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|---|---|---|---|---|---|---|
c837c6cae1fdd623c454f23fd753d852e0dce69e
|
yash261/mydata
|
[
"license:apache-2.0",
"region:us"
] |
2023-05-24T19:24:10+00:00
|
{"license": "apache-2.0"}
|
2023-05-24T19:24:10+00:00
|
|
4501650cc271a3a6736cf57bf7239b68bfc1be98
|
## Dataset Card for "AGabs_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/code-code-GeneratingAssertsAbstract
|
[
"region:us"
] |
2023-05-24T19:38:11+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 15586336, "num_examples": 15809}, {"name": "train", "num_bytes": 125099945, "num_examples": 126477}, {"name": "test", "num_bytes": 15640963, "num_examples": 15810}], "download_size": 33528231, "dataset_size": 156327244}}
|
2023-05-30T15:13:52+00:00
|
6ce0d49f850aa9dde884516de2b8f520ab2aa399
|
SriPrasanna/coffee-beans
|
[
"region:us"
] |
2023-05-24T19:40:51+00:00
|
{}
|
2023-05-24T21:28:00+00:00
|
|
3eb875b16bf38c8a2d35ab5bd08a4a4dbc803538
|
araldsopoti/qa
|
[
"license:openrail",
"region:us"
] |
2023-05-24T19:41:04+00:00
|
{"license": "openrail"}
|
2023-05-24T19:45:00+00:00
|
|
e76504e682bea6fe533ef23a6c8317c1a022b29e
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
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).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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 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]
|
AntonioRenatoMontefusco/KDDChallenge2023FirstHalf
|
[
"region:us"
] |
2023-05-24T19:55:08+00:00
|
{}
|
2023-05-24T20:50:48+00:00
|
ea65610661574ccfde67c8aaf055f7f6a2bd6b94
|
abhayzala/VPEval
|
[
"license:mit",
"region:us"
] |
2023-05-24T20:08:26+00:00
|
{"license": "mit"}
|
2023-05-24T21:53:24+00:00
|
|
4ad94b7df68debe91e40084db34b83372666adf1
|
# Dataset Card for "pre-training"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/T5_pre-training
|
[
"region:us"
] |
2023-05-24T20:20:14+00:00
|
{"dataset_info": {"features": [{"name": "pre-training", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1447722048, "num_examples": 2672450}], "download_size": 289612172, "dataset_size": 1447722048}}
|
2023-05-30T15:16:10+00:00
|
59769b5410348f3893cd36654618e3a16f8bc4ea
|
# Dataset Card for "test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
nouman-10/test
|
[
"region:us"
] |
2023-05-24T20:25:35+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 2359545.254237288, "num_examples": 170}], "download_size": 2345262, "dataset_size": 2359545.254237288}}
|
2023-05-24T20:25:37+00:00
|
cf48e3b7148d74d92e642c7e7204b1fcc2660db5
|
# Dataset Card for "AGraw_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/code-code-GeneratingAssertsRaw
|
[
"region:us"
] |
2023-05-24T20:31:18+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 20569417, "num_examples": 18816}, {"name": "train", "num_bytes": 164564740, "num_examples": 150523}, {"name": "test", "num_bytes": 20670941, "num_examples": 18815}], "download_size": 77171034, "dataset_size": 205805098}}
|
2023-05-30T15:15:29+00:00
|
b7ff4b2083415d4e14eccf3732cb56ae3eb6e792
|
# Dataset Card for "BFmed_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/code-code-BugFixingMed
|
[
"region:us"
] |
2023-05-24T21:10:42+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 4047457, "num_examples": 6546}, {"name": "train", "num_bytes": 32300602, "num_examples": 52364}, {"name": "test", "num_bytes": 4024395, "num_examples": 6545}], "download_size": 0, "dataset_size": 40372454}}
|
2023-05-30T15:16:44+00:00
|
41f2f4f748893802e541c6363c165d2fda582c86
|
# Dataset Card for "BFsmall_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/code-code-BugFixingSmall
|
[
"region:us"
] |
2023-05-24T21:10:58+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 1582636, "num_examples": 5835}, {"name": "train", "num_bytes": 12633815, "num_examples": 46680}, {"name": "test", "num_bytes": 1573020, "num_examples": 5835}], "download_size": 0, "dataset_size": 15789471}}
|
2023-05-30T15:17:41+00:00
|
0bd8dafbb29b7670e5d5cbb17483ad95f94555aa
|
# Dataset Card for "CS_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>
|
semeru/text-code-CodeSummarization
|
[
"region:us"
] |
2023-05-24T21:11:07+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 23742716, "num_examples": 104273}, {"name": "test", "num_bytes": 20824989, "num_examples": 90908}], "download_size": 0, "dataset_size": 44567705}}
|
2023-05-30T15:17:13+00:00
|
8ddafc6bc30235ce67d2968261843b2e030dbb24
|
# Dataset Card for "MG_finetuning"
## Reference
<pre><code>@article{Mastropaolo2022TransferLearningForCodeRelatedTasks
title={Using Transfer Learning for Code-Related Tasks},
author={Mastropaolo, Antonio and Cooper, Nathan and Nader Palacio, David and Scalabrino, Simone and
Poshyvanyk, Denys and Oliveto, Rocco and Bavota, Gabriele},
journal={arXiv preprint arXiv:2206.08574},
year={2022}
}</code></pre>[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
semeru/code-code-InjectMutants
|
[
"region:us"
] |
2023-05-24T21:11:23+00:00
|
{"dataset_info": {"features": [{"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 3146615, "num_examples": 11560}, {"name": "train", "num_bytes": 25193181, "num_examples": 92476}, {"name": "test", "num_bytes": 3154425, "num_examples": 11559}], "download_size": 0, "dataset_size": 31494221}}
|
2023-05-30T15:18:28+00:00
|
570b9dc7e55b68356b35539e4adccbb74a00b7ec
|
# Dataset Card for "53649cd7"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/53649cd7
|
[
"region:us"
] |
2023-05-24T21:11:31+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 182, "num_examples": 10}], "download_size": 1313, "dataset_size": 182}}
|
2023-05-24T21:11:33+00:00
|
eba41c74dcd9fc724736272061bf90f3a6e60cea
|
# Dataset Card for "6561e16e"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/6561e16e
|
[
"region:us"
] |
2023-05-24T21:11:34+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 182, "num_examples": 10}], "download_size": 1313, "dataset_size": 182}}
|
2023-05-24T21:11:35+00:00
|
353e7a996d4f577f37e4f15d26e6e907a98f42f0
|
# raccoon dataset
### the top 1000 highest rated Question Answer branches in the Open Assistant dataset
|
sruly/raccoon-dataset-v1
|
[
"size_categories:n<1K",
"language:en",
"license:apache-2.0",
"open assistant",
"region:us"
] |
2023-05-24T21:55:43+00:00
|
{"language": ["en"], "license": "apache-2.0", "size_categories": ["n<1K"], "pretty_name": "raccoon dataset", "tags": ["open assistant"]}
|
2023-05-24T22:28:53+00:00
|
3d8b0dd2d6e44721de334ffca11830b67683a464
|
# Dataset Card for "e5be4a03"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/e5be4a03
|
[
"region:us"
] |
2023-05-24T22:13:21+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 182, "num_examples": 10}], "download_size": 1324, "dataset_size": 182}}
|
2023-05-24T22:13:23+00:00
|
48e0f745c3bc6a20c697f3fa542dca9f24eb9aad
|
# Dataset Card for "mobile-icons-poc"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
daekeun-ml/mobile-icons-poc
|
[
"region:us"
] |
2023-05-24T22:19:17+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 19041285.0, "num_examples": 140}], "download_size": 19031365, "dataset_size": 19041285.0}}
|
2023-05-24T22:19:19+00:00
|
8454abe0cc508213c931e32fff18f982fc26712f
|
# PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition
## Dataset Description
- **Homepage:** https://github.com/google-research-datasets/PropSegmEnt
- **Repository:** https://github.com/google-research-datasets/PropSegmEnt
- **Paper:** https://arxiv.org/abs/2212.10750
- **Point of Contact:** [email protected]
### Dataset Summary
This is a reproduced (i.e. after web-crawling) and processed version of [the "PropSegment" dataset](https://github.com/google-research-datasets/PropSegmEnt) from Google Research.
Since the [`News`](https://github.com/google-research-datasets/NewSHead) portion of the dataset is released only via urls, we reconstruct the dataset by crawling.
Overall, ~96% of the dataset can be reproduced, and the rest ~4% either have url no longer valid, or sentences that have been edited (i.e. cannot be aligned with the orignial dataset).
PropSegment (Proposition-level Segmentation and Entailment) is a large-scale, human annotated dataset for segmenting English text into propositions, and recognizing proposition-level entailment relations --- whether a different, related document entails each proposition, contradicts it, or neither.
The original dataset features >45k human annotated propositions, i.e. individual semantic units within sentences, as well as >35k entailment labels between propositions and documents.
Check out more details in the [dataset paper](https://arxiv.org/abs/2212.10750).
## Dataset Structure
Here we provide processed versions of the dataset for seq2seq model inputs/outputs.
`proposition_segmentation.*.jsonl` contains data for the text segmentation task, i.e. split a sentence into propositions.
The output propositions are concatenated as one string (with no particular order between them) by a special token `[SEP]`.
Each proposition is annotated as spans enclosed by `[M]` and `[/M]`.
```
{
"sentence": "This film marks the directorial debut for production designer Robert Stromberg.",
"propositions": "This film marks the directorial debut for [M]production designer Robert Stromberg.[/M][SEP]This [M]film marks the directorial debut for[/M] production designer [M]Robert Stromberg[/M]."
}
```
`propnli.*.jsonl` contains examples for the proposition-to-document entailment task, i.e. Given a proposition and a document, predict whether the proposition can be entailed/contradicted, or neutral with respect to the document.
```
{
"hypothesis": "[M]The Departed is[/M] a 2006 feature film [M]directed by Martin Scorsese.[/M]",
"premise": "The Departed is a 2006 American crime thriller film directed by Martin Scorsese and written by William Monahan. It starred Leonardo DiCaprio, Matt Damon, Jack Nicholson, and Mark Wahlberg, with Martin Sheen, Ray Winstone, Vera Farmiga, and Alec Baldwin in supporting roles. It is a remake of the Hong Kong film Infernal Affairs (2002).\nThe Departed won the Oscar for Best Picture at the 79th Academy Awards. Scorsese received the Oscar for Best Director, Thelma Schoonmaker the Oscar for Best Editing and William Monahan the Oscar for Best Adapted Screenplay.",
"label": "e"
}
```
### Citation
```
@inproceedings{chen2023propsegment,
title = "{PropSegmEnt}: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition",
author = "Chen, Sihao and Buthpitiya, Senaka and Fabrikant, Alex and Roth, Dan and Schuster, Tal",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
year = "2023",
}
```
|
sihaochen/propsegment
|
[
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-4.0",
"NLP",
"Entailment",
"NLI",
"google-research-datasets",
"arxiv:2212.10750",
"region:us"
] |
2023-05-24T22:29:22+00:00
|
{"language": ["en"], "license": "cc-by-4.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification", "token-classification", "text-generation"], "pretty_name": "PropSegment", "tags": ["NLP", "Entailment", "NLI", "google-research-datasets"]}
|
2023-05-26T17:18:53+00:00
|
1154c87e5eac77af81d0f472e6a0ae77fd4a0436
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
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).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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 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]
|
VirtualRoyalty/SST5
|
[
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"region:us"
] |
2023-05-24T22:31:48+00:00
|
{"language": ["en"], "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "pretty_name": "sst-5"}
|
2023-05-24T23:10:29+00:00
|
4b488fd661b9a63f581729e38804c8f5b9e62ab9
|
cap1569hug/nva-queenmaria
|
[
"license:other",
"region:us"
] |
2023-05-24T22:43:21+00:00
|
{"license": "other"}
|
2023-05-25T00:30:03+00:00
|
|
5ce75280894458152d5da9f41ec7fab4c00f922d
|
xiaohk/embeddings
|
[
"license:mit",
"region:us"
] |
2023-05-24T23:13:07+00:00
|
{"license": "mit"}
|
2024-02-14T21:12:13+00:00
|
|
085e47b4f7502a102a90f4d2b9b66d0bcef00b15
|
VirtualRoyalty/20ng
|
[
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"region:us"
] |
2023-05-24T23:24:03+00:00
|
{"language": ["en"], "size_categories": ["1K<n<10K"], "task_categories": ["text-classification"], "pretty_name": "20ng"}
|
2023-05-24T23:51:25+00:00
|
|
04fade0adb3b7260cac927441e4aaee253fd02ba
|
Cheetor1996/Ayane_Shirakawa
|
[
"license:cc-by-2.0",
"region:us"
] |
2023-05-24T23:42:04+00:00
|
{"license": "cc-by-2.0"}
|
2023-05-24T23:43:48+00:00
|
|
a4dfcb4b8f6089ad1505bf5220ddf7be0a39d404
|
**Sayoko Kagami** from Helter Skelter Hakudaku no Mura
- *Trained with anime (full-final-pruned) model*
- *Works the best with ALL, MIDD, OUTD, and OUTALL LoRA weight block, and with 0.5+ weights.*
|
Cheetor1996/Sayoko_Kagami
|
[
"language:en",
"license:cc-by-2.0",
"art",
"region:us"
] |
2023-05-24T23:46:19+00:00
|
{"language": ["en"], "license": "cc-by-2.0", "tags": ["art"]}
|
2023-05-24T23:58:33+00:00
|
5bd72733d111c465e2ccaf465c9707402fb6a06f
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:09:41+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28615, "num_examples": 200}], "download_size": 0, "dataset_size": 28615}}
|
2023-05-25T00:21:49+00:00
|
945539284edd1202c0f1f5fa21049d5d394bc867
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:10:55+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28618, "num_examples": 200}], "download_size": 0, "dataset_size": 28618}}
|
2023-05-25T00:22:59+00:00
|
956c42129a0c7f50b8276efe6a41eeb05f7c93cf
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:24:37+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28448, "num_examples": 200}], "download_size": 13914, "dataset_size": 28448}}
|
2023-05-25T00:24:41+00:00
|
83c613bd5e1d80ea51940c4a1b79895636dd8a4c
|
# data summary
`zhihu_qa` instruction data follow `Open-Assistant`'s format
* 3k questions and 23w answsers on zhihu.com
* Questions taken from 10 popular topics:
* “Culture” (文化)
* “Education” (教育)
* “Art” (艺术)
* “University” (大学)
* “The Internet” (互联网)
* “Psychology” (心理)
* “Technology” (科技)
* “Health” (健康)
* “Career Development” (职业发展)
* “Lifestyle” (生活方式)
## sample
```json
{
"INSTRUCTION": "上海有哪些夜生活？ 老歌里面有唱到“夜上海”，那么现在的上海到底有哪些丰富的夜生活呢？",
"RESPONSE": "地点：闵行区男子技术学院（也叫MIT）去年夏季学期的一天晚上，心情不好，和同学在校园逛到凌晨一点多。去各个地方买饮料喝，在冰火吃烧烤。郊区自然不像市区这么热闹，但是这么晚了居然还有人。",
"SOURCE": "zhihu",
"meta": {
"question_id": 29639528,
"answer": 62379612,
"answer_type": "short_answers",
"tags": [
"上海",
"城市生活",
"城市",
"生活方式",
"夜生活"
]
}
}
```
|
zirui3/zhihu_qa_oa_instructions
|
[
"license:cc-by-4.0",
"region:us"
] |
2023-05-25T00:24:38+00:00
|
{"license": "cc-by-4.0"}
|
2023-05-25T01:49:33+00:00
|
0de73e5527131668d065e4e2dacef2bde2018811
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:26:15+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28526, "num_examples": 200}], "download_size": 13948, "dataset_size": 28526}}
|
2023-05-25T00:26:19+00:00
|
1b41ee40d5358514775258da80fa6d1b7f792225
|
# Dataset Card for "tldr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Archeane/tldr
|
[
"region:us"
] |
2023-05-25T00:29:39+00:00
|
{"dataset_info": {"features": [{"name": "Summary", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "__index_level_0__", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 20981509.697089948, "num_examples": 6123}, {"name": "test", "num_bytes": 1168494.987213404, "num_examples": 341}, {"name": "valid", "num_bytes": 1165068.315696649, "num_examples": 340}], "download_size": 14342947, "dataset_size": 23315073.0}}
|
2023-05-25T00:29:56+00:00
|
d0d290c9b1a8bea9891cd79af4b22f250bfec6dc
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_A_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_A_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:30:56+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28669, "num_examples": 200}], "download_size": 14083, "dataset_size": 28669}}
|
2023-05-25T00:31:00+00:00
|
8240c5a607fee2f8436582105f30ffd52a44c8cf
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:32:12+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28704, "num_examples": 200}], "download_size": 14133, "dataset_size": 28704}}
|
2023-05-25T00:32:17+00:00
|
c3b85253b69811c7bfa9b937d52ee84cd4b9e728
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_A_T_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_A_T_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:34:58+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28706, "num_examples": 200}], "download_size": 14162, "dataset_size": 28706}}
|
2023-05-25T00:35:02+00:00
|
9c3e10e2cbf60949c279df62d180f2a158288066
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:36:12+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28843, "num_examples": 200}], "download_size": 14303, "dataset_size": 28843}}
|
2023-05-25T00:36:16+00:00
|
c0f35e0b69d6c4391994b97c86fea0e56d964eba
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:38:19+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28562, "num_examples": 200}], "download_size": 14034, "dataset_size": 28562}}
|
2023-05-25T00:38:22+00:00
|
77a70f3070a7b02feca03a75c7c81a6e62163c8a
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:40:00+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28562, "num_examples": 200}], "download_size": 14026, "dataset_size": 28562}}
|
2023-05-25T00:40:04+00:00
|
f8467b95d6e87b12b6c2091cb4f63de3c01c4060
|
# Dataset Card for "12eae292"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/12eae292
|
[
"region:us"
] |
2023-05-25T00:42:00+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 176, "num_examples": 10}], "download_size": 1332, "dataset_size": 176}}
|
2023-05-25T00:42:01+00:00
|
88fd66a54562b07cb95855bc46fbf0df19d345ea
|
# Dataset Card for "9f0acde5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/9f0acde5
|
[
"region:us"
] |
2023-05-25T00:42:03+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 176, "num_examples": 10}], "download_size": 1332, "dataset_size": 176}}
|
2023-05-25T00:42:06+00:00
|
57f23dac3ea8069cdb5a40abf0c5563484bf7393
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:42:16+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28609, "num_examples": 200}], "download_size": 14030, "dataset_size": 28609}}
|
2023-05-25T00:42:20+00:00
|
e548b0c3f19260a5793f3507ec1bf861ff610dc8
|
# Dataset Card for "b1a936ee"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/b1a936ee
|
[
"region:us"
] |
2023-05-25T00:45:27+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 184, "num_examples": 10}], "download_size": 1338, "dataset_size": 184}}
|
2023-05-25T00:45:28+00:00
|
e5723a1719cce71a5ab73fb85f2dce28dba1fcc9
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_A_C_Q_rices_ns_200"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_A_C_Q_rices_ns_200
|
[
"region:us"
] |
2023-05-25T00:45:46+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 28670, "num_examples": 200}], "download_size": 14063, "dataset_size": 28670}}
|
2023-05-25T00:45:49+00:00
|
2bae7e818a1ba521203c0cd042321d7a1ee38a34
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T00:48:07+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 141394, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141394, "num_examples": 1000}], "download_size": 106130, "dataset_size": 282788}}
|
2023-05-25T01:23:53+00:00
|
e9472f417a3462bfd3788890afd59100349c6311
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T00:49:28+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 141084, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141084, "num_examples": 1000}], "download_size": 104516, "dataset_size": 282168}}
|
2023-05-25T01:25:12+00:00
|
f336688b0f0a2630a53f031673140873e96e9f35
|
KimuGenie/YNAT
|
[
"license:cc-by-sa-4.0",
"region:us"
] |
2023-05-25T00:50:10+00:00
|
{"license": "cc-by-sa-4.0"}
|
2023-05-25T03:54:38+00:00
|
|
6a3a1ab621f1c547ed9979f1b2e4150e3cc08204
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T00:52:50+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 140521, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 140614, "num_examples": 1000}], "download_size": 105181, "dataset_size": 281135}}
|
2023-05-25T01:20:19+00:00
|
17f7958b27e6a6b4971e6a383f54e639620088dd
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T00:56:10+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 140602, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 140634, "num_examples": 1000}], "download_size": 104588, "dataset_size": 281236}}
|
2023-05-25T01:31:35+00:00
|
6211b17ccdfb9c9c7c91f91ec2bab96136f0c23a
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T00:59:38+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 140706, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 140601, "num_examples": 1000}], "download_size": 105389, "dataset_size": 281307}}
|
2023-05-25T01:34:47+00:00
|
8aa498e1da300c1d7ad5382bc8b3abe5bfbd288c
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T01:03:11+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 140791, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 140621, "num_examples": 1000}], "download_size": 105484, "dataset_size": 281412}}
|
2023-05-25T01:38:06+00:00
|
cccc53b58474ff2cb0b8dc7d735c97ebe31fd813
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T01:06:51+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large__", "num_bytes": 140863, "num_examples": 1000}, {"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141014, "num_examples": 1000}], "download_size": 105742, "dataset_size": 281877}}
|
2023-05-25T01:41:33+00:00
|
a88ef9629f447b127fa207c50f611a9c999676de
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T01:53:44+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141431, "num_examples": 1000}], "download_size": 53194, "dataset_size": 141431}}
|
2023-05-25T02:06:09+00:00
|
b5baeec07454eab470d77d7348ddbee06529a761
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T01:55:40+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 140949, "num_examples": 1000}], "download_size": 0, "dataset_size": 140949}}
|
2023-05-25T02:08:25+00:00
|
f03f333da331e6fdb820934f1dfd0a099d9a7596
|
# Dataset Card for "crop_crack_and_potholes"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
eoruadl/crop_crack_and_potholes
|
[
"region:us"
] |
2023-05-25T02:23:32+00:00
|
{"dataset_info": {"features": [{"name": "pixel_values", "dtype": "image"}, {"name": "label", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 89367721.592, "num_examples": 2284}, {"name": "validation", "num_bytes": 23868017.0, "num_examples": 571}], "download_size": 120998222, "dataset_size": 113235738.592}}
|
2023-05-25T04:18:17+00:00
|
08c1373c277847280b061f0913ad499cb9fb3142
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T02:25:17+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141736, "num_examples": 1000}], "download_size": 53453, "dataset_size": 141736}}
|
2023-05-26T17:12:31+00:00
|
916c596e8246d060f181e0a04a9752a7096b52c5
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T02:29:56+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141256, "num_examples": 1000}], "download_size": 53034, "dataset_size": 141256}}
|
2023-05-25T02:30:01+00:00
|
c47eed10c497059ebffed4c6ab1538e72c0182db
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_T_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T02:34:44+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141415, "num_examples": 1000}], "download_size": 53152, "dataset_size": 141415}}
|
2023-05-25T02:34:48+00:00
|
c0819e47fd55010ea4a1f4a5cbf874c918d5dd23
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_T_A_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T02:39:42+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141496, "num_examples": 1000}], "download_size": 53241, "dataset_size": 141496}}
|
2023-05-25T02:39:48+00:00
|
4a6ab34d6ac54314e51bdd41a630f825553bec46
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_A_D_PNP_GENERIC_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T02:44:39+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141464, "num_examples": 1000}], "download_size": 53158, "dataset_size": 141464}}
|
2023-05-25T03:07:54+00:00
|
19f6500675793e96283de41a37723056ab069f3d
|
wyuelin/testDataset
|
[
"license:apache-2.0",
"region:us"
] |
2023-05-25T02:53:09+00:00
|
{"license": "apache-2.0"}
|
2023-05-25T02:55:28+00:00
|
|
722d308b383bc2ab469ecc0810508359b50d7089
|
TempoFunk/big
|
[
"license:agpl-3.0",
"region:us"
] |
2023-05-25T02:59:03+00:00
|
{"license": "agpl-3.0"}
|
2023-05-25T06:38:52+00:00
|
|
39a49c4ba6e029b47453483314ae0084f2aa7179
|
yesongmin/luckyStrikeMixV5
|
[
"license:other",
"region:us"
] |
2023-05-25T03:00:04+00:00
|
{"license": "other"}
|
2023-05-25T03:12:12+00:00
|
|
2c76771d21fa5afce96688e7b96605845cf4cb9e
|
# Dataset Card for "07c1bf52"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/07c1bf52
|
[
"region:us"
] |
2023-05-25T03:08:49+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 178, "num_examples": 10}], "download_size": 1340, "dataset_size": 178}}
|
2023-05-25T03:08:50+00:00
|
1ec0f64dde9420c184e156791a2212f91f755bcc
|
# Dataset Card for "c3fa3b3b"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/c3fa3b3b
|
[
"region:us"
] |
2023-05-25T03:08:53+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 178, "num_examples": 10}], "download_size": 1340, "dataset_size": 178}}
|
2023-05-25T03:08:54+00:00
|
98857e848e9c61cc5eda1ef6bb66ae5bd228dd39
|
# Dataset Card for "skin_cancer_complete_dataset_resized_123"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Pranavkpba2000/skin_cancer_complete_dataset_resized_123
|
[
"region:us"
] |
2023-05-25T03:09:23+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "AK", "1": "BCC", "2": "BKL", "3": "DF", "4": "MEL", "5": "NV", "6": "SCC", "7": "VASC"}}}}], "splits": [{"name": "train", "num_bytes": 170043159.063, "num_examples": 28449}, {"name": "test", "num_bytes": 46642856.68, "num_examples": 7112}], "download_size": 204564103, "dataset_size": 216686015.743}}
|
2023-05-25T03:09:47+00:00
|
25715318ce573e665c243c695e2a6806fd1f009a
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_C_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_C_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T03:17:46+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 142014, "num_examples": 1000}], "download_size": 53621, "dataset_size": 142014}}
|
2023-05-25T03:26:25+00:00
|
5b1deb5e807650f7d8746a1be7bff8f66821875a
|
# Dataset Card for "en-id-parallel-sentences"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
carlesoctav/en-id-parallel-sentences
|
[
"region:us"
] |
2023-05-25T03:20:25+00:00
|
{"dataset_info": {"features": [{"name": "text_en", "dtype": "string"}, {"name": "text_id", "dtype": "string"}], "splits": [{"name": "msmarcoquery", "num_bytes": 41010003, "num_examples": 500000}, {"name": "combinedtech", "num_bytes": 44901963, "num_examples": 276659}, {"name": "msmarcocollection", "num_bytes": 351086941, "num_examples": 500000}, {"name": "TED2020", "num_bytes": 32590228, "num_examples": 163319}, {"name": "Tatoeba", "num_bytes": 797670, "num_examples": 10543}, {"name": "NeuLabTedTalks", "num_bytes": 19440416, "num_examples": 94224}, {"name": "QED", "num_bytes": 40115874, "num_examples": 274581}, {"name": "tico19", "num_bytes": 959990, "num_examples": 3071}], "download_size": 282831590, "dataset_size": 530903085}}
|
2023-05-25T03:20:44+00:00
|
4b65d0deddfae7232223f02337da56c88d525275
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_T_C_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_T_C_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T03:33:49+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 141796, "num_examples": 1000}], "download_size": 53543, "dataset_size": 141796}}
|
2023-05-25T03:33:53+00:00
|
3a23bc7dfd183140db798f3a7b7ba5a8e1820a50
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_T_A_C_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_T_A_C_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T03:39:36+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 142083, "num_examples": 1000}], "download_size": 53743, "dataset_size": 142083}}
|
2023-05-25T03:39:40+00:00
|
544ed3ea2a564ba0c401bb295cdb57c21b68951b
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_A_C_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_A_C_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T03:45:39+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 142120, "num_examples": 1000}], "download_size": 0, "dataset_size": 142120}}
|
2023-05-25T04:01:01+00:00
|
674461adfc2f1dcf9640a51e1432d554304df8be
|
# Dataset Card for "VQAv2_sample_validation_google_flan_t5_xxl_mode_C_D_PNP_GENERIC_A_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_sample_validation_google_flan_t5_xxl_mode_C_D_PNP_GENERIC_A_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T03:52:33+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 142504, "num_examples": 1000}], "download_size": 54144, "dataset_size": 142504}}
|
2023-05-25T03:52:37+00:00
|
435e1ec61ab12f8ba1b7a7fad02b8c15dfa74731
|
# Dataset Card for "fac"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
johngonzalezv/fac
|
[
"region:us"
] |
2023-05-25T03:52:58+00:00
|
{"dataset_info": {"features": [{"name": "pixel_values", "dtype": "image"}, {"name": "label", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 4992111.0, "num_examples": 4}], "download_size": 0, "dataset_size": 4992111.0}}
|
2023-05-25T04:16:20+00:00
|
3a5b8cf67cf14001925a65d12ce850c44d1b5c6a
|
# Dataset Card for "VQAv2_minival_validation_google_flan_t5_xxl_mode_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_minival_validation_google_flan_t5_xxl_mode_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T04:11:45+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 143183, "num_examples": 1000}], "download_size": 0, "dataset_size": 143183}}
|
2023-05-25T04:15:01+00:00
|
48d5411e402b7888167abde9f439690438e70c03
|
# Dataset Card for "VQAv2_minival_validation_google_flan_t5_xxl_mode_C_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_minival_validation_google_flan_t5_xxl_mode_C_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T04:16:50+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 142374, "num_examples": 1000}], "download_size": 52804, "dataset_size": 142374}}
|
2023-05-25T04:16:54+00:00
|
20db1515f3009e488351500ad7ba7665c9bb0bf3
|
# Dataset Card for "DOA_dataset_6_classes2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
FidelOdok/DOA_dataset_6_classes2
|
[
"region:us"
] |
2023-05-25T04:29:06+00:00
|
{"dataset_info": {"features": [{"name": "audio", "dtype": "audio"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "0", "1": "1", "2": "2", "3": "3", "4": "4", "5": "5", "6": "6"}}}}], "splits": [{"name": "train", "num_bytes": 24221585400.202, "num_examples": 62869}], "download_size": 24218154768, "dataset_size": 24221585400.202}}
|
2023-05-25T05:17:28+00:00
|
f836195381cabc040cbd7f5622ffa4e9a80d25cc
|
# Dataset Card for "077f7b8d"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/077f7b8d
|
[
"region:us"
] |
2023-05-25T04:39:04+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 178, "num_examples": 10}], "download_size": 1331, "dataset_size": 178}}
|
2023-05-25T04:39:05+00:00
|
6d1e20d765c9446ffabbe2f5d308b5a135963b53
|
# Dataset Card for "VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_1000"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_1000
|
[
"region:us"
] |
2023-05-25T05:07:21+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 143060, "num_examples": 1000}], "download_size": 53460, "dataset_size": 143060}}
|
2023-05-25T05:07:25+00:00
|
a8150ed07caeecc607f473af14a13aa49ea4be01
|
# Dataset Card for "ca1338a0"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
results-sd-v1-5-sd-v2-1-if-v1-0-karlo/ca1338a0
|
[
"region:us"
] |
2023-05-25T05:31:03+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 184, "num_examples": 10}], "download_size": 1338, "dataset_size": 184}}
|
2023-05-25T05:31:04+00:00
|
6760bcc999ea2bce8f5f074bfbd1b85d9bd635f8
|
# Dataset Card for "product_ads"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
coeuslearning/product_ads
|
[
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:en",
"license:openrail",
"art",
"region:us"
] |
2023-05-25T05:41:14+00:00
|
{"language": ["en"], "license": "openrail", "size_categories": ["1K<n<10K"], "task_categories": ["text-generation"], "pretty_name": "Product Ads", "dataset_info": {"features": [{"name": "name", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "ad", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 5006, "num_examples": 25}], "download_size": 6203, "dataset_size": 5006}, "tags": ["art"]}
|
2023-05-25T05:42:26+00:00
|
99c1f31cf3759a0877da93cf9c586ab9e713aef2
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
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).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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 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]
|
Crespo/llm-test
|
[
"task_categories:text-generation",
"size_categories:n<1K",
"language:en",
"license:apache-2.0",
"region:us"
] |
2023-05-25T05:48:16+00:00
|
{"language": ["en"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["text-generation"]}
|
2023-05-25T06:47:32+00:00
|
b7732098d32396fb9f690e9d50cb7f1758861305
|
https://github.com/HKUST-KnowComp/WinoWhy
```
@inproceedings{zhang2020WinoWhy,
author = {Hongming Zhang and Xinran Zhao and Yangqiu Song},
title = {WinoWhy: A Deep Diagnosis of Essential Commonsense Knowledge for Answering Winograd Schema Challenge},
booktitle = {Proceedings of Annual Meeting of the Association for Computational Linguistics (ACL) 2020},
year = {2020}
}
```
|
tasksource/winowhy
|
[
"language:en",
"license:mit",
"region:us"
] |
2023-05-25T06:02:41+00:00
|
{"language": ["en"], "license": "mit"}
|
2023-05-31T07:23:25+00:00
|
69be31fdcab1fb4019b6311ed7f12fc42e8a4b13
|
https://github.com/wangcunxiang/Sen-Making-and-Explanation
```
@inproceedings{wang-etal-2019-make,
title = "Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation",
author = "Wang, Cunxiang and
Liang, Shuailong and
Zhang, Yue and
Li, Xiaonan and
Gao, Tian",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/P19-1393",
pages = "4020--4026",
abstract = "Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system has the sense-making capability. Existing benchmarks measure common sense knowledge indirectly or without reasoning. In this paper, we release a benchmark to directly test whether a system can differentiate natural language statements that make sense from those that do not make sense. In addition, a system is asked to identify the most crucial reason why a statement does not make sense. We evaluate models trained over large-scale language modeling tasks as well as human performance, showing that there are different challenges for system sense-making.",
}
```
|
tasksource/sen-making
|
[
"task_categories:text-classification",
"task_categories:multiple-choice",
"language:en",
"explanation",
"region:us"
] |
2023-05-25T06:06:10+00:00
|
{"language": ["en"], "task_categories": ["text-classification", "multiple-choice"], "tags": ["explanation"]}
|
2023-05-31T07:22:27+00:00
|
4c89487c1503217fa1b08a31efa01bec67a442c8
|
xswu/human_preference_dataset
|
[
"license:cc-by-4.0",
"region:us"
] |
2023-05-25T06:11:12+00:00
|
{"license": "cc-by-4.0"}
|
2023-05-25T06:11:12+00:00
|
|
4967d8aaa06a4ea97a88bf77071d66be0140bc45
|
https://github.com/allenai/aristo-leaderboard/tree/master/tracie/data
```
@inproceedings{ZRNKSR21,
author = {Ben Zhou and Kyle Richardson and Qiang Ning and Tushar Khot and Ashish Sabharwal and Dan Roth},
title = {Temporal Reasoning on Implicit Events from Distant Supervision},
booktitle = {NAACL},
year = {2021},
}
```
|
tasksource/tracie
|
[
"task_categories:text-classification",
"language:en",
"license:apache-2.0",
"nli",
"region:us"
] |
2023-05-25T06:17:09+00:00
|
{"language": ["en"], "license": "apache-2.0", "task_categories": ["text-classification"], "tags": ["nli"]}
|
2023-05-31T07:26:23+00:00
|
05540fc3781bb7b0ccd1484f2070129a3fa77431
|
# Dataset Card for "dataset_combined"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
michalby24/dataset_combined
|
[
"region:us"
] |
2023-05-25T06:24:47+00:00
|
{"dataset_info": {"features": [{"name": "client_id", "dtype": "string"}, {"name": "path", "dtype": "string"}, {"name": "audio", "dtype": {"audio": {"sampling_rate": 48000}}}, {"name": "sentence", "dtype": "string"}, {"name": "up_votes", "dtype": "int64"}, {"name": "down_votes", "dtype": "int64"}, {"name": "age", "dtype": "string"}, {"name": "gender", "dtype": "string"}, {"name": "accent", "dtype": "string"}, {"name": "locale", "dtype": "string"}, {"name": "segment", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1418231642.398, "num_examples": 39509}], "download_size": 1326265217, "dataset_size": 1418231642.398}}
|
2023-05-25T06:26:22+00:00
|
7c5f851c9aca023b9d0aaa62eb96fc493f0a1b9d
|
Data of all Turkish Stock Market between dates of 28 April - 24 May 2023. The granuality of data is 1m, there is around 500 symbol, 3m rows.
You can use this data for following tasks:
- Time series prediction
- Anomaly detection
- Time series classification
- Time series clustering.
|
umarigan/stock_intraday_data
|
[
"region:us"
] |
2023-05-25T06:40:26+00:00
|
{}
|
2023-05-25T07:58:09+00:00
|
a8a95601216b92ab96897c8b464a66cc48460d4a
|
# Dataset Card for "VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_25994"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_Q_rices_ns_25994
|
[
"region:us"
] |
2023-05-25T06:46:29+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "prompt", "sequence": "string"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 325999922, "num_examples": 25994}], "download_size": 17855048, "dataset_size": 325999922}}
|
2023-06-09T05:33:52+00:00
|
4de16696e60db8af24084f7f5ac7997ab12cdf32
|
Conversation Ending Check
|
Chakshu/conversation_ender
|
[
"task_categories:text-classification",
"size_categories:n<1K",
"language:en",
"license:mit",
"Conversation",
"region:us"
] |
2023-05-25T06:57:48+00:00
|
{"language": ["en"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-classification"], "pretty_name": "Conversation Enders", "tags": ["Conversation"]}
|
2023-05-25T07:56:31+00:00
|
5975a089c57a97e8aa59798dc3eec0760914b210
|
# Dataset Card for Acapella Evaluation
## Dataset Description
- **Homepage:** <https://ccmusic-database.github.io>
- **Repository:** <https://huggingface.co/datasets/CCMUSIC/acapella_evaluation>
- **Paper:** <https://doi.org/10.5281/zenodo.5676893>
- **Leaderboard:** <https://ccmusic-database.github.io/team.html>
- **Point of Contact:** <https://www.mdpi.com/2076-3417/12/19/9931>
### Dataset Summary
This database contains 6 Mandarin song segments sung by 22 singers, totaling 132 audio clips. Each segment consists of a verse and a chorus. Four judges evaluate the singing from nine aspects which are pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance on a 10-point scale. The scores are recorded in a sheet.
### Supported Tasks and Leaderboards
Acapella evaluation/scoring
### Languages
Chinese, English
## Dataset Structure
### Data Instances
.wav & .csv
### Data Fields
song, singer id, pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance
### Data Splits
song1-6
## Dataset Creation
### Curation Rationale
Lack of a training dataset for acapella scoring system
### Source Data
#### Initial Data Collection and Normalization
Zhaorui Liu, Monan Zhou
#### Who are the source language producers?
Students and judges from CCMUSIC
### Annotations
#### Annotation process
6 Mandarin song segments were sung by 22 singers, totaling 132 audio clips. Each segment consists of a verse and a chorus. Four judges evaluate the singing from nine aspects which are pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance on a 10-point scale. The scores are recorded in a sheet.
#### Who are the annotators?
Judges from CCMUSIC
### Personal and Sensitive Information
Singers' and judges' names are hided
## Considerations for Using the Data
### Social Impact of Dataset
Providing a training dataset for acapella scoring system may improve the developement of related Apps
### Discussion of Biases
Only for Mandarin songs
### Other Known Limitations
No starting point has been marked for the vocal
## Additional Information
### Dataset Curators
Zijin Li
### Evaluation
[Li, R.; Zhang, M. Singing-Voice Timbre Evaluations Based on Transfer Learning. Appl. Sci. 2022, 12, 9931. https://doi.org/10.3390/app12199931](https://www.mdpi.com/2076-3417/12/19/9931)
### Licensing Information
```
MIT License
Copyright (c) CCMUSIC
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE 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 SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```
### Citation Information
```
@dataset{zhaorui_liu_2021_5676893,
author = {Zhaorui Liu, Monan Zhou, Shenyang Xu, Yuan Wang, Zhaowen Wang, Wei Li and Zijin Li},
title = {CCMUSIC DATABASE: A Music Data Sharing Platform for Computational Musicology Research},
month = {nov},
year = {2021},
publisher = {Zenodo},
version = {1.1},
doi = {10.5281/zenodo.5676893},
url = {https://doi.org/10.5281/zenodo.5676893}
}
```
### Contributions
Provide a training dataset for acapella scoring system
|
ccmusic-database/acapella
|
[
"task_categories:audio-classification",
"task_categories:table-question-answering",
"task_categories:summarization",
"size_categories:n<1K",
"language:zh",
"language:en",
"license:mit",
"music",
"art",
"region:us"
] |
2023-05-25T07:05:41+00:00
|
{"language": ["zh", "en"], "license": "mit", "size_categories": ["n<1K"], "task_categories": ["audio-classification", "table-question-answering", "summarization"], "pretty_name": "Acapella Evaluation Dataset", "tags": ["music", "art"], "viewer": false}
|
2023-12-24T14:16:28+00:00
|
2f6c022606d7cbfa23651a231f0e5c9f3b603ad8
|
FreedomIntelligence/HuatuoGPT-sft-data-v1
|
[
"license:apache-2.0",
"region:us"
] |
2023-05-25T07:09:22+00:00
|
{"license": "apache-2.0"}
|
2023-06-01T10:05:15+00:00
|
|
c4ee6b9ab78909729b7d00c5de5299f4662e5a64
|
Data source: https://github.com/CVI-SZU/Linly/wiki/Linly-OpenLLaMA
|
Linly-AI/Chinese-pretraining-dataset
|
[
"license:apache-2.0",
"region:us"
] |
2023-05-25T07:31:43+00:00
|
{"license": "apache-2.0"}
|
2023-05-26T01:32:06+00:00
|
259870961a3e67c2458da0cabab52b43046e4b82
|
yfqiu-nlp/xlsum-en_XX-weights
|
[
"license:mit",
"region:us"
] |
2023-05-25T07:32:39+00:00
|
{"license": "mit", "dataset_info": {"features": [{"name": "document", "dtype": "string"}, {"name": "summary", "dtype": "string"}, {"name": "weight", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 804126747, "num_examples": 278111}, {"name": "valid", "num_bytes": 31781754, "num_examples": 11535}, {"name": "test", "num_bytes": 31585040, "num_examples": 11535}], "download_size": 549436619, "dataset_size": 867493541}}
|
2023-05-25T07:53:50+00:00
|
|
0901ef1740e5e659e3c96585d45e3d888d6e8746
|
# Dataset Card for "dolly_hhrlhf"
This is the dataset from mosaic mosaicml/dolly_hhrlhf removing some duplicates found.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Abzu/dolly_hhrlhf
|
[
"task_categories:question-answering",
"task_categories:text2text-generation",
"language:en",
"license:cc-by-sa-3.0",
"region:us"
] |
2023-05-25T07:34:30+00:00
|
{"language": ["en"], "license": "cc-by-sa-3.0", "task_categories": ["question-answering", "text2text-generation"], "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 22346337.075312525, "num_examples": 35205}, {"name": "test", "num_bytes": 2483137.924687476, "num_examples": 3912}], "download_size": 16025539, "dataset_size": 24829475}}
|
2023-06-04T18:33:11+00:00
|
46b05072be13058c632486f6ba931431335f9d9c
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
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).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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 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]
|
AntonioRenatoMontefusco/second1_half
|
[
"region:us"
] |
2023-05-25T07:43:22+00:00
|
{}
|
2023-05-25T07:45:27+00:00
|
ff031e767bb43765ee554abf672a2a7cc7dc5ce6
|
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
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).
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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 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]
|
AntonioRenatoMontefusco/second2_half
|
[
"region:us"
] |
2023-05-25T07:46:41+00:00
|
{}
|
2023-05-25T07:47:59+00:00
|
88c95f799ef83a86a40b70119bc943abf2c51f9f
|
# Dataset Card for "wizard"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Abzu/wizard
|
[
"task_categories:text-generation",
"language:en",
"license:cc-by-sa-3.0",
"region:us"
] |
2023-05-25T07:58:06+00:00
|
{"language": ["en"], "license": "cc-by-sa-3.0", "task_categories": ["text-generation"], "dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 85659801.65210004, "num_examples": 49263}, {"name": "test", "num_bytes": 9518335.347899958, "num_examples": 5474}], "download_size": 50310834, "dataset_size": 95178137}}
|
2023-06-04T18:35:21+00:00
|
805a91866c7243826ae16a129e4135dc05498ca0
|
# Dataset Card for "VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_C_Q_rices_ns_25994"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
CVasNLPExperiments/VQAv2_minival_validation_google_flan_t5_xxl_mode_D_PNP_GENERIC_C_Q_rices_ns_25994
|
[
"region:us"
] |
2023-05-25T08:09:19+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "question", "dtype": "string"}, {"name": "true_label", "sequence": "string"}, {"name": "prediction", "dtype": "string"}], "splits": [{"name": "fewshot_0_clip_tags_LAION_ViT_H_14_2B_with_openai_Attributes_LAION_ViT_H_14_2B_descriptors_text_davinci_003_full_DETA_detections_deta_swin_large_o365_coco_classes_caption_all_patches_Salesforce_blip_image_captioning_large_clean_", "num_bytes": 3698359, "num_examples": 25994}], "download_size": 1326018, "dataset_size": 3698359}}
|
2023-05-25T08:09:27+00:00
|
52285125e8027250ee57b47b4d34e3ffdcf17302
|
# HWR200: New open access dataset of handwritten texts images in Russian
This is a dataset of handwritten texts images in Russian created by 200 writers with
different handwriting and photographed in different environment.
### How to download
```
pip install huggingface_hub
apt-get install git-lfs
git clone https://huggingface.co/datasets/AntiplagiatCompany/HWR200
```
### Description
* Total size is 44G
* Total number of images with text is 30030
* Number of writers is 200
* Every handwritten text is photographed in three different ways: scanned, in poor light, in good light
* Different authors could write the same texts
* Some texts are "reuses" . they have copies of sentences from other texts
### Annotation example
```
// for original texts:
{
sentences: [{id: <id>, text: <sentence>}, ...],
words_count: <word count>,
full_text: <full text>
}
// for reuse texts:
{
reuse_0: {
sentences: [{id: <id>, text: <sentence>}, ...],
id: <original text file name>
intersection_score: <intersection_score>
}
reuse_1: { // if exists
sentences: [{id: <id>, text: <sentence>}, ...],
id: <original text file name>
intersection_score: <intersection_score>
}
start clear sentences: [<sentence>, <sentence>, ...] // if exists
end clear sentences: [<sentence>, <sentence>, ...] // if exists
words_count: <word count>
full_text: <full text>
}
// for fpr texts:
{
sentences: [{id: <id>, text: <sentence>}, ...],
words_count: <word count>,
full_text: <full text>
}
```
|
AntiplagiatCompany/HWR200
|
[
"size_categories:10K<n<100K",
"language:ru",
"license:apache-2.0",
"ocr",
"htr",
"handwritten text recognition",
"near duplicate detection",
"reuse detection",
"region:us"
] |
2023-05-25T08:10:37+00:00
|
{"language": ["ru"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "pretty_name": "HWR200", "tags": ["ocr", "htr", "handwritten text recognition", "near duplicate detection", "reuse detection"]}
|
2023-05-26T05:34:51+00:00
|
e329f9ba41605ca1f7ddcbfc2b35bd2dd7304c85
|
# Dataset Card for "dolly_hhrlhf_wizard"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Abzu/dolly_hhrlhf_wizard
|
[
"region:us"
] |
2023-05-25T08:15:25+00:00
|
{"dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 108006083.60236111, "num_examples": 84468}, {"name": "test", "num_bytes": 12001528.397638885, "num_examples": 9386}], "download_size": 67011577, "dataset_size": 120007612.0}}
|
2023-05-26T07:59:42+00:00
|
b6b14090aaaf51f1ff2b4690e563dd1a6bcb5af1
|
# Dataset Card for "WISE2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
PeterPanTheGenius/WISE2
|
[
"region:us"
] |
2023-05-25T08:21:10+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 71832426.0, "num_examples": 996}], "download_size": 71786826, "dataset_size": 71832426.0}}
|
2023-05-25T08:21:25+00:00
|
f6c588cbc2e234bf896cdfa7354c87533f4ce2b4
|
# Dataset Card for "news_channel_all_text"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
james-burton/news_channel_all_text
|
[
"region:us"
] |
2023-05-25T08:29:31+00:00
|
{"dataset_info": {"features": [{"name": " n_tokens_content", "dtype": "string"}, {"name": " n_unique_tokens", "dtype": "string"}, {"name": " n_non_stop_words", "dtype": "string"}, {"name": " n_non_stop_unique_tokens", "dtype": "string"}, {"name": " num_hrefs", "dtype": "string"}, {"name": " num_self_hrefs", "dtype": "string"}, {"name": " num_imgs", "dtype": "string"}, {"name": " num_videos", "dtype": "string"}, {"name": " average_token_length", "dtype": "string"}, {"name": " num_keywords", "dtype": "string"}, {"name": " global_subjectivity", "dtype": "string"}, {"name": " global_sentiment_polarity", "dtype": "string"}, {"name": " global_rate_positive_words", "dtype": "string"}, {"name": " global_rate_negative_words", "dtype": "string"}, {"name": " rate_positive_words", "dtype": "string"}, {"name": " rate_negative_words", "dtype": "string"}, {"name": "article_title", "dtype": "string"}, {"name": "channel", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 4893096, "num_examples": 17241}, {"name": "validation", "num_bytes": 863581, "num_examples": 3043}, {"name": "test", "num_bytes": 1439606, "num_examples": 5071}], "download_size": 3921037, "dataset_size": 7196283}}
|
2023-05-25T08:29:43+00:00
|
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