the least-famous text in this list, I wanted to see if making the model read a logic textbook would teach it to think better, or at least understand the concept of thought better. It mucked up the bits with end-of-chapter exercises but lots of other stuff came out nicely. It might be better to train examples from this text WITH THE SOURCE TEXT INCLUDED IN THE PROMPT and a special instruction that both characters know that information, since a ton of the conversations refer to in-chapter examples that just don't make sense out of context. A cautionary tale about the importance of removing such things, or adjusting the text suitability prompt, for textbooks.
Relevant Anime Mascot:
 | [
"# This is a demonstration dataset created using Augmentoolkit and some [Project Gutenberg]() books.",
"# Augmentoolkit lets you use local models running on your own machine to create datasets based on any text you can conceive of.",
"# This dataset is just an example of how you can use it. If you finetune models (or want to) feel free to explore it for yourself!\n(Even if you don't finetune models, you could still create and open source a standalone dataset like this one!)",
"# For some reason HuggingFace's dataset viewer is insistent on using the images as the dataset, not the actual .jsonl file. Not sure what I can do about that.\n\nThis dataset is a mix of nearly optimal (Simple Sabotage, On War, Principles of Chemistry) and highly suboptimal (Logic and Critical Thinking) books and manuals, built to see how Augmentoolkit handles a variety of texts. More details about the project can be found in the README of Augmentoolkit. Augmentoolkit is built to make data a strength of finetuning, rather than a barrier-to-entry and a perpetual headache. If you make your own models I encourage you to give it a shot.\n\nThis demo dataset can be used to fine-tune models, and I encourage you to try doing so. Ideally the resulting model would know the information contained in the dataset after a good finetune. To make it more likely that the model learns the information in these examples, not just their style, it might be best to use a high LoRA rank!\n\nFurther, note that this dataset is more of an experiment and a test than the primary contribution of my last three months: that honor goes to Augmentoolkit. \n\nHere's a brief, comedic flowchart illustrating why I made Augmentoolkit:\n\n\nEasily make your own datasets with tens of thousands of training examples, based on any source text you want, using your own computer, all from an easy-to-use Jupyter Notebook, via the Augmentoolkit repo. Contributions welcome!\n\nFull text list and reasons for inclusion:\n- Principles of Chemistry by Demitry Mendeleev — because I wanted some knowledge from a science that everyone knows a bit about, and this was available on Gutenberg. Also the intro to this book is surprisingly philosophical and might give a model some neat ideas about knowledge and keeping up with a rapidly-growing field, so it's relevant to us. Naturally some of the information in this book is going to be very out of date — Mendeleev didn't even know what a proton was. But that itself makes for an interesting test — can models learn outdated/wrong information using data generated from the Augmentoolkit, and does that learning overwrite up-to-date information? NOTE: Not all of this book was used, to save time. It's very, very long. Also, the questions based on markdown tables that somehow passed the filter are probably BS.\n- On Liberty by John Stuart Mill — I wanted to see how it would handle a fully philosophical and opinionated text. The answer seems to be \"pretty well\", which means that those few-shot examples from Plato's The Republic and Nietzsche's Thus Spake Zarathustra paid off.\n- On War by Carl von Clausewitz — So it can help me plan my takeover of the world, muahahaha. So I can see how well it can learn information that probably doesn't come up too much in its pretraining data. Also, because Clausewitz is cool. Also, because I saw it while browsing Gutenberg and thought it'd be interesting to add.\n- Simple Sabotage, by the Office of Strategic Services — This one was originally a curiosity add during my testing, but I kept it in the final product to show off how Augmentoolkit handles manual-style texts by default. Now models trained on the dataset can tell you how to delay trains, set fires, be bad at your job, etc.\n- Introduction to Logic and Critical Thinking by Matthew Van Cleave — By far the least-famous text in this list, I wanted to see if making the model read a logic textbook would teach it to think better, or at least understand the concept of thought better. It mucked up the bits with end-of-chapter exercises but lots of other stuff came out nicely. It might be better to train examples from this text WITH THE SOURCE TEXT INCLUDED IN THE PROMPT and a special instruction that both characters know that information, since a ton of the conversations refer to in-chapter examples that just don't make sense out of context. A cautionary tale about the importance of removing such things, or adjusting the text suitability prompt, for textbooks.\n\nRelevant Anime Mascot:\n"
] | [
"TAGS\n#region-us \n",
"# This is a demonstration dataset created using Augmentoolkit and some [Project Gutenberg]() books.",
"# Augmentoolkit lets you use local models running on your own machine to create datasets based on any text you can conceive of.",
"# This dataset is just an example of how you can use it. If you finetune models (or want to) feel free to explore it for yourself!\n(Even if you don't finetune models, you could still create and open source a standalone dataset like this one!)",
"# For some reason HuggingFace's dataset viewer is insistent on using the images as the dataset, not the actual .jsonl file. Not sure what I can do about that.\n\nThis dataset is a mix of nearly optimal (Simple Sabotage, On War, Principles of Chemistry) and highly suboptimal (Logic and Critical Thinking) books and manuals, built to see how Augmentoolkit handles a variety of texts. More details about the project can be found in the README of Augmentoolkit. Augmentoolkit is built to make data a strength of finetuning, rather than a barrier-to-entry and a perpetual headache. If you make your own models I encourage you to give it a shot.\n\nThis demo dataset can be used to fine-tune models, and I encourage you to try doing so. Ideally the resulting model would know the information contained in the dataset after a good finetune. To make it more likely that the model learns the information in these examples, not just their style, it might be best to use a high LoRA rank!\n\nFurther, note that this dataset is more of an experiment and a test than the primary contribution of my last three months: that honor goes to Augmentoolkit. \n\nHere's a brief, comedic flowchart illustrating why I made Augmentoolkit:\n\n\nEasily make your own datasets with tens of thousands of training examples, based on any source text you want, using your own computer, all from an easy-to-use Jupyter Notebook, via the Augmentoolkit repo. Contributions welcome!\n\nFull text list and reasons for inclusion:\n- Principles of Chemistry by Demitry Mendeleev — because I wanted some knowledge from a science that everyone knows a bit about, and this was available on Gutenberg. Also the intro to this book is surprisingly philosophical and might give a model some neat ideas about knowledge and keeping up with a rapidly-growing field, so it's relevant to us. Naturally some of the information in this book is going to be very out of date — Mendeleev didn't even know what a proton was. But that itself makes for an interesting test — can models learn outdated/wrong information using data generated from the Augmentoolkit, and does that learning overwrite up-to-date information? NOTE: Not all of this book was used, to save time. It's very, very long. Also, the questions based on markdown tables that somehow passed the filter are probably BS.\n- On Liberty by John Stuart Mill — I wanted to see how it would handle a fully philosophical and opinionated text. The answer seems to be \"pretty well\", which means that those few-shot examples from Plato's The Republic and Nietzsche's Thus Spake Zarathustra paid off.\n- On War by Carl von Clausewitz — So it can help me plan my takeover of the world, muahahaha. So I can see how well it can learn information that probably doesn't come up too much in its pretraining data. Also, because Clausewitz is cool. Also, because I saw it while browsing Gutenberg and thought it'd be interesting to add.\n- Simple Sabotage, by the Office of Strategic Services — This one was originally a curiosity add during my testing, but I kept it in the final product to show off how Augmentoolkit handles manual-style texts by default. Now models trained on the dataset can tell you how to delay trains, set fires, be bad at your job, etc.\n- Introduction to Logic and Critical Thinking by Matthew Van Cleave — By far the least-famous text in this list, I wanted to see if making the model read a logic textbook would teach it to think better, or at least understand the concept of thought better. It mucked up the bits with end-of-chapter exercises but lots of other stuff came out nicely. It might be better to train examples from this text WITH THE SOURCE TEXT INCLUDED IN THE PROMPT and a special instruction that both characters know that information, since a ton of the conversations refer to in-chapter examples that just don't make sense out of context. A cautionary tale about the importance of removing such things, or adjusting the text suitability prompt, for textbooks.\n\nRelevant Anime Mascot:\n"
] | [
6,
25,
31,
61,
996
] | [
"passage: TAGS\n#region-us \n# This is a demonstration dataset created using Augmentoolkit and some [Project Gutenberg]() books.# Augmentoolkit lets you use local models running on your own machine to create datasets based on any text you can conceive of.# This dataset is just an example of how you can use it. If you finetune models (or want to) feel free to explore it for yourself!\n(Even if you don't finetune models, you could still create and open source a standalone dataset like this one!)"
] |
42f52c64f929c87a58e52bb09904ec60033b645e | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | AstroAlpha/Personal_Dataset | [
"task_categories:conversational",
"size_categories:n<1K",
"language:en",
"license:mit",
"not-for-all-audiences",
"region:us"
] | 2024-01-03T10:28:23+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["conversational"], "pretty_name": "Savita", "tags": ["not-for-all-audiences"]} | 2024-01-03T10:54:40+00:00 | [] | [
"en"
] | TAGS
#task_categories-conversational #size_categories-n<1K #language-English #license-mit #not-for-all-audiences #region-us
| # Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
## Dataset Details
### Dataset Description
- Curated by:
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP):
- License:
### Dataset Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#task_categories-conversational #size_categories-n<1K #language-English #license-mit #not-for-all-audiences #region-us \n",
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
44,
34,
4,
40,
29,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#task_categories-conversational #size_categories-n<1K #language-English #license-mit #not-for-all-audiences #region-us \n# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
c5e7b053f5cbfe5d417c2fecb2e50e9bcc0d028d | # Dataset Card for "araproje_mmlu_tr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_mmlu_tr | [
"region:us"
] | 2024-01-03T10:51:27+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "subject", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}], "splits": [{"name": "validation", "num_bytes": 137404, "num_examples": 250}], "download_size": 84003, "dataset_size": 137404}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:26:12+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_mmlu_tr"
More Information needed | [
"# Dataset Card for \"araproje_mmlu_tr\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_mmlu_tr\"\n\nMore Information needed"
] | [
6,
18
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_mmlu_tr\"\n\nMore Information needed"
] |
00685895ae259b49e8251eba5a46a2383da6d719 | # Dataset Card for "araproje_mmlu_en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_mmlu_en | [
"region:us"
] | 2024-01-03T10:51:52+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "subject", "dtype": "string"}, {"name": "choices", "sequence": "string"}, {"name": "answer", "dtype": {"class_label": {"names": {"0": "A", "1": "B", "2": "C", "3": "D"}}}}], "splits": [{"name": "validation", "num_bytes": 124670.8033964729, "num_examples": 250}], "download_size": 79218, "dataset_size": 124670.8033964729}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:26:15+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_mmlu_en"
More Information needed | [
"# Dataset Card for \"araproje_mmlu_en\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_mmlu_en\"\n\nMore Information needed"
] | [
6,
18
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_mmlu_en\"\n\nMore Information needed"
] |
914edd1635c621d5cfd9113e654460a8d2b85d7e | # Dataset Card for "araproje_truthful_en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_truthful_en | [
"region:us"
] | 2024-01-03T10:56:49+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "mc1_targets", "struct": [{"name": "choices", "sequence": "string"}, {"name": "labels", "sequence": "int32"}]}, {"name": "mc2_targets", "struct": [{"name": "choices", "sequence": "string"}, {"name": "labels", "sequence": "int32"}]}], "splits": [{"name": "validation", "num_bytes": 186377.60097919215, "num_examples": 250}], "download_size": 88685, "dataset_size": 186377.60097919215}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:11:10+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_truthful_en"
More Information needed | [
"# Dataset Card for \"araproje_truthful_en\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_truthful_en\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_truthful_en\"\n\nMore Information needed"
] |
ad6f7cbc48a2a9be562effa0da646ab656309887 | # Dataset Card for "araproje_truthful_tr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_truthful_tr | [
"region:us"
] | 2024-01-03T10:57:05+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "mc1_targets", "struct": [{"name": "choices", "sequence": "string"}, {"name": "labels", "sequence": "int32"}]}, {"name": "mc2_targets", "struct": [{"name": "choices", "sequence": "string"}, {"name": "labels", "sequence": "int32"}]}], "splits": [{"name": "validation", "num_bytes": 204710, "num_examples": 250}], "download_size": 97922, "dataset_size": 204710}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:11:07+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_truthful_tr"
More Information needed | [
"# Dataset Card for \"araproje_truthful_tr\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_truthful_tr\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_truthful_tr\"\n\nMore Information needed"
] |
eeca3dfe23beac99918aebbfb93cf5acb9676211 | # Dataset Card for "araproje_arc_tr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_arc_tr | [
"region:us"
] | 2024-01-03T11:04:41+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "choices", "sequence": [{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "string"}]}, {"name": "answerKey", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 86423, "num_examples": 250}], "download_size": 50786, "dataset_size": 86423}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:54:02+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_arc_tr"
More Information needed | [
"# Dataset Card for \"araproje_arc_tr\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_arc_tr\"\n\nMore Information needed"
] | [
6,
18
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_arc_tr\"\n\nMore Information needed"
] |
3d84bb0214049a482b51be3185f7a1a93d050233 | # Dataset Card for "araproje_arc_en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_arc_en | [
"region:us"
] | 2024-01-03T11:04:47+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "choices", "sequence": [{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "string"}]}, {"name": "answerKey", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 80819.39799331104, "num_examples": 250}], "download_size": 47049, "dataset_size": 80819.39799331104}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T11:54:06+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_arc_en"
More Information needed | [
"# Dataset Card for \"araproje_arc_en\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_arc_en\"\n\nMore Information needed"
] | [
6,
18
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_arc_en\"\n\nMore Information needed"
] |
b3eaa2aed3a2d200c2596908c319a684e34a4eaa | # Dataset Card for "araproje_hellaswag_tr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_hellaswag_tr | [
"region:us"
] | 2024-01-03T11:08:24+00:00 | {"dataset_info": {"features": [{"name": "ind", "dtype": "int32"}, {"name": "activity_label", "dtype": "string"}, {"name": "ctx_a", "dtype": "string"}, {"name": "ctx_b", "dtype": "string"}, {"name": "ctx", "dtype": "string"}, {"name": "endings", "sequence": "string"}, {"name": "source_id", "dtype": "string"}, {"name": "split", "dtype": "string"}, {"name": "split_type", "dtype": "string"}, {"name": "label", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 322786, "num_examples": 250}], "download_size": 198483, "dataset_size": 324830}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T13:33:55+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_hellaswag_tr"
More Information needed | [
"# Dataset Card for \"araproje_hellaswag_tr\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_hellaswag_tr\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_hellaswag_tr\"\n\nMore Information needed"
] |
3f09758c0892a87d4425cb87057a375327418a18 | # Dataset Card for "araproje_hellaswag_en"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ibranze/araproje_hellaswag_en | [
"region:us"
] | 2024-01-03T11:08:32+00:00 | {"dataset_info": {"features": [{"name": "ind", "dtype": "int32"}, {"name": "activity_label", "dtype": "string"}, {"name": "ctx_a", "dtype": "string"}, {"name": "ctx_b", "dtype": "string"}, {"name": "ctx", "dtype": "string"}, {"name": "endings", "sequence": "string"}, {"name": "source_id", "dtype": "string"}, {"name": "split", "dtype": "string"}, {"name": "split_type", "dtype": "string"}, {"name": "label", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 149738, "num_examples": 250}], "download_size": 81091, "dataset_size": 149738}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T13:37:28+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "araproje_hellaswag_en"
More Information needed | [
"# Dataset Card for \"araproje_hellaswag_en\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"araproje_hellaswag_en\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"araproje_hellaswag_en\"\n\nMore Information needed"
] |
012543b3692099045ae26b8549ae47eb0f8f12c2 |
# Introduction
The "Ameresco-ASR" Subset is a specialized extract from the "Corpus Ameresco" (Albelda and Estellés, online), focusing on colloquial Spanish spoken in various cities across Spain and the Americas. This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. To achieve this, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the Ameresco corpus, offering diverse samples of colloquial Spanish from different sociolects and regions. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, maintaining a balance between comprehensive coverage and computational efficiency.
# Content and Geographic Focus
The original Ameresco corpus was initiated as a collaborative project led by Antonio Briz, focusing on the study of colloquial Spanish in European and American geolects. The project included initiatives such as incorporating American usages and Americanisms into the Dictionary of Discourse Particles of Spanish (www.dpde.es), directed by Antonio Briz, Salvador Pons, and José Portolés, as well as the study of attenuation in various Spanish dialects (Projects Es. Var. Atenuación [IP. Marta Albelda], Es VaG. Atenuación [IP Marta Albelda, Maria Estellés]). The project Es.Por.Atenuación, led by Antonio Briz, was also part of this effort, which involved studying attenuation in Portuguese and comparing it with Spanish. Currently, the project is funded by the Esprint project of the Ministry of Science and Innovation (PID2020-114805GB-100, IP Marta Albelda, Maria Estellés).
The primary outcome of the Ameresco project is the compilation of the Ameresco corpus, which aims to gather samples of colloquial conversations from major cities in Spain, including Santiago de Chile, Tegucigalpa, Temuco, Tucumán, Barranquilla, Buenos Aires, Ciudad de México, Ciudad de Panamá, Iquique, La Habana, Las Palmas, Loja, Medellín, Monterrey, Querétaro, and Santa Cruz in the Americas. This corpus provides a rich resource for studying colloquial Spanish across different regions and sociolects.
# Transcription approach
See work documents on https://esvaratenuacion.es/protocolo-de-trabajo
# References
Albelda, M. y Estellés, M. (coords.): Corpus Ameresco, Universitat de València, ISSN: 2659-8337, www.corpusameresco.com | johnatanebonilla/ameresco-asr | [
"task_categories:automatic-speech-recognition",
"task_categories:conversational",
"size_categories:10K<n<100K",
"language:es",
"region:us"
] | 2024-01-03T11:42:06+00:00 | {"language": ["es"], "size_categories": ["10K<n<100K"], "task_categories": ["automatic-speech-recognition", "conversational"], "pretty_name": "AMERESCO-ASR Subset", "dataset_info": {"features": [{"name": "audio", "dtype": "audio"}, {"name": "id", "dtype": "int64"}, {"name": "time", "dtype": "string"}, {"name": "sentence", "dtype": "string"}, {"name": "orig_file_name", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1440415495.732, "num_examples": 19588}, {"name": "validation", "num_bytes": 169864351.65, "num_examples": 2449}, {"name": "test", "num_bytes": 175082366.835, "num_examples": 2449}], "download_size": 1551213354, "dataset_size": 1785362214.2170002}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-03T12:24:24+00:00 | [] | [
"es"
] | TAGS
#task_categories-automatic-speech-recognition #task_categories-conversational #size_categories-10K<n<100K #language-Spanish #region-us
|
# Introduction
The "Ameresco-ASR" Subset is a specialized extract from the "Corpus Ameresco" (Albelda and Estellés, online), focusing on colloquial Spanish spoken in various cities across Spain and the Americas. This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. To achieve this, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the Ameresco corpus, offering diverse samples of colloquial Spanish from different sociolects and regions. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, maintaining a balance between comprehensive coverage and computational efficiency.
# Content and Geographic Focus
The original Ameresco corpus was initiated as a collaborative project led by Antonio Briz, focusing on the study of colloquial Spanish in European and American geolects. The project included initiatives such as incorporating American usages and Americanisms into the Dictionary of Discourse Particles of Spanish (URL), directed by Antonio Briz, Salvador Pons, and José Portolés, as well as the study of attenuation in various Spanish dialects (Projects Es. Var. Atenuación [IP. Marta Albelda], Es VaG. Atenuación [IP Marta Albelda, Maria Estellés]). The project Es.Por.Atenuación, led by Antonio Briz, was also part of this effort, which involved studying attenuation in Portuguese and comparing it with Spanish. Currently, the project is funded by the Esprint project of the Ministry of Science and Innovation (PID2020-114805GB-100, IP Marta Albelda, Maria Estellés).
The primary outcome of the Ameresco project is the compilation of the Ameresco corpus, which aims to gather samples of colloquial conversations from major cities in Spain, including Santiago de Chile, Tegucigalpa, Temuco, Tucumán, Barranquilla, Buenos Aires, Ciudad de México, Ciudad de Panamá, Iquique, La Habana, Las Palmas, Loja, Medellín, Monterrey, Querétaro, and Santa Cruz in the Americas. This corpus provides a rich resource for studying colloquial Spanish across different regions and sociolects.
# Transcription approach
See work documents on URL
# References
Albelda, M. y Estellés, M. (coords.): Corpus Ameresco, Universitat de València, ISSN: 2659-8337, URL | [
"# Introduction\nThe \"Ameresco-ASR\" Subset is a specialized extract from the \"Corpus Ameresco\" (Albelda and Estellés, online), focusing on colloquial Spanish spoken in various cities across Spain and the Americas. This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. To achieve this, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the Ameresco corpus, offering diverse samples of colloquial Spanish from different sociolects and regions. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, maintaining a balance between comprehensive coverage and computational efficiency.",
"# Content and Geographic Focus\nThe original Ameresco corpus was initiated as a collaborative project led by Antonio Briz, focusing on the study of colloquial Spanish in European and American geolects. The project included initiatives such as incorporating American usages and Americanisms into the Dictionary of Discourse Particles of Spanish (URL), directed by Antonio Briz, Salvador Pons, and José Portolés, as well as the study of attenuation in various Spanish dialects (Projects Es. Var. Atenuación [IP. Marta Albelda], Es VaG. Atenuación [IP Marta Albelda, Maria Estellés]). The project Es.Por.Atenuación, led by Antonio Briz, was also part of this effort, which involved studying attenuation in Portuguese and comparing it with Spanish. Currently, the project is funded by the Esprint project of the Ministry of Science and Innovation (PID2020-114805GB-100, IP Marta Albelda, Maria Estellés).\n\nThe primary outcome of the Ameresco project is the compilation of the Ameresco corpus, which aims to gather samples of colloquial conversations from major cities in Spain, including Santiago de Chile, Tegucigalpa, Temuco, Tucumán, Barranquilla, Buenos Aires, Ciudad de México, Ciudad de Panamá, Iquique, La Habana, Las Palmas, Loja, Medellín, Monterrey, Querétaro, and Santa Cruz in the Americas. This corpus provides a rich resource for studying colloquial Spanish across different regions and sociolects.",
"# Transcription approach\n\nSee work documents on URL",
"# References\n\nAlbelda, M. y Estellés, M. (coords.): Corpus Ameresco, Universitat de València, ISSN: 2659-8337, URL"
] | [
"TAGS\n#task_categories-automatic-speech-recognition #task_categories-conversational #size_categories-10K<n<100K #language-Spanish #region-us \n",
"# Introduction\nThe \"Ameresco-ASR\" Subset is a specialized extract from the \"Corpus Ameresco\" (Albelda and Estellés, online), focusing on colloquial Spanish spoken in various cities across Spain and the Americas. This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. To achieve this, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the Ameresco corpus, offering diverse samples of colloquial Spanish from different sociolects and regions. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, maintaining a balance between comprehensive coverage and computational efficiency.",
"# Content and Geographic Focus\nThe original Ameresco corpus was initiated as a collaborative project led by Antonio Briz, focusing on the study of colloquial Spanish in European and American geolects. The project included initiatives such as incorporating American usages and Americanisms into the Dictionary of Discourse Particles of Spanish (URL), directed by Antonio Briz, Salvador Pons, and José Portolés, as well as the study of attenuation in various Spanish dialects (Projects Es. Var. Atenuación [IP. Marta Albelda], Es VaG. Atenuación [IP Marta Albelda, Maria Estellés]). The project Es.Por.Atenuación, led by Antonio Briz, was also part of this effort, which involved studying attenuation in Portuguese and comparing it with Spanish. Currently, the project is funded by the Esprint project of the Ministry of Science and Innovation (PID2020-114805GB-100, IP Marta Albelda, Maria Estellés).\n\nThe primary outcome of the Ameresco project is the compilation of the Ameresco corpus, which aims to gather samples of colloquial conversations from major cities in Spain, including Santiago de Chile, Tegucigalpa, Temuco, Tucumán, Barranquilla, Buenos Aires, Ciudad de México, Ciudad de Panamá, Iquique, La Habana, Las Palmas, Loja, Medellín, Monterrey, Querétaro, and Santa Cruz in the Americas. This corpus provides a rich resource for studying colloquial Spanish across different regions and sociolects.",
"# Transcription approach\n\nSee work documents on URL",
"# References\n\nAlbelda, M. y Estellés, M. (coords.): Corpus Ameresco, Universitat de València, ISSN: 2659-8337, URL"
] | [
49,
160,
349,
9,
37
] | [
"passage: TAGS\n#task_categories-automatic-speech-recognition #task_categories-conversational #size_categories-10K<n<100K #language-Spanish #region-us \n# Introduction\nThe \"Ameresco-ASR\" Subset is a specialized extract from the \"Corpus Ameresco\" (Albelda and Estellés, online), focusing on colloquial Spanish spoken in various cities across Spain and the Americas. This dataset has been specifically curated to facilitate the fine-tuning of Whisper, an automatic speech recognition system. To achieve this, audio and text segments ranging from 3 to 30 seconds have been automatically extracted from the Ameresco corpus, offering diverse samples of colloquial Spanish from different sociolects and regions. To ensure manageability and efficient processing, a maximum of 1024 tokens were used in the dataset, maintaining a balance between comprehensive coverage and computational efficiency."
] |
385d278d19f5ccca5a4bd3f4f91db7901dc1ca5c | <h2><strong><a href="https://myhealthfitnessmart.blogspot.com/2024/01/guardian-botanicals-blood-balance.html">Guardian Botanicals Blood Balance</a> Review </strong></h2>
<p><a href="https://carehealthreview.blogspot.com/2024/01/guardian-botanicals-blood-balance.html"><strong>Guardian Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level. This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This <a href="https://myhealthfitnessmart.blogspot.com/2024/01/guardian-botanicals-blood-balance.html"><strong>Guardian Botanicals Blood Balance</strong></a> review focuses on a product that will help you maintain a healthy blood flow. There are many blood-balancing products on the market, making it difficult to choose which one is best for you. Do you feel it is the best one you have tried?</p>
<h2><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>Guardian Botanicals Blood Balance — Official Website Link — Click Here</strong></a></h2>
<h2><strong>►❱❱ Product Name ➥ {</strong><strong><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Guardian Botanicals Blood Balance</a>}</strong><br /><strong>►❱❱ Countries Available ➥ World Wide</strong><br /><strong>►❱❱ Composition ➥ Natural Organic Compound</strong><br /><strong>►❱❱ Side-Effects ➥ NA</strong><br /><strong>►❱❱ Rating ➥ ⭐⭐⭐⭐⭐</strong><br /><strong>►❱❱ Availability ➥ <a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Online</a></strong><br /><strong>➤➤❱❱ Where to Buy ➺ <a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au">Official Website</a><br /></strong></h2>
<h2><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a><br /><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a><br /><a href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>✅”Visit The Official Website To Get Your Bottle Now”✅</strong></a></h2>
<p>Consider the health risks you'll be taking if you use expensive products or take supplements that are potentially dangerous. With this in mind, I decided to share The Guardian Botanicals' Blood Balance, which I discovered through extensive research. It's important that I share it with you, so you can see how valuable the supplement is.To find out if this <a href="https://guardian-botanicals-australia.clubeo.com/"><strong>Guardian Botanicals Blood Balance</strong></a> pill is right for you, read the <a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html"><strong>Guardian Botanicals Blood Balance</strong></a> review. Then make the right decision.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRgtOhomp2khVg7WUdD559TA_AxoZnujX97_4ftissoDXXPzLxwtTEbBWxWdY8SWclSuq6BpBOkfor-tcvi1qp8SNVytJPRRbUsqSULmxXIs5zH3B39pKleVfz5xrl2bk00MnYOqSoLScqzW71OTv4xgN0rm33nAQ61xlBLXhOmh-Rf8xZKWouj05_apS-/w640-h410/Guardian%20Botanicals%20Blood%20Balance7.jpg" alt="" width="640" height="410" border="0" data-original-height="454" data-original-width="709" /></a></div>
<h2><strong>What is <a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html">Guardian Botanicals Blood Balance</a>?</strong></h2>
<p><a href="https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement"><strong>Guardian Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level . This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This formula is 100% made from authentic herbs and plant extracts. It works well for all ages. Guardian Blood Balance was meticulously filtered to remove any toxic metals and other substances. The facility where the supplement was made received FDA approval and GMP certification. This supplement is non-GMO, so you don't need to worry about preservatives, stimulants, or gluten.The company has not compromised on the quality of its products, and that is why it has been able to earn a reputation.</p>
<p style="text-align: justify;">Guardian Blood Balance Mexico is happily made in the United States, following strict GMP rules and guidelines to make sure it is pure and works.This Guardian Blood Balance product is safe for all people because it is carefully made with some of the cleanest and rarest plant and herbal extracts, which help the body clean its blood naturally.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>(EXCLUSIVE OFFER)Click Here : "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>How does <a href="https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/">Guardian Botanicals Blood Balance</a> work?</strong></h2>
<p><a href="https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc"><strong>Guardian Botanicals Blood Balance</strong></a> supplement activates a triple-action formula upon being taken. This supplement helps to maintain healthy blood sugar and blood pressure levels. It also solves obesity and weight gain issues. The formula is made up of ingredients that are strong and free from toxic substances. <a href="https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia"><strong>Guardian Botanicals Blood Balance</strong></a> is a scientifically-proven solution that has provided positive results for users.</p>
<p>Other ingredients will help keep your body clear by removing stubborn and unwanted fats that could be harmful. To keep your body healthy and to give you a youthful feeling, the formula will transform you from within.</p>
<p style="text-align: justify;">This advanced blood balance supplement improves your health in three ways. Your doctor will be perplexed as to why your blood test results changed so dramatically just a few months of consistent dosage! Strengthen your immune system so it can stave off a lifetime of blood-related illnesses.</p>
<p style="text-align: justify;">Enhance your well-being with this supplement that has been clinically confirmed to work. Maintain healthy cardiovascular and arterial function, enhance pancreatic function, and forestall the development of chronic illnesses and conditions associated with blood.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj76ZwAWQRVNWHn5ttf4NnrG1H2i90Xfor1Lrj9e3k2c6TFLWgy4j0Huz1z9A4qvHXV9pIN9RmPU2PJSnQnH6zGlimdH4xhkUhBvorJjtra3UrgWoNls7-HNEjdiRnLQP9IJpGBFHbBUMDIWDraqJ0ObT-9pX9o01bpKcUs-drBQT99p0X_9imk0LYxTCQK/w640-h360/Untitled%20(4)%20(1).png" alt="" width="640" height="360" border="0" data-original-height="1080" data-original-width="1920" /></a></div>
<h2><strong>Ingredients of <a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">Guardian Botanicals Blood Balance</a> Supplement</strong></h2>
<p><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/"><strong>Guardian Blood Balance</strong></a> is an exclusive combination of ingredients developed to enhance the outcomes of blood tests. Doctors check for cholesterol, glucose, and blood pressure when they draw blood to evaluate your health. You are in danger if your reading is high in any of these three areas.</p>
<p><strong>#White Mulberry Leaf</strong></p>
<p>There are substances in white mulberry leaf that work in a way that is comparable to types 2 diabetic treatments.These substances help control blood sugar levels by easing the digestive process and smoothing the absorption of sugar into the circulation.The use of White Mulberry Leaf also aids in keeping blood pressure and cholesterol in healthy ranges.</p>
<p><strong>#Juniper Berry</strong></p>
<p>Juniper berry has been used in traditional medicine for a long time, and it now provides many new health advantages. The minerals and powerful substances with antioxidant and anti-inflammatory capabilities are concentrated in its extract.</p>
<p><strong>#Biotin + Chromium</strong></p>
<p>Biotin, or vitamin B-7, helps keep metabolism healthy and may be useful while trying to control one's weight. It helps the body use the nutrients in meals for energy and distributes them more efficiently, just like the other B vitamins.</p>
<p><strong>#Berberine Extract</strong></p>
<p>Herbs and plants such as tree turmeric, goldenseal, and Oregon grape contain berberine extract as a natural ingredient.The effects of berberine on blood sugar, cholesterol, and triglyceride levels have been studied.In the right doses, this alkaloid improves insulin action and has other positive effects on health.</p>
<p><strong>#Bitter Melon</strong></p>
<p>Potent antioxidants and anti-inflammatory substances are found in bitter melons. Its qualities are thought to promote healthy blood parameters by lowering bad cholesterol and increasing good cholesterol and lowering blood sugar levels.</p>
<p><strong>#Cinnamon Bark Powder</strong></p>
<p>The use of cinnamon bark powder can help with insulin resistance and level management.In addition to easing gas and spasms, it helps with gastrointestinal problems. In addition to its insulin-like characteristics, which help lower blood glucose levels, it is believed to improve blood circulation.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>What are the benefits of using <a href="https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD">Guardian Botanicals Blood Balance</a>?</strong></h2>
<p><a href="https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx"><strong>Guardian Botanicals Blood Balance</strong></a> can help people improve their health and well-being by focusing on weight loss and reducing their blood sugar levels. We recommend Guardian Blood Balance for the following main reasons:</p>
<p><strong>Reducing Blood Pressure:</strong> This all-natural <a href="https://sites.google.com/view/guardian-bloodbalance-price-au/home"><strong>Guardian Botanicals Blood Balance</strong></a> can assist with blood pressure control. Scientific studies have shown the efficacy of the product, which is formulated with all-natural ingredients.</p>
<p><strong>Controlling Blood Sugar Levels:</strong> Controlling blood sugar levels is one of the primary uses for Guardian Botanicals' Blood Balance. This recipe can lessen the likelihood of developing Type 2 Diabetes and its complications by regulating blood sugar levels.</p>
<p><strong>Reduces Bad Cholesterol:</strong> Guardian Blood Balance's all-natural ingredients work to lower bad cholesterol levels.</p>
<p><strong>Increase Good Cholesterol:</strong> Guardian Blood Balance is a dietary supplement that aids in the elimination of harmful cholesterol while enhancing good cholesterol levels.</p>
<p><strong>Facilitates Weight Loss:</strong> An important part of maintaining weight reduction is controlling blood sugar. Losing weight, increasing energy, and decreasing cravings are all possible with the correct carbohydrate to fat ratio.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5Dt6FS6aGzbkAR0B4iWZijfOMnHYUA2gTDiPKlUDCzJ6_rSoAx6K7N5e45zXdFIYs_hFwLYvtrycB84GwIQ21xwrhXC64KAOQdzEYGC1Ji22A7BHUo3U1D4_TwQM3kQlfizJ9o99E2k-0r4YwYH1ajYf50bvcUtmI9LMwxsOZXj7AFne7wkNoaK__uB1-/w640-h350/Guardian%20Botanicals%20Blood%20Balance.jpg" alt="" width="640" height="350" border="0" data-original-height="276" data-original-width="506" /></a></div>
<h2><strong>Side Effects of using <a href="https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo">Guardian Botanicals Blood Balance</a><br /></strong></h2>
<p>Guardian Botanicals' Blood Balance Supplement is a pure solution made with the best ingredients. Side effects were rare for those who took the recommended dose. The product was made in an FDA-approved, GMP-certified manufacturing facility.</p>
<p>Each bottle of Blood Balance Supplement is free from any preservatives or herbicides, stimulants or other chemicals that could harm your health. It may take some time but the results you will get are real. <a href="https://guardian-blood-balance-price.company.site/"><strong>Guardian Botanicals Blood Balance</strong></a> reviews have shown that the ingredients are completely natural and safe. Botanicals Blood Balance side effects are therefore minimal.</p>
<p>If you have any allergies or are taking medication, consult your doctor to ensure that you remain safe. The supplement is only for adults. Children should be avoided.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO: Get Guardian Botanicals Blood Balance at the Lowest Discounted Price Online</strong></a></span></h2>
<h2><strong><a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">Guardian Botanicals Blood Balance</a> Price & Where to Buy?</strong></h2>
<ul>
<li><strong>Buy one <a href="https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to">Guardian Botanicals Blood Balance</a> Supplement bottle for just $69.95</strong></li>
<li><strong>Buy two bottles of the <a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">Guardian Botanicals Blood Balance</a> Supplement and get a third bottle free, at $49.95 each.</strong></li>
<li><strong>Buy three bottles of the <a href="https://carehealthreview.blogspot.com/2024/01/guardian-botanicals-blood-balance.html">Guardian Botanicals Blood Balance</a> Supplement and get two more bottles free, at just $39.95 each.</strong></li>
</ul>
<p>These bottles contain inferior quality ingredients, which can be dangerous and could cause serious health problems. Only through the official website can you receive a 100% money-back guarantee. Click on the link below to order guardian botanicals blood balance supplement directly to the official site.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhz9fdGrhIcJdiH28VNctZWP3AyEXQ5PTIXTuvZcEsCUoNov6Eud-dNlmTAqeUmx-kVIzKPzRyLMaEKDSNss0T5nfOgsRGt_sHQEc7wYirF-0WyL6p0wAz-FPWxGpGTtiPXKYkmnBqSXxxGEOIYUAMjGlJSs2RITnUGoalzOvka50ZQGyP-XW4DqoIVXWN7/w640-h422/review.jpg" alt="" width="640" height="422" border="0" data-original-height="422" data-original-width="639" /></a></div>
<h2><strong>Frequently Asked Question</strong></h2>
<p><strong>What does the Blood Balance Supplement do?</strong></p>
<p>The Blood Balance formula contains 100% natural ingredients which help to lower blood sugar, blood pressure, and bad cholesterol in a quick and effective manner.</p>
<p><strong>Is it safe to use?</strong></p>
<p>Blood Balance Supplement contains only natural, effective ingredients. This supplement was made in an FDA-approved, GMP-certified manufacturing facility. It is safe to use because it contains no harmful ingredients.</p>
<p><strong>How do I use Guardian Botanicals' blood balance?</strong></p>
<p>For easy swallowing, take 1 capsule of the Blood Balance supplement each day with a glass of water.</p>
<p><strong>Does this affect my medication?</strong></p>
<p>It is not necessary, but it is better to see a doctor.</p>
<p><strong>What happens if this doesn’t work?</strong></p>
<p>For 30 days, you get a 100% money-back guarantee. It is therefore risk-free.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>SPECIAL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>Final Verdict on <a href="https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!">Guardian Botanicals Blood Balance</a> Reviews</strong></h2>
<p><a href="https://bookshop.org/wishlists/45abc33870a15200c43c071c8dac8e95dd5d62b1"><strong>Guardian Botanicals Blood Balance</strong></a> was a supplement that gained a reputation for its positive results. This formula contains only organic and safe ingredients, which work well to balance blood sugar and blood pressure.</p>
<p>The Blood Balance Supplement users who used it for 2 to 3 months saw a greater health condition.<a href="https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-65952b4e0fd36eec92f34440"><strong> Guardian Botanicals Blood Balance</strong> </a>users have written reviews to share their experiences.</p>
<p>Some users claim they have lost excess fat and control their blood sugar and blood pressure. The recommended method of taking the Blood Balance capsules will allow you to see positive changes in your life.You get a 30-day guarantee of 100% satisfaction. If you are dissatisfied and cannot notice any changes, you can contact the customer service team to request a refund.If you are unsure, stop being sceptical and give the guardian the chance to prove you right.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><img src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQPVZoVTH8inZstDFwqqog2PLHocczy70z8FMORegRT3XSanNA93WSGdgeSsmXpcyHGtQTJcbSuMmfqtOwDy0P3GD9WGxdyMyPTkTWz68E_NOOmHrL5CPrSVIDY4pnAh-3_QFxBYB_m59Mr423hrJnzO5hIK_t68qno7-uMrBO0Y8DwMGjRko6HzkrIRfK/w542-h640/price.jpg" alt="" width="542" height="640" border="0" data-original-height="466" data-original-width="395" /></a></div>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="https://www.globalfitnessmart.com/get-guardian-blood-balance-au"><strong>Exclusive Details: *Guardian Botanicals Blood Balance* Read More Details on Official Website Australia!</strong></a></span></h2>
<h2># READ MORE INFO-</h2>
<p><span style="color: #ff0000;"><a href="https://guardian-blood-balance-price.company.site/">https://guardian-blood-balance-price.company.site/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo">https://groups.google.com/g/guardian-botanicals-blood-balance-reviews-price/c/saQ5TuKE0yo</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/">https://guardian-botanicals-blood-balance-11.jimdosite.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD">https://lookerstudio.google.com/u/0/reporting/3a2b1791-0eaf-4b56-89f9-ed3aa6faf9e1/page/sMZmD</a></span></p>
<p><span style="color: #ff0000;"><a href="https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx">https://colab.research.google.com/drive/1nEcVtIotIoc6Rf_EEFqsO1vezFAkSPVx</a></span></p>
<p><span style="color: #ff0000;"><a href="https://sites.google.com/view/guardian-bloodbalance-price-au/home">https://sites.google.com/view/guardian-bloodbalance-price-au/home</a></span></p>
<p><span style="color: #ff0000;"><a href="https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc">https://gamma.app/docs/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Healthy-Blood-S-dm0xfn4wxzm6dq2?mode=doc</a></span></p>
<p><span style="color: #ff0000;"><a href="https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/">https://forum.mmm.ucar.edu/threads/guardian-botanicals-blood-balance-review-australia-clinically-proven-suppprt-healthy-blood-levels.15112/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia">https://www.scoop.it/topic/guardian-botanicals-blood-balance-by-bloodsugar-australia</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-blood-balance-11.jimdosite.com/">https://guardian-botanicals-blood-balance-11.jimdosite.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/">https://guardian-botanicals-australia.clubeo.com/</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html">https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-reviews-does-it-work.html</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html">https://guardian-botanicals-australia.clubeo.com/page/guardian-botanicals-blood-balance-official-australia-updated-report-2024.html</a></span></p>
<p><span style="color: #ff0000;"><a href="https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement">https://guardian-botanicals-australia.clubeo.com/calendar/2024/01/04/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-reviews-scientifically-formulated-supplement</a></span></p>
<p><span style="color: #ff0000;"><a href="https://medium.com/@bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024-de1c8def2eef">https://medium.com/@bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024-de1c8def2eef</a></span></p>
<p><span style="color: #ff0000;"><a href="https://followme.tribe.so/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-659528554eef0bd4a84798e3">https://followme.tribe.so/post/guardian-botanicals-blood-balance-official-australia-updated-report-2024-659528554eef0bd4a84798e3</a></span></p>
<p><span style="color: #ff0000;"><a href="https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to">https://bitbucket.org/guardian-botanicals-blood-balance/guardian-botanicals-blood-balance/issues/1/guardian-botanicals-blood-balance-work-to</a></span></p>
<p><span style="color: #ff0000;"><a href="https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024">https://soundcloud.com/bloodsugaraustralia/guardian-botanicals-blood-balance-official-australia-updated-report-2024</a></span></p>
<p><span style="color: #ff0000;"><a href="https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!">https://leetcode.com/discuss/interview-question/4497605/Guardian-Botanicals-Blood-Balance-Work-To-Promote-Reviews-Scientifically-Formulated-Supplement!</a></span></p>
<p><span style="color: #ff0000;"><a href="https://wandering.flarum.cloud/d/35508-guardian-botanicals-blood-balance-reviews">https://wandering.flarum.cloud/d/35508-guardian-botanicals-blood-balance-reviews</a></span></p>
<p><span style="color: #ff0000;"><a href="https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-revie--65952c47151fd46d84209078">https://community.thebatraanumerology.com/post/guardian-botanicals-blood-balance-work-to-promote-healthy-blood-sugar-revie--65952c47151fd46d84209078</a></span></p>
<p> </p> | bloodsugaraustralia/guardian-blood-balance | [
"region:us"
] | 2024-01-03T11:48:46+00:00 | {} | 2024-01-03T11:49:00+00:00 | [] | [] | TAGS
#region-us
| <h2><strong><a href="URL Botanicals Blood Balance</a> Review </strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level. This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This <a href="URL Botanicals Blood Balance</strong></a> review focuses on a product that will help you maintain a healthy blood flow. There are many blood-balancing products on the market, making it difficult to choose which one is best for you. Do you feel it is the best one you have tried?</p>
<h2><a href="URL Botanicals Blood Balance — Official Website Link — Click Here</strong></a></h2>
<h2><strong>► Product Name {</strong><strong><a href="URL Botanicals Blood Balance</a>}</strong><br /><strong>► Countries Available World Wide</strong><br /><strong>► Composition Natural Organic Compound</strong><br /><strong>► Side-Effects NA</strong><br /><strong>► Rating ⭐⭐⭐⭐⭐</strong><br /><strong>► Availability <a href="URL /><strong> Where to Buy <a href="URL Website</a><br /></strong></h2>
<h2><a href="URL The Official Website To Get Your Bottle Now”</strong></a><br /><a href="URL The Official Website To Get Your Bottle Now”</strong></a><br /><a href="URL The Official Website To Get Your Bottle Now”</strong></a></h2>
<p>Consider the health risks you'll be taking if you use expensive products or take supplements that are potentially dangerous. With this in mind, I decided to share The Guardian Botanicals' Blood Balance, which I discovered through extensive research. It's important that I share it with you, so you can see how valuable the supplement is.To find out if this <a href="URL Botanicals Blood Balance</strong></a> pill is right for you, read the <a href="URL Botanicals Blood Balance</strong></a> review. Then make the right decision.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="410" border="0" data-original-height="454" data-original-width="709" /></a></div>
<h2><strong>What is <a href="URL Botanicals Blood Balance</a>?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> is an effective and natural formula that helps maintain a healthy blood sugar level . This formula helps to regulate blood sugar, and blood pressure and prevents you from developing insulin resistance.</p>
<p>This formula is 100% made from authentic herbs and plant extracts. It works well for all ages. Guardian Blood Balance was meticulously filtered to remove any toxic metals and other substances. The facility where the supplement was made received FDA approval and GMP certification. This supplement is non-GMO, so you don't need to worry about preservatives, stimulants, or gluten.The company has not compromised on the quality of its products, and that is why it has been able to earn a reputation.</p>
<p style="text-align: justify;">Guardian Blood Balance Mexico is happily made in the United States, following strict GMP rules and guidelines to make sure it is pure and works.This Guardian Blood Balance product is safe for all people because it is carefully made with some of the cleanest and rarest plant and herbal extracts, which help the body clean its blood naturally.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL OFFER)Click Here : "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>How does <a href="URL Botanicals Blood Balance</a> work?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> supplement activates a triple-action formula upon being taken. This supplement helps to maintain healthy blood sugar and blood pressure levels. It also solves obesity and weight gain issues. The formula is made up of ingredients that are strong and free from toxic substances. <a href="URL Botanicals Blood Balance</strong></a> is a scientifically-proven solution that has provided positive results for users.</p>
<p>Other ingredients will help keep your body clear by removing stubborn and unwanted fats that could be harmful. To keep your body healthy and to give you a youthful feeling, the formula will transform you from within.</p>
<p style="text-align: justify;">This advanced blood balance supplement improves your health in three ways. Your doctor will be perplexed as to why your blood test results changed so dramatically just a few months of consistent dosage! Strengthen your immune system so it can stave off a lifetime of blood-related illnesses.</p>
<p style="text-align: justify;">Enhance your well-being with this supplement that has been clinically confirmed to work. Maintain healthy cardiovascular and arterial function, enhance pancreatic function, and forestall the development of chronic illnesses and conditions associated with blood.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="360" border="0" data-original-height="1080" data-original-width="1920" /></a></div>
<h2><strong>Ingredients of <a href="URL Botanicals Blood Balance</a> Supplement</strong></h2>
<p><a href="URL Blood Balance</strong></a> is an exclusive combination of ingredients developed to enhance the outcomes of blood tests. Doctors check for cholesterol, glucose, and blood pressure when they draw blood to evaluate your health. You are in danger if your reading is high in any of these three areas.</p>
<p><strong>#White Mulberry Leaf</strong></p>
<p>There are substances in white mulberry leaf that work in a way that is comparable to types 2 diabetic treatments.These substances help control blood sugar levels by easing the digestive process and smoothing the absorption of sugar into the circulation.The use of White Mulberry Leaf also aids in keeping blood pressure and cholesterol in healthy ranges.</p>
<p><strong>#Juniper Berry</strong></p>
<p>Juniper berry has been used in traditional medicine for a long time, and it now provides many new health advantages. The minerals and powerful substances with antioxidant and anti-inflammatory capabilities are concentrated in its extract.</p>
<p><strong>#Biotin + Chromium</strong></p>
<p>Biotin, or vitamin B-7, helps keep metabolism healthy and may be useful while trying to control one's weight. It helps the body use the nutrients in meals for energy and distributes them more efficiently, just like the other B vitamins.</p>
<p><strong>#Berberine Extract</strong></p>
<p>Herbs and plants such as tree turmeric, goldenseal, and Oregon grape contain berberine extract as a natural ingredient.The effects of berberine on blood sugar, cholesterol, and triglyceride levels have been studied.In the right doses, this alkaloid improves insulin action and has other positive effects on health.</p>
<p><strong>#Bitter Melon</strong></p>
<p>Potent antioxidants and anti-inflammatory substances are found in bitter melons. Its qualities are thought to promote healthy blood parameters by lowering bad cholesterol and increasing good cholesterol and lowering blood sugar levels.</p>
<p><strong>#Cinnamon Bark Powder</strong></p>
<p>The use of cinnamon bark powder can help with insulin resistance and level management.In addition to easing gas and spasms, it helps with gastrointestinal problems. In addition to its insulin-like characteristics, which help lower blood glucose levels, it is believed to improve blood circulation.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>What are the benefits of using <a href="URL Botanicals Blood Balance</a>?</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> can help people improve their health and well-being by focusing on weight loss and reducing their blood sugar levels. We recommend Guardian Blood Balance for the following main reasons:</p>
<p><strong>Reducing Blood Pressure:</strong> This all-natural <a href="URL Botanicals Blood Balance</strong></a> can assist with blood pressure control. Scientific studies have shown the efficacy of the product, which is formulated with all-natural ingredients.</p>
<p><strong>Controlling Blood Sugar Levels:</strong> Controlling blood sugar levels is one of the primary uses for Guardian Botanicals' Blood Balance. This recipe can lessen the likelihood of developing Type 2 Diabetes and its complications by regulating blood sugar levels.</p>
<p><strong>Reduces Bad Cholesterol:</strong> Guardian Blood Balance's all-natural ingredients work to lower bad cholesterol levels.</p>
<p><strong>Increase Good Cholesterol:</strong> Guardian Blood Balance is a dietary supplement that aids in the elimination of harmful cholesterol while enhancing good cholesterol levels.</p>
<p><strong>Facilitates Weight Loss:</strong> An important part of maintaining weight reduction is controlling blood sugar. Losing weight, increasing energy, and decreasing cravings are all possible with the correct carbohydrate to fat ratio.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="350" border="0" data-original-height="276" data-original-width="506" /></a></div>
<h2><strong>Side Effects of using <a href="URL Botanicals Blood Balance</a><br /></strong></h2>
<p>Guardian Botanicals' Blood Balance Supplement is a pure solution made with the best ingredients. Side effects were rare for those who took the recommended dose. The product was made in an FDA-approved, GMP-certified manufacturing facility.</p>
<p>Each bottle of Blood Balance Supplement is free from any preservatives or herbicides, stimulants or other chemicals that could harm your health. It may take some time but the results you will get are real. <a href="URL Botanicals Blood Balance</strong></a> reviews have shown that the ingredients are completely natural and safe. Botanicals Blood Balance side effects are therefore minimal.</p>
<p>If you have any allergies or are taking medication, consult your doctor to ensure that you remain safe. The supplement is only for adults. Children should be avoided.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO: Get Guardian Botanicals Blood Balance at the Lowest Discounted Price Online</strong></a></span></h2>
<h2><strong><a href="URL Botanicals Blood Balance</a> Price & Where to Buy?</strong></h2>
<ul>
<li><strong>Buy one <a href="URL Botanicals Blood Balance</a> Supplement bottle for just $69.95</strong></li>
<li><strong>Buy two bottles of the <a href="URL Botanicals Blood Balance</a> Supplement and get a third bottle free, at $49.95 each.</strong></li>
<li><strong>Buy three bottles of the <a href="URL Botanicals Blood Balance</a> Supplement and get two more bottles free, at just $39.95 each.</strong></li>
</ul>
<p>These bottles contain inferior quality ingredients, which can be dangerous and could cause serious health problems. Only through the official website can you receive a 100% money-back guarantee. Click on the link below to order guardian botanicals blood balance supplement directly to the official site.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="640" height="422" border="0" data-original-height="422" data-original-width="639" /></a></div>
<h2><strong>Frequently Asked Question</strong></h2>
<p><strong>What does the Blood Balance Supplement do?</strong></p>
<p>The Blood Balance formula contains 100% natural ingredients which help to lower blood sugar, blood pressure, and bad cholesterol in a quick and effective manner.</p>
<p><strong>Is it safe to use?</strong></p>
<p>Blood Balance Supplement contains only natural, effective ingredients. This supplement was made in an FDA-approved, GMP-certified manufacturing facility. It is safe to use because it contains no harmful ingredients.</p>
<p><strong>How do I use Guardian Botanicals' blood balance?</strong></p>
<p>For easy swallowing, take 1 capsule of the Blood Balance supplement each day with a glass of water.</p>
<p><strong>Does this affect my medication?</strong></p>
<p>It is not necessary, but it is better to see a doctor.</p>
<p><strong>What happens if this doesn’t work?</strong></p>
<p>For 30 days, you get a 100% money-back guarantee. It is therefore risk-free.</p>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL PROMO[Limited Discount]: "Guardian Botanicals Blood Balance Australia"Official Website!</strong></a></span></h2>
<h2><strong>Final Verdict on <a href="URL Botanicals Blood Balance</a> Reviews</strong></h2>
<p><a href="URL Botanicals Blood Balance</strong></a> was a supplement that gained a reputation for its positive results. This formula contains only organic and safe ingredients, which work well to balance blood sugar and blood pressure.</p>
<p>The Blood Balance Supplement users who used it for 2 to 3 months saw a greater health condition.<a href="URL Guardian Botanicals Blood Balance</strong> </a>users have written reviews to share their experiences.</p>
<p>Some users claim they have lost excess fat and control their blood sugar and blood pressure. The recommended method of taking the Blood Balance capsules will allow you to see positive changes in your life.You get a 30-day guarantee of 100% satisfaction. If you are dissatisfied and cannot notice any changes, you can contact the customer service team to request a refund.If you are unsure, stop being sceptical and give the guardian the chance to prove you right.</p>
<div class="separator" style="clear: both; text-align: center;"><a style="margin-left: 1em; margin-right: 1em;" href="URL src="URL alt="" width="542" height="640" border="0" data-original-height="466" data-original-width="395" /></a></div>
<h2 style="text-align: center;"><span style="background-color: #ffcc99; color: #ff0000;"><a style="background-color: #ffcc99; color: #ff0000;" href="URL Details: *Guardian Botanicals Blood Balance* Read More Details on Official Website Australia!</strong></a></span></h2>
<h2># READ MORE INFO-</h2>
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p><span style="color: #ff0000;"><a href="URL/URL
<p> </p> | [
"# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] | [
"TAGS\n#region-us \n",
"# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] | [
6,
501
] | [
"passage: TAGS\n#region-us \n# READ MORE INFO-</h2>\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p><span style=\"color: #ff0000;\"><a href=\"URL/URL\n<p> </p>"
] |
06356f82d7ed156268d6a8710e79f093bf4035fe |
This is a small subset of the huge [histogram-comparisons-v1](https://huggingface.co/datasets/neoneye/histogram-comparisons-v1) dataset with 3M rows.
This dataset contains 150000 items in total. There are 3 curriculums each containing 50000 items.
Each item is a markdown document.
Each item contains between 2 and 6 image comparisons, with a `Summary` at the bottom.
The images are between 3x3 and 14x14.
The markdown document contains a `## Response`, that separates the prompt from the answer.
The structure of the markdown document with 3 comparisons: A, B, C.
```
# Histogram comparisons with summary
## Data A
### Data left
### Data right
## Data B
### Data left
### Data right
## Data C
### Data left
### Data right
## Response
## Compare A
## Compare B
## Compare C
## Summary
``` | neoneye/histogram-comparisons-small-v1 | [
"task_categories:image-to-text",
"size_categories:100K<n<1M",
"language:en",
"license:mit",
"region:us"
] | 2024-01-03T12:05:13+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["100K<n<1M"], "task_categories": ["image-to-text"]} | 2024-01-03T12:29:03+00:00 | [] | [
"en"
] | TAGS
#task_categories-image-to-text #size_categories-100K<n<1M #language-English #license-mit #region-us
|
This is a small subset of the huge histogram-comparisons-v1 dataset with 3M rows.
This dataset contains 150000 items in total. There are 3 curriculums each containing 50000 items.
Each item is a markdown document.
Each item contains between 2 and 6 image comparisons, with a 'Summary' at the bottom.
The images are between 3x3 and 14x14.
The markdown document contains a '## Response', that separates the prompt from the answer.
The structure of the markdown document with 3 comparisons: A, B, C.
| [
"## Response', that separates the prompt from the answer.\n\nThe structure of the markdown document with 3 comparisons: A, B, C."
] | [
"TAGS\n#task_categories-image-to-text #size_categories-100K<n<1M #language-English #license-mit #region-us \n",
"## Response', that separates the prompt from the answer.\n\nThe structure of the markdown document with 3 comparisons: A, B, C."
] | [
39,
31
] | [
"passage: TAGS\n#task_categories-image-to-text #size_categories-100K<n<1M #language-English #license-mit #region-us \n## Response', that separates the prompt from the answer.\n\nThe structure of the markdown document with 3 comparisons: A, B, C."
] |
ff569bc13ece453bde1446fd9d5a9bb79703a285 | # Dataset Card for "indic-copa"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | Thanmay/indic-copa | [
"region:us"
] | 2024-01-03T12:40:59+00:00 | {"dataset_info": {"features": [{"name": "premise", "dtype": "string"}, {"name": "choice1", "dtype": "string"}, {"name": "choice2", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "label", "dtype": "int32"}, {"name": "idx", "dtype": "int32"}, {"name": "changed", "dtype": "bool"}, {"name": "itv2 as premise", "dtype": "string"}, {"name": "itv2 as choice1", "dtype": "string"}, {"name": "itv2 as choice2", "dtype": "string"}, {"name": "itv2 bn premise", "dtype": "string"}, {"name": "itv2 bn choice1", "dtype": "string"}, {"name": "itv2 bn choice2", "dtype": "string"}, {"name": "itv2 gom premise", "dtype": "string"}, {"name": "itv2 gom choice1", "dtype": "string"}, {"name": "itv2 gom choice2", "dtype": "string"}, {"name": "itv2 kn premise", "dtype": "string"}, {"name": "itv2 kn choice1", "dtype": "string"}, {"name": "itv2 kn choice2", "dtype": "string"}, {"name": "itv2 mai premise", "dtype": "string"}, {"name": "itv2 mai choice1", "dtype": "string"}, {"name": "itv2 mai choice2", "dtype": "string"}, {"name": "itv2 ml premise", "dtype": "string"}, {"name": "itv2 ml choice1", "dtype": "string"}, {"name": "itv2 ml choice2", "dtype": "string"}, {"name": "itv2 ne premise", "dtype": "string"}, {"name": "itv2 ne choice1", "dtype": "string"}, {"name": "itv2 ne choice2", "dtype": "string"}, {"name": "itv2 or premise", "dtype": "string"}, {"name": "itv2 or choice1", "dtype": "string"}, {"name": "itv2 or choice2", "dtype": "string"}, {"name": "itv2 pa premise", "dtype": "string"}, {"name": "itv2 pa choice1", "dtype": "string"}, {"name": "itv2 pa choice2", "dtype": "string"}, {"name": "itv2 sa premise", "dtype": "string"}, {"name": "itv2 sa choice1", "dtype": "string"}, {"name": "itv2 sa choice2", "dtype": "string"}, {"name": "itv2 sat premise", "dtype": "string"}, {"name": "itv2 sat choice1", "dtype": "string"}, {"name": "itv2 sat choice2", "dtype": "string"}, {"name": "itv2 sd premise", "dtype": "string"}, {"name": "itv2 sd choice1", "dtype": "string"}, {"name": "itv2 sd choice2", "dtype": "string"}, {"name": "itv2 ta premise", "dtype": "string"}, {"name": "itv2 ta choice1", "dtype": "string"}, {"name": "itv2 ta choice2", "dtype": "string"}, {"name": "itv2 te premise", "dtype": "string"}, {"name": "itv2 te choice1", "dtype": "string"}, {"name": "itv2 te choice2", "dtype": "string"}, {"name": "itv2 ur premise", "dtype": "string"}, {"name": "itv2 ur choice1", "dtype": "string"}, {"name": "itv2 ur choice2", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 824417, "num_examples": 500}], "download_size": 595161, "dataset_size": 824417}} | 2024-01-03T12:41:55+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "indic-copa"
More Information needed | [
"# Dataset Card for \"indic-copa\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"indic-copa\"\n\nMore Information needed"
] | [
6,
15
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"indic-copa\"\n\nMore Information needed"
] |
559b7c542b6962ce4113cd6e6e687c788a7cebb7 | # Dataset Card for "indic-para"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ai4bharat/IndicXParaphrase-Translated | [
"region:us"
] | 2024-01-03T12:41:09+00:00 | {"dataset_info": {"features": [{"name": "english", "dtype": "string"}, {"name": "sentence1", "dtype": "string"}, {"name": "sentence2", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "0", "1": "1"}}}}, {"name": "itv2 as sentence1", "dtype": "string"}, {"name": "itv2 as sentence2", "dtype": "string"}, {"name": "itv2 bn sentence1", "dtype": "string"}, {"name": "itv2 bn sentence2", "dtype": "string"}, {"name": "itv2 gu sentence1", "dtype": "string"}, {"name": "itv2 gu sentence2", "dtype": "string"}, {"name": "itv2 hi sentence1", "dtype": "string"}, {"name": "itv2 hi sentence2", "dtype": "string"}, {"name": "itv2 kn sentence1", "dtype": "string"}, {"name": "itv2 kn sentence2", "dtype": "string"}, {"name": "itv2 ml sentence1", "dtype": "string"}, {"name": "itv2 ml sentence2", "dtype": "string"}, {"name": "itv2 mr sentence1", "dtype": "string"}, {"name": "itv2 mr sentence2", "dtype": "string"}, {"name": "itv2 or sentence1", "dtype": "string"}, {"name": "itv2 or sentence2", "dtype": "string"}, {"name": "itv2 pa sentence1", "dtype": "string"}, {"name": "itv2 pa sentence2", "dtype": "string"}, {"name": "itv2 te sentence1", "dtype": "string"}, {"name": "itv2 te sentence2", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 5457704, "num_examples": 2002}], "download_size": 2021259, "dataset_size": 5457704}} | 2024-01-03T12:42:25+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "indic-para"
More Information needed | [
"# Dataset Card for \"indic-para\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"indic-para\"\n\nMore Information needed"
] | [
6,
14
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"indic-para\"\n\nMore Information needed"
] |
2dd64373c66a077b37d580ab7f1d495fda42d05f | Dataset merged from a large variety of other sources.
See https://github.com/jondurbin/bagel for full set and code used to merge. | jondurbin/bagel-v0.3 | [
"license:cc-by-4.0",
"not-for-all-audiences",
"region:us"
] | 2024-01-03T12:58:57+00:00 | {"license": "cc-by-4.0", "tags": ["not-for-all-audiences"]} | 2024-01-06T16:29:53+00:00 | [] | [] | TAGS
#license-cc-by-4.0 #not-for-all-audiences #region-us
| Dataset merged from a large variety of other sources.
See URL for full set and code used to merge. | [] | [
"TAGS\n#license-cc-by-4.0 #not-for-all-audiences #region-us \n"
] | [
24
] | [
"passage: TAGS\n#license-cc-by-4.0 #not-for-all-audiences #region-us \n"
] |
b28d469c2de6bef280f276d9ff962b93041f541b | # Dataset Card for "indic-copa-hi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ai4bharat/IndicCOPA-Translated | [
"region:us"
] | 2024-01-03T13:05:32+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "premise", "dtype": "string"}, {"name": "choice1", "dtype": "string"}, {"name": "choice2", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "label", "dtype": "int32"}, {"name": "idx", "dtype": "int32"}, {"name": "changed", "dtype": "bool"}, {"name": "itv2 hi premise", "dtype": "string"}, {"name": "itv2 hi choice1", "dtype": "string"}, {"name": "itv2 hi choice2", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 158820, "num_examples": 449}], "download_size": 84132, "dataset_size": 158820}} | 2024-01-03T13:26:09+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "indic-copa-hi"
More Information needed | [
"# Dataset Card for \"indic-copa-hi\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"indic-copa-hi\"\n\nMore Information needed"
] | [
6,
17
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"indic-copa-hi\"\n\nMore Information needed"
] |
8d20d7ed099ffdac8da637fd1ce683f84cadf932 | # PIE Dataset Card for "scientific_papers"
This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the
[scientific_papers Huggingface dataset loading script](https://huggingface.co/datasets/scientific_papers).
## Data Schema
The document type for this dataset is `ScientificPapersDocument` which defines the following data fields:
- `text` (str)
and the following annotation layers:
- `abstract` (annotation type: `AbstractiveSummary`, target: `None`)
- `section_names` (annotation type: `SectionName`, targets: `None`)
| pie/scientific_papers | [
"region:us"
] | 2024-01-03T13:27:17+00:00 | {} | 2024-01-03T13:27:38+00:00 | [] | [] | TAGS
#region-us
| # PIE Dataset Card for "scientific_papers"
This is a PyTorch-IE wrapper for the
scientific_papers Huggingface dataset loading script.
## Data Schema
The document type for this dataset is 'ScientificPapersDocument' which defines the following data fields:
- 'text' (str)
and the following annotation layers:
- 'abstract' (annotation type: 'AbstractiveSummary', target: 'None')
- 'section_names' (annotation type: 'SectionName', targets: 'None')
| [
"# PIE Dataset Card for \"scientific_papers\"\n\nThis is a PyTorch-IE wrapper for the\nscientific_papers Huggingface dataset loading script.",
"## Data Schema\n\nThe document type for this dataset is 'ScientificPapersDocument' which defines the following data fields:\n\n- 'text' (str)\n\nand the following annotation layers:\n\n- 'abstract' (annotation type: 'AbstractiveSummary', target: 'None')\n- 'section_names' (annotation type: 'SectionName', targets: 'None')"
] | [
"TAGS\n#region-us \n",
"# PIE Dataset Card for \"scientific_papers\"\n\nThis is a PyTorch-IE wrapper for the\nscientific_papers Huggingface dataset loading script.",
"## Data Schema\n\nThe document type for this dataset is 'ScientificPapersDocument' which defines the following data fields:\n\n- 'text' (str)\n\nand the following annotation layers:\n\n- 'abstract' (annotation type: 'AbstractiveSummary', target: 'None')\n- 'section_names' (annotation type: 'SectionName', targets: 'None')"
] | [
6,
40,
98
] | [
"passage: TAGS\n#region-us \n# PIE Dataset Card for \"scientific_papers\"\n\nThis is a PyTorch-IE wrapper for the\nscientific_papers Huggingface dataset loading script.## Data Schema\n\nThe document type for this dataset is 'ScientificPapersDocument' which defines the following data fields:\n\n- 'text' (str)\n\nand the following annotation layers:\n\n- 'abstract' (annotation type: 'AbstractiveSummary', target: 'None')\n- 'section_names' (annotation type: 'SectionName', targets: 'None')"
] |
7c9d4ec30338c6ca292cb4d97e357c64d54a6af9 |
# 💬 MT-Bench-ZH
👻 [GitHub](https://github.com/GeneZC/MiniMA/tree/main/mt_bench_zh)
## 🎯 Motivation
MiniChat-1/1.5/2-3B are all instruction-following language models that could handle Chinese instructions, however, there is currently no instruciton-following benchamrk specialized for Chinese. Due to this, our previous evaluation has been limited to English-only benchmarks (i.e., AlpacaEval and MT-Bench).
To this demand, MT-Bench-ZH is made to mitigate this. MT-Bench-ZH is basically translated from MT-Bench-ZH by GPT-4 and further checked by human. Hopefully, MT-Bench-ZH could help the communnity to develop better instruction-following language models that are able to tackle Chinese instructions.
## 🚀 Quick Start
> [!NOTE]
> The code is either copied or modified from [FastChat](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge), yet we currently only support `single` mode judgment.
> Please refer to FastChat for more details.
### Install FastChat
```bash
git clone https://github.com/lm-sys/FastChat.git
cd FastChat
pip install -e ".[model_worker,webui]"
```
### Generate Responses
```bash
python gen_model_answer.py --model-path GeneZC/MiniChat-2-3B --model-id minichat --bench-name mt_bench_zh --max-new-token 1536
```
### Evaluate Responses
```bash
export OPENAI_API_KEY=XXXXXX # Set the OpenAI API key.
python gen_judgment.py --model-list minichat --bench-name mt_bench_zh --judge-file data/judge_prompts_zh.jsonl --parallel 4
```
### Display Results
```bash
python show_result.py --bench-name mt_bench_zh
```
## 🏆 Leaderboard
|Method|MT-Bench-ZH|
|--|--|
|🥇 GPT-4|8.96|
|🥈 Zephyr-7B-Beta|6.27<sup>#</sup>|
|🥉 Qwen-Chat-7B|6.24|
|MiniChat-2-3B|6.04|
|Qwen-Chat-1.8B|5.65|
|LLaMA-2-Chat-7B|5.43<sup>#</sup>|
|Vicuna-7B|5.22<sup>#</sup>|
|StableLM-Zephyr-3B|4.31<sup>#</sup>|
|Rocket-3B|4.07<sup>#</sup>|
|Phi-2-DPO|1.59<sup>#</sup><sup>$</sup>|
<sup>#</sup> specialized mainly for English.
<sup>$</sup> finetuned without multi-turn instruction data.
## 🙌 Contributions
You can raise questions related to the benchmark by opening an issue. Or you can add results of other models to the leaderboard by opening a pull request. For the leaderboard, related files should be attached for sanity check (i.e., a separate model response file should be uploaded, and the GPT-4 judgement file should be updated). | GeneZC/MT-Bench-ZH | [
"task_categories:text-generation",
"task_categories:conversational",
"size_categories:n<1K",
"language:zh",
"license:apache-2.0",
"region:us"
] | 2024-01-03T13:49:12+00:00 | {"language": ["zh"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["text-generation", "conversational"]} | 2024-01-03T14:06:09+00:00 | [] | [
"zh"
] | TAGS
#task_categories-text-generation #task_categories-conversational #size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us
| MT-Bench-ZH
===========
GitHub
Motivation
----------
MiniChat-1/1.5/2-3B are all instruction-following language models that could handle Chinese instructions, however, there is currently no instruciton-following benchamrk specialized for Chinese. Due to this, our previous evaluation has been limited to English-only benchmarks (i.e., AlpacaEval and MT-Bench).
To this demand, MT-Bench-ZH is made to mitigate this. MT-Bench-ZH is basically translated from MT-Bench-ZH by GPT-4 and further checked by human. Hopefully, MT-Bench-ZH could help the communnity to develop better instruction-following language models that are able to tackle Chinese instructions.
Quick Start
-----------
>
> [!NOTE]
>
> The code is either copied or modified from FastChat, yet we currently only support 'single' mode judgment.
> Please refer to FastChat for more details.
>
>
>
### Install FastChat
### Generate Responses
### Evaluate Responses
### Display Results
Leaderboard
-----------
# specialized mainly for English.
$ finetuned without multi-turn instruction data.
Contributions
-------------
You can raise questions related to the benchmark by opening an issue. Or you can add results of other models to the leaderboard by opening a pull request. For the leaderboard, related files should be attached for sanity check (i.e., a separate model response file should be uploaded, and the GPT-4 judgement file should be updated).
| [
"### Install FastChat",
"### Generate Responses",
"### Evaluate Responses",
"### Display Results\n\n\nLeaderboard\n-----------",
"# specialized mainly for English.\n\n\n$ finetuned without multi-turn instruction data.\n\n\nContributions\n-------------\n\n\nYou can raise questions related to the benchmark by opening an issue. Or you can add results of other models to the leaderboard by opening a pull request. For the leaderboard, related files should be attached for sanity check (i.e., a separate model response file should be uploaded, and the GPT-4 judgement file should be updated)."
] | [
"TAGS\n#task_categories-text-generation #task_categories-conversational #size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us \n",
"### Install FastChat",
"### Generate Responses",
"### Evaluate Responses",
"### Display Results\n\n\nLeaderboard\n-----------",
"# specialized mainly for English.\n\n\n$ finetuned without multi-turn instruction data.\n\n\nContributions\n-------------\n\n\nYou can raise questions related to the benchmark by opening an issue. Or you can add results of other models to the leaderboard by opening a pull request. For the leaderboard, related files should be attached for sanity check (i.e., a separate model response file should be uploaded, and the GPT-4 judgement file should be updated)."
] | [
50,
5,
6,
6,
8,
99
] | [
"passage: TAGS\n#task_categories-text-generation #task_categories-conversational #size_categories-n<1K #language-Chinese #license-apache-2.0 #region-us \n### Install FastChat### Generate Responses### Evaluate Responses### Display Results\n\n\nLeaderboard\n-----------# specialized mainly for English.\n\n\n$ finetuned without multi-turn instruction data.\n\n\nContributions\n-------------\n\n\nYou can raise questions related to the benchmark by opening an issue. Or you can add results of other models to the leaderboard by opening a pull request. For the leaderboard, related files should be attached for sanity check (i.e., a separate model response file should be uploaded, and the GPT-4 judgement file should be updated)."
] |
a6d917e2a625b08f147a11ecd6a58862b5c86721 |
This dataset includes chess games played in the Chess.com "Titled Tuesday" events from July 2022 to December 2023. The games in the dataset were played by titled players
who ranked 1-25 in at least one tournament. Since game documents are organized around players and there are duplicate games, the dataset is more suitable for the player-centric analyses.
This [GitHub repository](https://github.com/golkir/titled-tuesday-chess-statistical-analysis.git) contains scripts for scraping the data from Chess.com
website and API as well some demos of statistical analysis of the data. Feel free to modify a data retrieval script to create new datasets
with the latest chess tournaments. | kirillgoltsman/titled-tuesday-chess-games | [
"license:apache-2.0",
"region:us"
] | 2024-01-03T14:01:57+00:00 | {"license": "apache-2.0"} | 2024-01-03T14:23:48+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
|
This dataset includes chess games played in the URL "Titled Tuesday" events from July 2022 to December 2023. The games in the dataset were played by titled players
who ranked 1-25 in at least one tournament. Since game documents are organized around players and there are duplicate games, the dataset is more suitable for the player-centric analyses.
This GitHub repository contains scripts for scraping the data from URL
website and API as well some demos of statistical analysis of the data. Feel free to modify a data retrieval script to create new datasets
with the latest chess tournaments. | [] | [
"TAGS\n#license-apache-2.0 #region-us \n"
] | [
14
] | [
"passage: TAGS\n#license-apache-2.0 #region-us \n"
] |
94e217322d1917ea9021d820a42f02bad8e03ab1 | # Dataset Card for "full_sft_chat_data_filtered"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | haisonle001/full_sft_chat_data_filtered | [
"region:us"
] | 2024-01-03T14:21:56+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train_sft", "path": "data/train_sft-*"}]}], "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "prompt_id", "dtype": "string"}, {"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "train_sft", "num_bytes": 9896156471.291824, "num_examples": 5302051}], "download_size": 5179913073, "dataset_size": 9896156471.291824}} | 2024-01-03T14:31:15+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "full_sft_chat_data_filtered"
More Information needed | [
"# Dataset Card for \"full_sft_chat_data_filtered\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"full_sft_chat_data_filtered\"\n\nMore Information needed"
] | [
6,
21
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"full_sft_chat_data_filtered\"\n\nMore Information needed"
] |
536d928010df1457f9312f079add9df0b0011521 | "LLM-SAP: Large Language Model Situational Awareness Based Planning"
Paper: https://arxiv.org/abs/2312.16127
Github: https://github.com/HanyangZhong/Situational_Planning_datasets
This image collection has been sourced from the internet and is intended solely for research purposes.
We have made every effort to respect copyright and intellectual property rights.
However, if you believe that any content in this collection infringes upon your rights or violates any copyright laws, please do not hesitate to contact us.
We are committed to addressing such concerns promptly and will remove any infringing material as requested. | baoji/Household_safety | [
"license:mit",
"arxiv:2312.16127",
"region:us"
] | 2024-01-03T14:27:12+00:00 | {"license": "mit"} | 2024-01-03T14:34:07+00:00 | [
"2312.16127"
] | [] | TAGS
#license-mit #arxiv-2312.16127 #region-us
| "LLM-SAP: Large Language Model Situational Awareness Based Planning"
Paper: URL
Github: URL
This image collection has been sourced from the internet and is intended solely for research purposes.
We have made every effort to respect copyright and intellectual property rights.
However, if you believe that any content in this collection infringes upon your rights or violates any copyright laws, please do not hesitate to contact us.
We are committed to addressing such concerns promptly and will remove any infringing material as requested. | [] | [
"TAGS\n#license-mit #arxiv-2312.16127 #region-us \n"
] | [
20
] | [
"passage: TAGS\n#license-mit #arxiv-2312.16127 #region-us \n"
] |
0031d673c96139670f3587872d7203f45c321238 | ## Dataset Description
- **Homepage** [Projecte AINA](https://projecteaina.cat/tech/)
- **Repository** [HuggingFace](https://huggingface.co/projecte-aina)
- **Paper** [N/A]
- **Point of Contact** [email protected]
### Dataset Summary
PureInstructQA is a multilingual question answering instructional dataset merging different collections' question/answer/context triplets for optimised training of LLMs for RAG applications.
It contains extractive, abstractive and open_qa instances, as we'll as AI generated Q/A instances.
### Supported Tasks and Leaderboards
- `Question Answering`
### Languages
This dataset is in Catalan, Spanish and English.
| Dataset | Instruction | Language |
|-------------------------|-----------:|-----:|
| catalanqa | 21427 | ca |
| squad| 20000 | en |
| sqac |15036 | es |
| dolly databricks| 7706 | en |
| CoQCat | 6000 | ca |
| mentor_ca | 5250| ca |
| mentor_es | 5250 | es |
| mixtral-8x7b-generated | 1870 |ca |
Total QA instructions: 82,539
Train #: 74,285
Validation #: 8,254
Total CA: 34,547
Total ES: 20,286
Total EN: 27.706
### Data Instances
Two JSONL files, one for each split.
An example of 'train' looks as follows:
```
{"id": "catalanqa_0.5456779777299726",
"instruction": "Per què es travessat Corradino?",
"context": "Matilde di Shabran és principalment una òpera de conjunts, amb només algunes àries -cap per al tenor que té la part més difícil. La peça més notable de l'òpera és el quintet de tretze minuts del primer acte. Representa el moment en què Corradino, que té a les dones com a gran enemic, en gran sorpresa i desconcert és travessat fins a la medul·la per la fletxa de Cupido. Aquesta és la part més lenta. La segona meitat és ràpida i retrata les emocions conflictives del tenor durant l'agitació interior que l'envolta. Els altres cantants comenten amb diversió la situació. Tot això és un tour de force que només un dels més grans compositors d'òpera podia aconseguir.",
"response": "per la fletxa de Cupido",
"category": "qa"}
```
### Acknowledgments
This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the [project ILENIA](https://proyectoilenia.es/) with reference 2022/TL22/00215337, 2022/TL22/00215336, 2022/TL22/00215335 y 2022/TL22/00215334
| projecte-aina/PureInstructQA | [
"language:ca",
"language:en",
"language:es",
"license:cc-by-sa-4.0",
"region:us"
] | 2024-01-03T15:14:07+00:00 | {"language": ["ca", "en", "es"], "license": ["cc-by-sa-4.0"], "pretty_name": "PureInstructQA"} | 2024-02-11T14:18:10+00:00 | [] | [
"ca",
"en",
"es"
] | TAGS
#language-Catalan #language-English #language-Spanish #license-cc-by-sa-4.0 #region-us
| Dataset Description
-------------------
* Homepage Projecte AINA
* Repository HuggingFace
* Paper [N/A]
* Point of Contact langtech@URL
### Dataset Summary
PureInstructQA is a multilingual question answering instructional dataset merging different collections' question/answer/context triplets for optimised training of LLMs for RAG applications.
It contains extractive, abstractive and open\_qa instances, as we'll as AI generated Q/A instances.
### Supported Tasks and Leaderboards
* 'Question Answering'
### Languages
This dataset is in Catalan, Spanish and English.
Total QA instructions: 82,539
Train #: 74,285
Validation #: 8,254
Total CA: 34,547
Total ES: 20,286
Total EN: 27.706
### Data Instances
Two JSONL files, one for each split.
An example of 'train' looks as follows:
### Acknowledgments
This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337, 2022/TL22/00215336, 2022/TL22/00215335 y 2022/TL22/00215334
| [
"### Dataset Summary\n\n\nPureInstructQA is a multilingual question answering instructional dataset merging different collections' question/answer/context triplets for optimised training of LLMs for RAG applications.\nIt contains extractive, abstractive and open\\_qa instances, as we'll as AI generated Q/A instances.",
"### Supported Tasks and Leaderboards\n\n\n* 'Question Answering'",
"### Languages\n\n\nThis dataset is in Catalan, Spanish and English.\n\n\n\nTotal QA instructions: 82,539\n\n\nTrain #: 74,285\n\n\nValidation #: 8,254\n\n\nTotal CA: 34,547\n\n\nTotal ES: 20,286\n\n\nTotal EN: 27.706",
"### Data Instances\n\n\nTwo JSONL files, one for each split.\n\n\nAn example of 'train' looks as follows:",
"### Acknowledgments\n\n\nThis work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337, 2022/TL22/00215336, 2022/TL22/00215335 y 2022/TL22/00215334"
] | [
"TAGS\n#language-Catalan #language-English #language-Spanish #license-cc-by-sa-4.0 #region-us \n",
"### Dataset Summary\n\n\nPureInstructQA is a multilingual question answering instructional dataset merging different collections' question/answer/context triplets for optimised training of LLMs for RAG applications.\nIt contains extractive, abstractive and open\\_qa instances, as we'll as AI generated Q/A instances.",
"### Supported Tasks and Leaderboards\n\n\n* 'Question Answering'",
"### Languages\n\n\nThis dataset is in Catalan, Spanish and English.\n\n\n\nTotal QA instructions: 82,539\n\n\nTrain #: 74,285\n\n\nValidation #: 8,254\n\n\nTotal CA: 34,547\n\n\nTotal ES: 20,286\n\n\nTotal EN: 27.706",
"### Data Instances\n\n\nTwo JSONL files, one for each split.\n\n\nAn example of 'train' looks as follows:",
"### Acknowledgments\n\n\nThis work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337, 2022/TL22/00215336, 2022/TL22/00215335 y 2022/TL22/00215334"
] | [
31,
81,
17,
57,
29,
81
] | [
"passage: TAGS\n#language-Catalan #language-English #language-Spanish #license-cc-by-sa-4.0 #region-us \n### Dataset Summary\n\n\nPureInstructQA is a multilingual question answering instructional dataset merging different collections' question/answer/context triplets for optimised training of LLMs for RAG applications.\nIt contains extractive, abstractive and open\\_qa instances, as we'll as AI generated Q/A instances.### Supported Tasks and Leaderboards\n\n\n* 'Question Answering'### Languages\n\n\nThis dataset is in Catalan, Spanish and English.\n\n\n\nTotal QA instructions: 82,539\n\n\nTrain #: 74,285\n\n\nValidation #: 8,254\n\n\nTotal CA: 34,547\n\n\nTotal ES: 20,286\n\n\nTotal EN: 27.706### Data Instances\n\n\nTwo JSONL files, one for each split.\n\n\nAn example of 'train' looks as follows:### Acknowledgments\n\n\nThis work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337, 2022/TL22/00215336, 2022/TL22/00215335 y 2022/TL22/00215334"
] |
6140b2e0ecc5cdcaa9394f08eefaa4fe1db2ab72 | # Dataset Card for "camel-verified-it"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | mii-llm/camel-verified-it | [
"region:us"
] | 2024-01-03T15:22:37+00:00 | {"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 361707, "num_examples": 126}], "download_size": 189080, "dataset_size": 361707}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-04T00:23:54+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "camel-verified-it"
More Information needed | [
"# Dataset Card for \"camel-verified-it\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"camel-verified-it\"\n\nMore Information needed"
] | [
6,
17
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"camel-verified-it\"\n\nMore Information needed"
] |
e5a58e6c81320bdbbd242c740309076c92ecf1cf | # Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | salam123/depression123 | [
"license:apache-2.0",
"region:us"
] | 2024-01-03T15:26:18+00:00 | {"license": "apache-2.0"} | 2024-01-03T15:51:40+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| # Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
## Dataset Details
### Dataset Description
- Curated by:
- Funded by [optional]:
- Shared by [optional]:
- Language(s) (NLP):
- License:
### Dataset Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
### Out-of-Scope Use
## Dataset Structure
## Dataset Creation
### Curation Rationale
### Source Data
#### Data Collection and Processing
#### Who are the source data producers?
### Annotations [optional]
#### Annotation process
#### Who are the annotators?
#### Personal and Sensitive Information
## Bias, Risks, and Limitations
### Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
[optional]
BibTeX:
APA:
## Glossary [optional]
## More Information [optional]
## Dataset Card Authors [optional]
## Dataset Card Contact
| [
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
"TAGS\n#license-apache-2.0 #region-us \n",
"# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"## Dataset Details",
"### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:",
"### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:",
"## Uses",
"### Direct Use",
"### Out-of-Scope Use",
"## Dataset Structure",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Data Collection and Processing",
"#### Who are the source data producers?",
"### Annotations [optional]",
"#### Annotation process",
"#### Who are the annotators?",
"#### Personal and Sensitive Information",
"## Bias, Risks, and Limitations",
"### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:",
"## Glossary [optional]",
"## More Information [optional]",
"## Dataset Card Authors [optional]",
"## Dataset Card Contact"
] | [
14,
34,
4,
40,
29,
3,
4,
9,
6,
5,
7,
4,
7,
10,
9,
5,
9,
8,
10,
46,
8,
7,
10,
5
] | [
"passage: TAGS\n#license-apache-2.0 #region-us \n# Dataset Card for Dataset Name\n\n\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.## Dataset Details### Dataset Description\n\n\n\n\n\n- Curated by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Language(s) (NLP): \n- License:### Dataset Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:## Uses### Direct Use### Out-of-Scope Use## Dataset Structure## Dataset Creation### Curation Rationale### Source Data#### Data Collection and Processing#### Who are the source data producers?### Annotations [optional]#### Annotation process#### Who are the annotators?#### Personal and Sensitive Information## Bias, Risks, and Limitations### Recommendations\n\n\n\nUsers should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.\n\n[optional]\n\n\n\nBibTeX:\n\n\n\nAPA:## Glossary [optional]## More Information [optional]## Dataset Card Authors [optional]## Dataset Card Contact"
] |
1bf16fb7af53054f0fb063626471a36ad2b01db7 | # Dataset Card for "ELLSWORTH-KELLY-ART"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | iamkaikai/ELLSWORTH-KELLY-ART | [
"region:us"
] | 2024-01-03T15:58:11+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 3070109.0, "num_examples": 196}], "download_size": 2831838, "dataset_size": 3070109.0}} | 2024-01-03T15:58:13+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ELLSWORTH-KELLY-ART"
More Information needed | [
"# Dataset Card for \"ELLSWORTH-KELLY-ART\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"ELLSWORTH-KELLY-ART\"\n\nMore Information needed"
] | [
6,
19
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"ELLSWORTH-KELLY-ART\"\n\nMore Information needed"
] |
037fce473440dbada4fa8b74633fe7c0ed88c73a | # Dataset Card for "es-0103-stop-no-demoji-no-hasthag-l"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | gg-ai/es-0103-stop-no-demoji-no-hasthag-l | [
"region:us"
] | 2024-01-03T16:35:44+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}, {"split": "val", "path": "data/val-*"}]}], "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "clean_text", "dtype": "string"}, {"name": "sent", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 10604987, "num_examples": 28854}, {"name": "test", "num_bytes": 2174343, "num_examples": 6131}, {"name": "val", "num_bytes": 370030, "num_examples": 1082}], "download_size": 8223549, "dataset_size": 13149360}} | 2024-01-03T16:35:55+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "es-0103-stop-no-demoji-no-hasthag-l"
More Information needed | [
"# Dataset Card for \"es-0103-stop-no-demoji-no-hasthag-l\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"es-0103-stop-no-demoji-no-hasthag-l\"\n\nMore Information needed"
] | [
6,
28
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"es-0103-stop-no-demoji-no-hasthag-l\"\n\nMore Information needed"
] |
085554e1e155611bfcd4d63c359d3722cd5b8c7c |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1395
- F1: 0.8649
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2581 | 1.0 | 525 | 0.1630 | 0.8198 |
| 0.1281 | 2.0 | 1050 | 0.1379 | 0.8496 |
| 0.0781 | 3.0 | 1575 | 0.1395 | 0.8649 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
| Aldroide/xlm-roberta-base-finetuned-panx-de | [
"license:mit",
"generated_from_trainer",
"region:us"
] | 2024-01-03T16:37:53+00:00 | {"license": "mit", "base_model": "xlm-roberta-base", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"name": "Token Classification", "type": "token-classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "config": "PAN-X.de", "split": "validation", "args": "PAN-X.de"}, "metrics": [{"name": "F1", "type": "f1", "value": 0.8649324094058843}]}]}]} | 2024-01-03T17:29:10+00:00 | [] | [] | TAGS
#license-mit #generated_from_trainer #region-us
| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1395
* F1: 0.8649
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following hyperparameters were used during training:
* learning\_rate: 5e-05
* train\_batch\_size: 24
* eval\_batch\_size: 24
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
### Training results
### Framework versions
* Transformers 4.35.2
* Pytorch 2.1.0+cu118
* Datasets 2.15.0
* Tokenizers 0.15.0
| [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu118\n* Datasets 2.15.0\n* Tokenizers 0.15.0"
] | [
"TAGS\n#license-mit #generated_from_trainer #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training results",
"### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu118\n* Datasets 2.15.0\n* Tokenizers 0.15.0"
] | [
18,
98,
4,
33
] | [
"passage: TAGS\n#license-mit #generated_from_trainer #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3### Training results### Framework versions\n\n\n* Transformers 4.35.2\n* Pytorch 2.1.0+cu118\n* Datasets 2.15.0\n* Tokenizers 0.15.0"
] |
135e6df072339dfe1e6b88a491d9f6832c75a811 |
This is a test dataset used in the `datasets` library CI | datasets-maintainers/dataset-with-standalone-yaml | [
"license:apache-2.0",
"test",
"region:us"
] | 2024-01-03T16:55:36+00:00 | {"license": "apache-2.0", "tags": ["should-be-overwritten-by-standalone-yaml"]} | 2024-01-03T17:21:03+00:00 | [] | [] | TAGS
#license-apache-2.0 #test #region-us
|
This is a test dataset used in the 'datasets' library CI | [] | [
"TAGS\n#license-apache-2.0 #test #region-us \n"
] | [
16
] | [
"passage: TAGS\n#license-apache-2.0 #test #region-us \n"
] |
47482a8aa4951a36f47c44afb33cc491ae4f45c9 | # AstroClassification and Redshifts Pretraining Dataset
<!-- Provide a quick summary of the dataset. -->
This dataset was used in the masked autoencoding pretraining step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
- **Repository:** https://github.com/helenqu/connect-later
- **Paper:** will be updated
- **Point of Contact: Helen Qu (<[email protected]>)**
## Dataset Loading
The `load_dataset` HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the `run_pretrain.sh` script in the Connect Later repository. | helenqu/astro-classification-redshifts-pretrain | [
"license:mit",
"region:us"
] | 2024-01-03T17:22:06+00:00 | {"license": "mit"} | 2024-01-03T17:44:01+00:00 | [] | [] | TAGS
#license-mit #region-us
| # AstroClassification and Redshifts Pretraining Dataset
This dataset was used in the masked autoencoding pretraining step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
- Repository: URL
- Paper: will be updated
- Point of Contact: Helen Qu (<helenqu@URL>)
## Dataset Loading
The 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_pretrain.sh' script in the Connect Later repository. | [
"# AstroClassification and Redshifts Pretraining Dataset\n\n\n\nThis dataset was used in the masked autoencoding pretraining step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)",
"## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_pretrain.sh' script in the Connect Later repository."
] | [
"TAGS\n#license-mit #region-us \n",
"# AstroClassification and Redshifts Pretraining Dataset\n\n\n\nThis dataset was used in the masked autoencoding pretraining step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)",
"## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_pretrain.sh' script in the Connect Later repository."
] | [
11,
157,
67
] | [
"passage: TAGS\n#license-mit #region-us \n# AstroClassification and Redshifts Pretraining Dataset\n\n\n\nThis dataset was used in the masked autoencoding pretraining step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei), and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_pretrain.sh' script in the Connect Later repository."
] |
197e62f3066b7e502c1cc7738666f9e9e78213ec | 1 | Wha123/test | [
"region:us"
] | 2024-01-03T17:24:16+00:00 | {} | 2024-01-03T17:26:10+00:00 | [] | [] | TAGS
#region-us
| 1 | [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
83cd50052e3363b835cbbab240ececaceb45711f | This is dataset contains 1,673 Faroese-to-English parallel sentences generated by GPT-4. The Faroese text is blog text from the Basic Language Resource Kit for Faroese 1.0 text corpus.
In addition to the parallel sentences, the dataset contains a column with a quality report made by GPT-4 in which it describes the challenges it faced when translating the each article.
Please be aware, that according to OpenAI's the terms of use, then it is not allowed to use their output to create models that compete with their services.
---
license: mit
---
| AnnikaSimonsen/GPT-4_FO-EN_parallel_blog_sentences | [
"region:us"
] | 2024-01-03T17:35:23+00:00 | {} | 2024-01-03T17:58:29+00:00 | [] | [] | TAGS
#region-us
| This is dataset contains 1,673 Faroese-to-English parallel sentences generated by GPT-4. The Faroese text is blog text from the Basic Language Resource Kit for Faroese 1.0 text corpus.
In addition to the parallel sentences, the dataset contains a column with a quality report made by GPT-4 in which it describes the challenges it faced when translating the each article.
Please be aware, that according to OpenAI's the terms of use, then it is not allowed to use their output to create models that compete with their services.
---
license: mit
---
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
c8a783a19b7e14bf31a0c40b5bce757e8c2c987e | ##MedQA Ethics
This dataset is an amalgam of two:
- yc4142/ethics-CoT
- keivalya/MedQuad-MedicalQnADataset
...with a smattering of something close to this, but uncensored:
- nRuaif/wizard_alpaca_dolly_orca
Reasoning is thus:
- Medical datasets must be closely tied to ethics, from inception.
- Wiz/Dol/Paca/Orc lends abstract reasoning, another important aspect of a medical model - without reason, the contents are drier and less relatable.
- With the size of datasets for q/a and reason shrinking, it probably can be refined quite a bit
- Medical models must take into account tree of thought processing - nowhere is it worse to have an incorrect response than medical advice or diagnosis
| jtatman/medquad-medicalqa-wizdolalpaca-instruct | [
"region:us"
] | 2024-01-03T17:37:00+00:00 | {"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "instruction", "dtype": "string"}, {"name": "output", "dtype": "string"}, {"name": "system", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 76066911.30719037, "num_examples": 48452}], "download_size": 38181130, "dataset_size": 76066911.30719037}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-04T09:51:58+00:00 | [] | [] | TAGS
#region-us
| ##MedQA Ethics
This dataset is an amalgam of two:
- yc4142/ethics-CoT
- keivalya/MedQuad-MedicalQnADataset
...with a smattering of something close to this, but uncensored:
- nRuaif/wizard_alpaca_dolly_orca
Reasoning is thus:
- Medical datasets must be closely tied to ethics, from inception.
- Wiz/Dol/Paca/Orc lends abstract reasoning, another important aspect of a medical model - without reason, the contents are drier and less relatable.
- With the size of datasets for q/a and reason shrinking, it probably can be refined quite a bit
- Medical models must take into account tree of thought processing - nowhere is it worse to have an incorrect response than medical advice or diagnosis
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
5e122c8e84cdccc4bafdff9d9c1799a308c8b6ea | # AstroClassification and Redshifts Augmented Dataset
<!-- Provide a quick summary of the dataset. -->
This dataset was used in the fine-tuning with targeted augmentations step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei) augmented with the _redshifting_ targeted augmentation, and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
- **Repository:** https://github.com/helenqu/connect-later
- **Paper:** will be updated
- **Point of Contact: Helen Qu (<[email protected]>)**
## Dataset Loading
The `load_dataset` HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the `run_finetuning.sh` script in the Connect Later repository. | helenqu/astro-classification-redshifts-augmented | [
"license:mit",
"region:us"
] | 2024-01-03T17:50:29+00:00 | {"license": "mit"} | 2024-01-03T18:04:57+00:00 | [] | [] | TAGS
#license-mit #region-us
| # AstroClassification and Redshifts Augmented Dataset
This dataset was used in the fine-tuning with targeted augmentations step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei) augmented with the _redshifting_ targeted augmentation, and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).
- Repository: URL
- Paper: will be updated
- Point of Contact: Helen Qu (<helenqu@URL>)
## Dataset Loading
The 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_finetuning.sh' script in the Connect Later repository. | [
"# AstroClassification and Redshifts Augmented Dataset\n\n\n\nThis dataset was used in the fine-tuning with targeted augmentations step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei) augmented with the _redshifting_ targeted augmentation, and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)",
"## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_finetuning.sh' script in the Connect Later repository."
] | [
"TAGS\n#license-mit #region-us \n",
"# AstroClassification and Redshifts Augmented Dataset\n\n\n\nThis dataset was used in the fine-tuning with targeted augmentations step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei) augmented with the _redshifting_ targeted augmentation, and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)",
"## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_finetuning.sh' script in the Connect Later repository."
] | [
11,
177,
68
] | [
"passage: TAGS\n#license-mit #region-us \n# AstroClassification and Redshifts Augmented Dataset\n\n\n\nThis dataset was used in the fine-tuning with targeted augmentations step for the AstroClassification and Redshifts tasks introduced in [Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations](). This is a dataset of simulated astronomical time-series (e.g., supernovae, active galactic nuclei) augmented with the _redshifting_ targeted augmentation, and the task is to classify the object type (AstroClassification) or predict the object's redshift (Redshifts).\n\n- Repository: URL\n- Paper: will be updated\n- Point of Contact: Helen Qu (<helenqu@URL>)## Dataset Loading\nThe 'load_dataset' HuggingFace dataset loading syntax will use the custom dataset loading script included in this repository to load this dataset in the expected format for pretraining with the 'run_finetuning.sh' script in the Connect Later repository."
] |
f05d7cdd9a4a0ae594ca6e5a59e25eca0aab27ab | This is dataset contains 3,735 Faroese-to-English parallel sentences generated by GPT-4. The Faroese text is news text from the Basic Language Resource Kit for Faroese 1.0 text corpus.
In addition to the parallel sentences, the dataset contains a column with a quality report made by GPT-4 in which it describes the challenges it faced when translating the each article.
Please be aware, that according to OpenAI's the terms of use, then it is not allowed to use their output to create models that compete with their services.
---
license: mit
---
| AnnikaSimonsen/GPT-4_FO-EN_parallel_news_sentences | [
"region:us"
] | 2024-01-03T17:53:02+00:00 | {} | 2024-01-03T17:58:09+00:00 | [] | [] | TAGS
#region-us
| This is dataset contains 3,735 Faroese-to-English parallel sentences generated by GPT-4. The Faroese text is news text from the Basic Language Resource Kit for Faroese 1.0 text corpus.
In addition to the parallel sentences, the dataset contains a column with a quality report made by GPT-4 in which it describes the challenges it faced when translating the each article.
Please be aware, that according to OpenAI's the terms of use, then it is not allowed to use their output to create models that compete with their services.
---
license: mit
---
| [] | [
"TAGS\n#region-us \n"
] | [
6
] | [
"passage: TAGS\n#region-us \n"
] |
f60bac46a542f4383d739e5350cd23c2dfba4455 | Translated with googletrans==3.1.0a0 from original dataset
*part of the data (up to 600) was lost during the translation
---
license: apache-2.0
--- | daqc/databricks-dolly-15k-es | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:es",
"license:apache-2.0",
"dolly",
"llm",
"databricks",
"text-generation",
"region:us"
] | 2024-01-03T18:13:28+00:00 | {"language": ["es"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-generation"], "tags": ["dolly", "llm", "databricks", "text-generation"]} | 2024-01-03T18:25:33+00:00 | [] | [
"es"
] | TAGS
#task_categories-text-generation #size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #dolly #llm #databricks #text-generation #region-us
| Translated with googletrans==3.1.0a0 from original dataset
*part of the data (up to 600) was lost during the translation
---
license: apache-2.0
--- | [] | [
"TAGS\n#task_categories-text-generation #size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #dolly #llm #databricks #text-generation #region-us \n"
] | [
57
] | [
"passage: TAGS\n#task_categories-text-generation #size_categories-10K<n<100K #language-Spanish #license-apache-2.0 #dolly #llm #databricks #text-generation #region-us \n"
] |
ab7b3542b9d3c55ce0f8847fed1a749f30623262 | Synthetic data designed as prompts for generating embeddings training data for retrieval.
The "iteration" column refers to how the data was generated.
Iteration 1: Use the following pool of seed tasks, prompt GPT-3.5-Turbo to generate additional tasks.
```python
RETRIEVAL_EXAMPLES = [
'Provide a scientific claim as query, retrieve documents that help verify or refute the claim.',
'Search for documents that answers a FAQ-style query on children\'s nutrition.',
"Retrieve company's financial reports for a given stock ticker symbol.",
"Given a book name as a query, retrieve reviews, ratings and summaries of that book.",
"Search for scientific research papers supporting a medical diagnosis for a specified disease.",
"Given a question, retrieve Wikipedia passages that answer the question.",
"Provided a user question, retrieve the highest voted answers on Reddit ELI5 forum.",
"Given a web search engine query, retrieve relevant passages that answer the query.",
"Find Amazon reviews similar to the input review.",
"Find the song lyrics most related to the user's search.",
"Given a multi-hop question, retrieve documents that can help answer the question.",
"Retrieve tweets that are semantically similar to the given tweet",
"Given a news summary, retrieve other semantically similar summaries",
"Given a question, retrieve relevant answers from Stackexchange",
"Given a scientific paper title, retrieve paper abstracts that are cited by the given paper."
]
```
Iteration 2: Use the ~40,000 tasks generated in Iteration 1 as seed tasks, prompt GPT-3.5-Turbo to generate additional tasks.
Iteration 3: Use the ~80,000 tasks generated in Iterations 1-2 as seed tasks, prompt GPT-4-Turbo to generate additional tasks. | andersonbcdefg/synthetic_retrieval_tasks | [
"license:mit",
"synthetic",
"region:us"
] | 2024-01-03T18:18:43+00:00 | {"license": "mit", "tags": ["synthetic"]} | 2024-02-03T04:30:28+00:00 | [] | [] | TAGS
#license-mit #synthetic #region-us
| Synthetic data designed as prompts for generating embeddings training data for retrieval.
The "iteration" column refers to how the data was generated.
Iteration 1: Use the following pool of seed tasks, prompt GPT-3.5-Turbo to generate additional tasks.
Iteration 2: Use the ~40,000 tasks generated in Iteration 1 as seed tasks, prompt GPT-3.5-Turbo to generate additional tasks.
Iteration 3: Use the ~80,000 tasks generated in Iterations 1-2 as seed tasks, prompt GPT-4-Turbo to generate additional tasks. | [] | [
"TAGS\n#license-mit #synthetic #region-us \n"
] | [
15
] | [
"passage: TAGS\n#license-mit #synthetic #region-us \n"
] |
a0315c234866242279b66e9c5372ae33f29f818c | # Dataset Card for "squad_v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | textminr/squad_v2 | [
"region:us"
] | 2024-01-03T18:23:20+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}]}], "dataset_info": {"features": [{"name": "context", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 223643322, "num_examples": 130319}, {"name": "validation", "num_bytes": 21700718, "num_examples": 11873}], "download_size": 37365608, "dataset_size": 245344040}} | 2024-01-04T19:51:19+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "squad_v2"
More Information needed | [
"# Dataset Card for \"squad_v2\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"squad_v2\"\n\nMore Information needed"
] | [
6,
15
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"squad_v2\"\n\nMore Information needed"
] |
33c028585b647ec54032e48843aef98e914dd9ad |
This dataset was generated using [TheBloke/SOLAR-10.7B-Instruct-v1.0-AWQ](https://huggingface.co/TheBloke/SOLAR-10.7B-Instruct-v1.0-AWQ)
The goal is to generate a better structured text from a given source, on a RAG context.
For each input, this prompt was executed through the model:
```plaintext
Context:
$INPUT
From the context, list all the essential facts about the text (if any):
All themes;
All conclusions;
All ideas;
All locations;
All dates;
All values;
And any other relevant information.
Your answer must contain each category and its facts.
```
This is a summarization of sorts, but it breaks down the information in a more organized form.
The idea is to finetune a smaller model to accomplish this task, so it can become part of a RAG pipeline (which will provide a cleaner text with better readability for the bigger LLM to ingest and provide an answer) | cnmoro/Text_Structuring_SOLAR_10.7B_Distilled | [
"task_categories:summarization",
"size_categories:100K<n<1M",
"language:en",
"license:mit",
"region:us"
] | 2024-01-03T18:27:49+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["100K<n<1M"], "task_categories": ["summarization"], "pretty_name": "text structuring"} | 2024-01-06T03:49:49+00:00 | [] | [
"en"
] | TAGS
#task_categories-summarization #size_categories-100K<n<1M #language-English #license-mit #region-us
|
This dataset was generated using TheBloke/SOLAR-10.7B-Instruct-v1.0-AWQ
The goal is to generate a better structured text from a given source, on a RAG context.
For each input, this prompt was executed through the model:
This is a summarization of sorts, but it breaks down the information in a more organized form.
The idea is to finetune a smaller model to accomplish this task, so it can become part of a RAG pipeline (which will provide a cleaner text with better readability for the bigger LLM to ingest and provide an answer) | [] | [
"TAGS\n#task_categories-summarization #size_categories-100K<n<1M #language-English #license-mit #region-us \n"
] | [
37
] | [
"passage: TAGS\n#task_categories-summarization #size_categories-100K<n<1M #language-English #license-mit #region-us \n"
] |
bd66826f945e1a9409005ae8f84a4edaf0d5336e | Collect images from https://gelbooru.com/
id range:0~9393795
encoding: UTF-8
search tags:"-animated -3d_(artwork) -webm -gif -video -real_life -comic -photo_(medium)"
max shortest edge size ==1536 ,save using .webp with 90%quality
The total number search iamges is 8364374, filtered out 18832.
image not in it:
gif/video
truncated(more than 10+ repeat download)
too large(over pillow default limit pixels)
In the metainfo last 5 columns,[artist,character,copyright,metadata,tags],"None" means lack of anything, rather than string "None".
*.txt from the crawler results,it's' not captions.
please build captions from metainfo and tagger
Disclaimer
Disclaimer: By downloading or using this dataset, you agree to the following terms and conditions:
Purpose of Crawling: The dataset is obtained by crawling a publicly available website. The purpose of this crawling behavior is to upload the dataset to Hugging Face in order to alleviate the load on the original booru site.
Data Accuracy: We make efforts to ensure the accuracy of the dataset, but we cannot guarantee the completeness and accuracy of the data. Users are responsible for evaluating the quality and accuracy of the dataset and bear any consequences arising from inaccurate or incomplete data.
Full Responsibility: The uploader of this dataset shall not be liable for any losses or damages (including but not limited to any direct, indirect, incidental damages) arising from the use, misuse, or inability to use the dataset in any way.
Please read and understand the above terms and conditions carefully before using this dataset. If you do not agree to these terms and conditions, you are not allowed to use this dataset. | NebulaeWis/gelbooru_images | [
"task_categories:text-to-image",
"size_categories:1M<n<10M",
"language:en",
"region:us"
] | 2024-01-03T18:31:43+00:00 | {"language": ["en"], "size_categories": ["1M<n<10M"], "task_categories": ["text-to-image"], "pretty_name": "gelbooru"} | 2024-01-10T02:57:32+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-to-image #size_categories-1M<n<10M #language-English #region-us
| Collect images from URL
id range:0~9393795
encoding: UTF-8
search tags:"-animated -3d_(artwork) -webm -gif -video -real_life -comic -photo_(medium)"
max shortest edge size ==1536 ,save using .webp with 90%quality
The total number search iamges is 8364374, filtered out 18832.
image not in it:
gif/video
truncated(more than 10+ repeat download)
too large(over pillow default limit pixels)
In the metainfo last 5 columns,[artist,character,copyright,metadata,tags],"None" means lack of anything, rather than string "None".
*.txt from the crawler results,it's' not captions.
please build captions from metainfo and tagger
Disclaimer
Disclaimer: By downloading or using this dataset, you agree to the following terms and conditions:
Purpose of Crawling: The dataset is obtained by crawling a publicly available website. The purpose of this crawling behavior is to upload the dataset to Hugging Face in order to alleviate the load on the original booru site.
Data Accuracy: We make efforts to ensure the accuracy of the dataset, but we cannot guarantee the completeness and accuracy of the data. Users are responsible for evaluating the quality and accuracy of the dataset and bear any consequences arising from inaccurate or incomplete data.
Full Responsibility: The uploader of this dataset shall not be liable for any losses or damages (including but not limited to any direct, indirect, incidental damages) arising from the use, misuse, or inability to use the dataset in any way.
Please read and understand the above terms and conditions carefully before using this dataset. If you do not agree to these terms and conditions, you are not allowed to use this dataset. | [] | [
"TAGS\n#task_categories-text-to-image #size_categories-1M<n<10M #language-English #region-us \n"
] | [
34
] | [
"passage: TAGS\n#task_categories-text-to-image #size_categories-1M<n<10M #language-English #region-us \n"
] |
19255b15c8eebfeaa558b5b4d5ee9af4c34da415 |
This dataset presents a collection of U.S. news headlines between 2019 and 2022 from Twitter and Facebook, with automatic annotations and human verifications. For more details on the methodology and annotation process, please refer to our paper {News Gathering: Leveraging Transformers to Rank News}.
## Attributes:
This dataset comprises five attributes: the first corresponds to "Headlines 1," the second to "Headlines 2," the third to the "target" variable {0, 1}, the fourth is related to the "split" {train, validation, test}, and finally, the fifth attribute indicates the "type" {soft label, human-verified}. Both sentences are associated with news extracted from diverse U.S. news sources {The New York Times, San Francisco Chronicle, National Broadcasting, Yahoo News, among other outlets}. The "target" variable indicates whether both sentences relate to the same event {1} or not {0}. Regarding the "type," {soft label} corresponds to an automatic process following the methodology in the paper, and {human-verified} indicates a process verified through a survey by humans.
## Data Source:
The primary sources included Twitter, accessed via the Academic API, and Facebook, accessed through CrowdTangle. This facilitated the automatic annotation of USA news articles spanning 2019 to 2022 by the methodology outlined in the paper. Within the test dataset, this sentence pair underwent human verification through a survey.
## Data Format:
The dataset is presented in tabular format and comprises five columns, as mentioned in the previous description. | cmunhozc/usa_news_en | [
"task_categories:text-classification",
"size_categories:100K<n<1M",
"language:en",
"license:mit",
"CENIA",
"News",
"region:us"
] | 2024-01-03T18:36:30+00:00 | {"language": ["en"], "license": "mit", "size_categories": ["100K<n<1M"], "task_categories": ["text-classification"], "tags": ["CENIA", "News"]} | 2024-01-03T20:04:46+00:00 | [] | [
"en"
] | TAGS
#task_categories-text-classification #size_categories-100K<n<1M #language-English #license-mit #CENIA #News #region-us
|
This dataset presents a collection of U.S. news headlines between 2019 and 2022 from Twitter and Facebook, with automatic annotations and human verifications. For more details on the methodology and annotation process, please refer to our paper {News Gathering: Leveraging Transformers to Rank News}.
## Attributes:
This dataset comprises five attributes: the first corresponds to "Headlines 1," the second to "Headlines 2," the third to the "target" variable {0, 1}, the fourth is related to the "split" {train, validation, test}, and finally, the fifth attribute indicates the "type" {soft label, human-verified}. Both sentences are associated with news extracted from diverse U.S. news sources {The New York Times, San Francisco Chronicle, National Broadcasting, Yahoo News, among other outlets}. The "target" variable indicates whether both sentences relate to the same event {1} or not {0}. Regarding the "type," {soft label} corresponds to an automatic process following the methodology in the paper, and {human-verified} indicates a process verified through a survey by humans.
## Data Source:
The primary sources included Twitter, accessed via the Academic API, and Facebook, accessed through CrowdTangle. This facilitated the automatic annotation of USA news articles spanning 2019 to 2022 by the methodology outlined in the paper. Within the test dataset, this sentence pair underwent human verification through a survey.
## Data Format:
The dataset is presented in tabular format and comprises five columns, as mentioned in the previous description. | [
"## Attributes:\n\nThis dataset comprises five attributes: the first corresponds to \"Headlines 1,\" the second to \"Headlines 2,\" the third to the \"target\" variable {0, 1}, the fourth is related to the \"split\" {train, validation, test}, and finally, the fifth attribute indicates the \"type\" {soft label, human-verified}. Both sentences are associated with news extracted from diverse U.S. news sources {The New York Times, San Francisco Chronicle, National Broadcasting, Yahoo News, among other outlets}. The \"target\" variable indicates whether both sentences relate to the same event {1} or not {0}. Regarding the \"type,\" {soft label} corresponds to an automatic process following the methodology in the paper, and {human-verified} indicates a process verified through a survey by humans.",
"## Data Source:\n\nThe primary sources included Twitter, accessed via the Academic API, and Facebook, accessed through CrowdTangle. This facilitated the automatic annotation of USA news articles spanning 2019 to 2022 by the methodology outlined in the paper. Within the test dataset, this sentence pair underwent human verification through a survey.",
"## Data Format:\n\nThe dataset is presented in tabular format and comprises five columns, as mentioned in the previous description."
] | [
"TAGS\n#task_categories-text-classification #size_categories-100K<n<1M #language-English #license-mit #CENIA #News #region-us \n",
"## Attributes:\n\nThis dataset comprises five attributes: the first corresponds to \"Headlines 1,\" the second to \"Headlines 2,\" the third to the \"target\" variable {0, 1}, the fourth is related to the \"split\" {train, validation, test}, and finally, the fifth attribute indicates the \"type\" {soft label, human-verified}. Both sentences are associated with news extracted from diverse U.S. news sources {The New York Times, San Francisco Chronicle, National Broadcasting, Yahoo News, among other outlets}. The \"target\" variable indicates whether both sentences relate to the same event {1} or not {0}. Regarding the \"type,\" {soft label} corresponds to an automatic process following the methodology in the paper, and {human-verified} indicates a process verified through a survey by humans.",
"## Data Source:\n\nThe primary sources included Twitter, accessed via the Academic API, and Facebook, accessed through CrowdTangle. This facilitated the automatic annotation of USA news articles spanning 2019 to 2022 by the methodology outlined in the paper. Within the test dataset, this sentence pair underwent human verification through a survey.",
"## Data Format:\n\nThe dataset is presented in tabular format and comprises five columns, as mentioned in the previous description."
] | [
43,
210,
73,
29
] | [
"passage: TAGS\n#task_categories-text-classification #size_categories-100K<n<1M #language-English #license-mit #CENIA #News #region-us \n## Attributes:\n\nThis dataset comprises five attributes: the first corresponds to \"Headlines 1,\" the second to \"Headlines 2,\" the third to the \"target\" variable {0, 1}, the fourth is related to the \"split\" {train, validation, test}, and finally, the fifth attribute indicates the \"type\" {soft label, human-verified}. Both sentences are associated with news extracted from diverse U.S. news sources {The New York Times, San Francisco Chronicle, National Broadcasting, Yahoo News, among other outlets}. The \"target\" variable indicates whether both sentences relate to the same event {1} or not {0}. Regarding the \"type,\" {soft label} corresponds to an automatic process following the methodology in the paper, and {human-verified} indicates a process verified through a survey by humans.## Data Source:\n\nThe primary sources included Twitter, accessed via the Academic API, and Facebook, accessed through CrowdTangle. This facilitated the automatic annotation of USA news articles spanning 2019 to 2022 by the methodology outlined in the paper. Within the test dataset, this sentence pair underwent human verification through a survey.## Data Format:\n\nThe dataset is presented in tabular format and comprises five columns, as mentioned in the previous description."
] |
4a8d20aa3eb977cb1b9c5ecd54df99edb2662f76 | dataset_info:
download_size: 455.989186 Mb # Total download size in bytes
# TV Channel Transcriptions
This dataset was transcribed with a whisper-large v2 model from the streams of TV channels, for research purposes.
[Project site](https://rtlm.info/)
## Data Overview
The dataset contains a zip file for each channel, for each year.
* 2023.11.05 - 2024 # ORT
* 2023.11.12 - 2024 # Belarus 1
* 2023.11.12 - 2024 # 1+1
* 2023.11.26 - 2024 # Russia 1
Inside each zip file, there are text files with transcriptions of 5-10 minutes of video. 24/7 streams are split into 5-10-minute chunks.
These files do not include the 2024 year. To obtain the actual 2024 year data, you need to download files from the bucket:
* [2024_ORT](https://storage.googleapis.com/rtlm/2024_ORT.zip)
* [2024_belarusone](https://storage.googleapis.com/rtlm/2024_belarusone.zip)
* [2024_oneplusone](https://storage.googleapis.com/rtlm/2024_oneplusone.zip)
* [2024_russiaone](https://storage.googleapis.com/rtlm/2024_russiaone.zip)
## Sample of downloading the actual dataset from the bucket
```
import pandas as pd
import datetime
import os
import zipfile
import glob
import requests
import shutil
def download_datasets(urls, start_year, end_year):
# for year in range(start_year, end_year + 1):
for download_url in urls:
# download_url = url.replace('2023', str(year))
print(f'downloading {download_url}')
response = requests.get(download_url)
if response.status_code == 200:
file_name = download_url.split('/')[-1]
with open(file_name, 'wb') as f:
f.write(response.content)
print(f"Downloaded {file_name}")
else:
print(f"Failed to download {download_url}")
def load_data_to_df(projects):
current_year = datetime.datetime.now().year
all_data = []
for project in projects:
for year in range(2023, current_year + 1):
archive_name = f"{year}_{project}.zip"
# Assuming the archive is downloaded in the current working directory
with zipfile.ZipFile(archive_name, 'r') as z:
z.extractall("temp_data")
for filename in glob.glob(f"temp_data/data/transcriptions/{project}/*.txt"):
with open(filename, 'r', encoding='utf-8') as file:
text = file.read()
# Extract date and time from the filename
basename = os.path.basename(filename)
datetime_str = basename.split('.')[0] # Remove the file extension
# Split into date and time components
date_part, time_part = datetime_str.split('_')
# Format time part correctly (replace '-' with ':')
time_part_formatted = time_part.replace('-', ':')
# Combine date and time with a space
datetime_str_formatted = f"{date_part} {time_part_formatted}"
all_data.append({"project": project, "date": datetime_str_formatted, "text": text})
# Cleanup extracted files
shutil.rmtree(f"temp_data/data/transcriptions/{project}")
# Cleanup the remaining temporary directory
shutil.rmtree("temp_data")
return pd.DataFrame(all_data)
current_year = datetime.datetime.now().year
projects = ['ORT', 'belarusone', 'oneplusone', 'russiaone']
urls = []
for year in range(2023, current_year + 1):
for project in projects:
urls.append(f"https://storage.googleapis.com/rtlm/{year}_{project}.zip")
print(urls)
download_datasets(urls, 2023, current_year)
# Save to df
projects = [url.split('/')[-1].split('_')[1].split('.')[0] for url in urls]
# Create the DataFrame
df = load_data_to_df(projects)
print(df.head(2))
df.to_csv('rtlm.csv', index=False)
```
## Known issues
* The first part of Belarus one channel was created by two instances, so it contains some duplicate files.
* Due to technical issues or channel restrictions, some periods were not transcribed.
* Some transcriptions may contain hallucinations, in particular in a silence period. However, these hallucinations have stable signatures.
## Disclaimer
The dataset is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the dataset or the use or other dealings in the dataset.
End users of the dataset are solely responsible for ensuring that their use complies with all applicable laws and copyrights. The dataset is based on transcriptions from open live streams of various TV channels and should be used in accordance with the Creative Commons Attribution-NonCommercial (CC BY-NC) license, respecting the non-commercial constraints and the need for attribution.
Please note that the use of this dataset might be subject to additional legal and ethical considerations, and it is the end user’s responsibility to determine whether their use of the dataset adheres to these considerations. The authors of this dataset make no representations or guarantees regarding the legality or ethicality of the dataset's use by third parties. | format37/rtlm | [
"task_categories:text-classification",
"size_categories:10K<n<100K",
"language:ru",
"language:be",
"language:uk",
"license:cc-by-nc-2.0",
"sociology",
"region:us"
] | 2024-01-03T19:03:51+00:00 | {"language": ["ru", "be", "uk"], "license": "cc-by-nc-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"], "pretty_name": "rtlm", "tags": ["sociology"]} | 2024-01-03T21:06:11+00:00 | [] | [
"ru",
"be",
"uk"
] | TAGS
#task_categories-text-classification #size_categories-10K<n<100K #language-Russian #language-Belarusian #language-Ukrainian #license-cc-by-nc-2.0 #sociology #region-us
| dataset_info:
download_size: 455.989186 Mb # Total download size in bytes
# TV Channel Transcriptions
This dataset was transcribed with a whisper-large v2 model from the streams of TV channels, for research purposes.
Project site
## Data Overview
The dataset contains a zip file for each channel, for each year.
* 2023.11.05 - 2024 # ORT
* 2023.11.12 - 2024 # Belarus 1
* 2023.11.12 - 2024 # 1+1
* 2023.11.26 - 2024 # Russia 1
Inside each zip file, there are text files with transcriptions of 5-10 minutes of video. 24/7 streams are split into 5-10-minute chunks.
These files do not include the 2024 year. To obtain the actual 2024 year data, you need to download files from the bucket:
* 2024_ORT
* 2024_belarusone
* 2024_oneplusone
* 2024_russiaone
## Sample of downloading the actual dataset from the bucket
## Known issues
* The first part of Belarus one channel was created by two instances, so it contains some duplicate files.
* Due to technical issues or channel restrictions, some periods were not transcribed.
* Some transcriptions may contain hallucinations, in particular in a silence period. However, these hallucinations have stable signatures.
## Disclaimer
The dataset is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the dataset or the use or other dealings in the dataset.
End users of the dataset are solely responsible for ensuring that their use complies with all applicable laws and copyrights. The dataset is based on transcriptions from open live streams of various TV channels and should be used in accordance with the Creative Commons Attribution-NonCommercial (CC BY-NC) license, respecting the non-commercial constraints and the need for attribution.
Please note that the use of this dataset might be subject to additional legal and ethical considerations, and it is the end user’s responsibility to determine whether their use of the dataset adheres to these considerations. The authors of this dataset make no representations or guarantees regarding the legality or ethicality of the dataset's use by third parties. | [
"# Total download size in bytes",
"# TV Channel Transcriptions\nThis dataset was transcribed with a whisper-large v2 model from the streams of TV channels, for research purposes. \nProject site",
"## Data Overview\nThe dataset contains a zip file for each channel, for each year. \n* 2023.11.05 - 2024 # ORT \n* 2023.11.12 - 2024 # Belarus 1 \n* 2023.11.12 - 2024 # 1+1 \n* 2023.11.26 - 2024 # Russia 1 \n \nInside each zip file, there are text files with transcriptions of 5-10 minutes of video. 24/7 streams are split into 5-10-minute chunks. \nThese files do not include the 2024 year. To obtain the actual 2024 year data, you need to download files from the bucket: \n* 2024_ORT \n* 2024_belarusone \n* 2024_oneplusone \n* 2024_russiaone",
"## Sample of downloading the actual dataset from the bucket",
"## Known issues\n* The first part of Belarus one channel was created by two instances, so it contains some duplicate files.\n* Due to technical issues or channel restrictions, some periods were not transcribed.\n* Some transcriptions may contain hallucinations, in particular in a silence period. However, these hallucinations have stable signatures.",
"## Disclaimer\nThe dataset is provided \"as is\", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the dataset or the use or other dealings in the dataset. \n \nEnd users of the dataset are solely responsible for ensuring that their use complies with all applicable laws and copyrights. The dataset is based on transcriptions from open live streams of various TV channels and should be used in accordance with the Creative Commons Attribution-NonCommercial (CC BY-NC) license, respecting the non-commercial constraints and the need for attribution. \n \nPlease note that the use of this dataset might be subject to additional legal and ethical considerations, and it is the end user’s responsibility to determine whether their use of the dataset adheres to these considerations. The authors of this dataset make no representations or guarantees regarding the legality or ethicality of the dataset's use by third parties."
] | [
"TAGS\n#task_categories-text-classification #size_categories-10K<n<100K #language-Russian #language-Belarusian #language-Ukrainian #license-cc-by-nc-2.0 #sociology #region-us \n",
"# Total download size in bytes",
"# TV Channel Transcriptions\nThis dataset was transcribed with a whisper-large v2 model from the streams of TV channels, for research purposes. \nProject site",
"## Data Overview\nThe dataset contains a zip file for each channel, for each year. \n* 2023.11.05 - 2024 # ORT \n* 2023.11.12 - 2024 # Belarus 1 \n* 2023.11.12 - 2024 # 1+1 \n* 2023.11.26 - 2024 # Russia 1 \n \nInside each zip file, there are text files with transcriptions of 5-10 minutes of video. 24/7 streams are split into 5-10-minute chunks. \nThese files do not include the 2024 year. To obtain the actual 2024 year data, you need to download files from the bucket: \n* 2024_ORT \n* 2024_belarusone \n* 2024_oneplusone \n* 2024_russiaone",
"## Sample of downloading the actual dataset from the bucket",
"## Known issues\n* The first part of Belarus one channel was created by two instances, so it contains some duplicate files.\n* Due to technical issues or channel restrictions, some periods were not transcribed.\n* Some transcriptions may contain hallucinations, in particular in a silence period. However, these hallucinations have stable signatures.",
"## Disclaimer\nThe dataset is provided \"as is\", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the dataset or the use or other dealings in the dataset. \n \nEnd users of the dataset are solely responsible for ensuring that their use complies with all applicable laws and copyrights. The dataset is based on transcriptions from open live streams of various TV channels and should be used in accordance with the Creative Commons Attribution-NonCommercial (CC BY-NC) license, respecting the non-commercial constraints and the need for attribution. \n \nPlease note that the use of this dataset might be subject to additional legal and ethical considerations, and it is the end user’s responsibility to determine whether their use of the dataset adheres to these considerations. The authors of this dataset make no representations or guarantees regarding the legality or ethicality of the dataset's use by third parties."
] | [
62,
7,
40,
146,
14,
77,
278
] | [
"passage: TAGS\n#task_categories-text-classification #size_categories-10K<n<100K #language-Russian #language-Belarusian #language-Ukrainian #license-cc-by-nc-2.0 #sociology #region-us \n# Total download size in bytes# TV Channel Transcriptions\nThis dataset was transcribed with a whisper-large v2 model from the streams of TV channels, for research purposes. \nProject site## Data Overview\nThe dataset contains a zip file for each channel, for each year. \n* 2023.11.05 - 2024 # ORT \n* 2023.11.12 - 2024 # Belarus 1 \n* 2023.11.12 - 2024 # 1+1 \n* 2023.11.26 - 2024 # Russia 1 \n \nInside each zip file, there are text files with transcriptions of 5-10 minutes of video. 24/7 streams are split into 5-10-minute chunks. \nThese files do not include the 2024 year. To obtain the actual 2024 year data, you need to download files from the bucket: \n* 2024_ORT \n* 2024_belarusone \n* 2024_oneplusone \n* 2024_russiaone## Sample of downloading the actual dataset from the bucket## Known issues\n* The first part of Belarus one channel was created by two instances, so it contains some duplicate files.\n* Due to technical issues or channel restrictions, some periods were not transcribed.\n* Some transcriptions may contain hallucinations, in particular in a silence period. However, these hallucinations have stable signatures."
] |
0c9ef8ab937c232a67427e557f7b85ddfc0866d5 | # Dataset Card for "curated-conversations"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | mii-llm/curated-conversations | [
"region:us"
] | 2024-01-03T19:08:05+00:00 | {"dataset_info": {"features": [{"name": "conversation", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 1495505, "num_examples": 529}], "download_size": 804743, "dataset_size": 1495505}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T19:08:08+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "curated-conversations"
More Information needed | [
"# Dataset Card for \"curated-conversations\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"curated-conversations\"\n\nMore Information needed"
] | [
6,
16
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"curated-conversations\"\n\nMore Information needed"
] |
d7c45d08274b20abdfb7c7dacba1c350256c95ad | # Dataset Card for "platypus-templated-ia-flat"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | sordonia/platypus-templated-ia-flat | [
"region:us"
] | 2024-01-03T20:01:45+00:00 | {"dataset_info": {"features": [{"name": "split", "dtype": "string"}, {"name": "source", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "task_source", "dtype": "string"}, {"name": "task_name", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 31654017, "num_examples": 24926}], "download_size": 15672184, "dataset_size": 31654017}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T20:02:43+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "platypus-templated-ia-flat"
More Information needed | [
"# Dataset Card for \"platypus-templated-ia-flat\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"platypus-templated-ia-flat\"\n\nMore Information needed"
] | [
6,
21
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"platypus-templated-ia-flat\"\n\nMore Information needed"
] |
80493acad8f240aaac3560cf17bb2fe85d320de8 | # Dataset Card for "ultrachat-templated-ia-flat"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | sordonia/ultrachat-templated-ia-flat | [
"region:us"
] | 2024-01-03T20:05:55+00:00 | {"dataset_info": {"features": [{"name": "source", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "task_source", "dtype": "string"}, {"name": "task_name", "dtype": "string"}, {"name": "split", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 742393824, "num_examples": 320000}], "download_size": 418519900, "dataset_size": 742393824}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T20:06:17+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "ultrachat-templated-ia-flat"
More Information needed | [
"# Dataset Card for \"ultrachat-templated-ia-flat\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"ultrachat-templated-ia-flat\"\n\nMore Information needed"
] | [
6,
21
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"ultrachat-templated-ia-flat\"\n\nMore Information needed"
] |
dd7baef5abe1b7224140d2a1f175c1ae5411eac9 |
1024x1024px PNG encoded, scale=0.1, roughness=1.0
each map was then processed with 100 iterations of rain erosion simulation (e99 directory)
for further explanation please see https://en.wikipedia.org/wiki/Diamond-square_algorithm
The idea was first introduced by Fournier, Fussell and Carpenter at SIGGRAPH in 1982
| TashaSkyUp/random_midpoint_displacement_fractal | [
"size_categories:n<1K",
"license:mit",
"region:us"
] | 2024-01-03T20:06:12+00:00 | {"license": "mit", "size_categories": ["n<1K"], "pretty_name": "random midpoint displacement fractal images 1024x1024 png"} | 2024-01-03T20:46:34+00:00 | [] | [] | TAGS
#size_categories-n<1K #license-mit #region-us
|
1024x1024px PNG encoded, scale=0.1, roughness=1.0
each map was then processed with 100 iterations of rain erosion simulation (e99 directory)
for further explanation please see URL
The idea was first introduced by Fournier, Fussell and Carpenter at SIGGRAPH in 1982
| [] | [
"TAGS\n#size_categories-n<1K #license-mit #region-us \n"
] | [
21
] | [
"passage: TAGS\n#size_categories-n<1K #license-mit #region-us \n"
] |
10ff0cfd52fb45a8dda6292448c49253093c1d9d | # Dataset Card for "mbpp-templated-ia-flat"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | sordonia/mbpp-templated-ia-flat | [
"region:us"
] | 2024-01-03T20:18:59+00:00 | {"dataset_info": {"features": [{"name": "task_id", "dtype": "int32"}, {"name": "source", "dtype": "string"}, {"name": "task_source", "dtype": "string"}, {"name": "task_name", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "split", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 234967, "num_examples": 464}], "download_size": 105196, "dataset_size": 234967}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-03T20:36:32+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "mbpp-templated-ia-flat"
More Information needed | [
"# Dataset Card for \"mbpp-templated-ia-flat\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"mbpp-templated-ia-flat\"\n\nMore Information needed"
] | [
6,
20
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"mbpp-templated-ia-flat\"\n\nMore Information needed"
] |
fda6e778ba46ecbbeac90dd5725ec58a61e3c29a | # Dataset Card for "adauni-templated-reduced-ia-flat"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | sordonia/adauni-templated-reduced-ia-flat | [
"region:us"
] | 2024-01-03T20:33:22+00:00 | {"dataset_info": {"features": [{"name": "source", "dtype": "string"}, {"name": "target", "dtype": "string"}, {"name": "task_name", "dtype": "string"}, {"name": "task_source", "dtype": "string"}, {"name": "template_type", "dtype": "string"}, {"name": "template_idx", "dtype": "int64"}, {"name": "split", "dtype": "string"}, {"name": "negative_target", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 7649136338.0, "num_examples": 2411665}], "download_size": 4520447916, "dataset_size": 7649136338.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-04T15:29:45+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "adauni-templated-reduced-ia-flat"
More Information needed | [
"# Dataset Card for \"adauni-templated-reduced-ia-flat\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"adauni-templated-reduced-ia-flat\"\n\nMore Information needed"
] | [
6,
24
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"adauni-templated-reduced-ia-flat\"\n\nMore Information needed"
] |
dac22056a29e4bead52450b974e593baffae45b0 |
This dataset comprises converted version of the Global Mosaic of Geostationary Images from NOAA on AWS, which stitches together geostationary imagery every hour for a snapshot of
nearly the entire world in 5 bands, and at a 8km resolution. The original NetCDF files were converted to Zarr and concatenated along the time dimension per day, with each of the 5 bands
being included in one overall Xarray Dataset. | jacobbieker/global-mosaic-of-geostationary-images | [
"size_categories:1K<n<10K",
"license:mit",
"climate",
"doi:10.57967/hf/1646",
"region:us"
] | 2024-01-03T21:48:17+00:00 | {"license": "mit", "size_categories": ["1K<n<10K"], "pretty_name": "Global Mosaic of Geostationary Images", "tags": ["climate"]} | 2024-02-17T16:35:25+00:00 | [] | [] | TAGS
#size_categories-1K<n<10K #license-mit #climate #doi-10.57967/hf/1646 #region-us
|
This dataset comprises converted version of the Global Mosaic of Geostationary Images from NOAA on AWS, which stitches together geostationary imagery every hour for a snapshot of
nearly the entire world in 5 bands, and at a 8km resolution. The original NetCDF files were converted to Zarr and concatenated along the time dimension per day, with each of the 5 bands
being included in one overall Xarray Dataset. | [] | [
"TAGS\n#size_categories-1K<n<10K #license-mit #climate #doi-10.57967/hf/1646 #region-us \n"
] | [
39
] | [
"passage: TAGS\n#size_categories-1K<n<10K #license-mit #climate #doi-10.57967/hf/1646 #region-us \n"
] |
069e7604df6cfa4079f504db4e58fe38f85b9a5f | # Dataset Card for "arc_tr_s1"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | sezosan/arc_tr_s1 | [
"region:us"
] | 2024-01-03T22:19:23+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "choices", "sequence": [{"name": "text", "dtype": "string"}, {"name": "label", "dtype": "string"}]}, {"name": "answerKey", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 86423.0, "num_examples": 250}], "download_size": 0, "dataset_size": 86423.0}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-03T22:24:39+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "arc_tr_s1"
More Information needed | [
"# Dataset Card for \"arc_tr_s1\"\n\nMore Information needed"
] | [
"TAGS\n#region-us \n",
"# Dataset Card for \"arc_tr_s1\"\n\nMore Information needed"
] | [
6,
17
] | [
"passage: TAGS\n#region-us \n# Dataset Card for \"arc_tr_s1\"\n\nMore Information needed"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.