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6a3a471b8cb086aafafc0e97da2da1d2485228dc
|
# Dataset Card for "synthdog_en_barcode"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
hansihe/synthdog_en_barcode
|
[
"region:us"
] |
2023-08-20T21:14:55+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "validation", "num_bytes": 103858986.269, "num_examples": 1051}, {"name": "train", "num_bytes": 770921261.76, "num_examples": 7932}, {"name": "test", "num_bytes": 92140975.673, "num_examples": 1017}], "download_size": 949514062, "dataset_size": 966921223.702}, "configs": [{"config_name": "default", "data_files": [{"split": "validation", "path": "data/validation-*"}, {"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-20T21:16:19+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "synthdog_en_barcode"
More Information needed
|
[
"# Dataset Card for \"synthdog_en_barcode\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"synthdog_en_barcode\"\n\nMore Information needed"
] |
[
6,
18
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"synthdog_en_barcode\"\n\nMore Information needed"
] |
98176e288cb5dfabd620e419435fb2cc7ec57e0b
|
# Dataset Card for "dataset_kabyle"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
ad019el/dataset_kabyle
|
[
"region:us"
] |
2023-08-20T21:41:50+00:00
|
{"dataset_info": {"features": [{"name": "path", "dtype": "string"}, {"name": "audio", "dtype": {"audio": {"sampling_rate": 16000}}}, {"name": "sentence", "dtype": "string"}, {"name": "sentence_ar", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 44154966.0, "num_examples": 1500}, {"name": "test", "num_bytes": 15731788.0, "num_examples": 500}], "download_size": 58865938, "dataset_size": 59886754.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]}
|
2023-08-29T15:52:08+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "dataset_kabyle"
More Information needed
|
[
"# Dataset Card for \"dataset_kabyle\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"dataset_kabyle\"\n\nMore Information needed"
] |
[
6,
15
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"dataset_kabyle\"\n\nMore Information needed"
] |
f9404b4252a6cbdad60c12e40dada2a2233ca31f
|
# Dataset Card for "FindSumAll"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
jessiedu314/FindSumAll
|
[
"region:us"
] |
2023-08-20T21:42:04+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": "document", "dtype": "string"}, {"name": "summary", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1142199650, "num_examples": 83254}, {"name": "validation", "num_bytes": 142621982, "num_examples": 10405}, {"name": "test", "num_bytes": 142826827, "num_examples": 10405}], "download_size": 635119558, "dataset_size": 1427648459}}
|
2023-08-20T21:42:32+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "FindSumAll"
More Information needed
|
[
"# Dataset Card for \"FindSumAll\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"FindSumAll\"\n\nMore Information needed"
] |
[
6,
14
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"FindSumAll\"\n\nMore Information needed"
] |
63ff41dc726bdb5036ff58e5a086901f857c5f84
|
# Dataset of kumano/熊野/熊野 (Kantai Collection)
This is the dataset of kumano/熊野/熊野 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, long_hair, ponytail, blue_eyes, hair_ornament`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 521.51 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kumano_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 336.58 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kumano_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1197 | 711.79 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kumano_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 479.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kumano_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1197 | 943.57 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kumano_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kumano_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 9 |  |  |  |  |  | 1girl, solo, looking_at_viewer, cowboy_shot, simple_background, white_background, breasts, green_eyes, competition_swimsuit, navel, smile, white_bikini |
| 1 | 9 |  |  |  |  |  | 1girl, blush, looking_at_viewer, solo, collarbone, cowboy_shot, hair_between_eyes, navel, simple_background, small_breasts, white_background, white_panties, underwear_only |
| 2 | 5 |  |  |  |  |  | 1girl, day, looking_at_viewer, navel, outdoors, solo, beach, cloud, cowboy_shot, medium_breasts, ocean, small_breasts, smile, blue_sky, collarbone, one-piece_swimsuit, slingshot_swimsuit, white_bikini |
| 3 | 17 |  |  |  |  |  | 1girl, brown_jacket, brown_skirt, pleated_skirt, school_uniform, blazer, frilled_skirt, red_bowtie, solo, shirt, smile, cowboy_shot, long_sleeves, brown_cardigan, simple_background, white_background, brown_thighhighs, open_mouth, hair_between_eyes, ribbon |
| 4 | 6 |  |  |  |  |  | 1girl, blazer, brown_jacket, brown_skirt, pleated_skirt, school_uniform, solo, cowboy_shot, looking_at_viewer, red_bowtie, simple_background, white_background, brown_cardigan, frilled_skirt, green_eyes, dated, one-hour_drawing_challenge, smile |
| 5 | 13 |  |  |  |  |  | 1girl, brown_jacket, red_bowtie, school_uniform, solo, upper_body, blazer, simple_background, white_background, smile, brown_cardigan, looking_at_viewer, green_eyes, hair_between_eyes, one-hour_drawing_challenge, open_mouth |
| 6 | 6 |  |  |  |  |  | 1girl, ascot, brown_thighhighs, pleated_skirt, school_uniform, solo, white_background, blazer, blush, brown_skirt, looking_at_viewer, simple_background, long_sleeves, open_mouth, sitting, smile, shirt |
| 7 | 9 |  |  |  |  |  | 2girls, blazer, brown_jacket, red_bowtie, school_uniform, white_background, simple_background, brown_cardigan, brown_skirt, open_mouth, pleated_skirt, shirt, solo_focus, upper_body, blush, green_eyes, green_hair, smile |
| 8 | 6 |  |  |  |  |  | 1girl, aqua_eyes, school_uniform, skirt, solo, thighhighs, turret, looking_at_viewer, smile, blush, open_mouth |
| 9 | 8 |  |  |  |  |  | blue_bowtie, collared_shirt, school_uniform, white_shirt, black_jacket, black_skirt, blazer, long_sleeves, pleated_skirt, smile, 1girl, open_mouth, sweater_vest, blush, hair_between_eyes, hair_ribbon, outdoors, solo_focus, 2girls, kneehighs, official_alternate_costume, school_bag, simple_background |
| 10 | 6 |  |  |  |  |  | 1girl, blush, nipples, navel, open_mouth, pussy, solo, brown_thighhighs, censored, looking_at_viewer, medium_breasts, nude, spread_legs, sweat, on_back, shirt, small_breasts |
| 11 | 13 |  |  |  |  |  | fake_animal_ears, playboy_bunny, rabbit_ears, strapless_leotard, detached_collar, wrist_cuffs, 1girl, rabbit_tail, black_leotard, medium_breasts, cowboy_shot, fake_tail, looking_at_viewer, black_pantyhose, green_eyes, red_bowtie, 2girls, fishnet_pantyhose, open_mouth, solo_focus, white_background |
| 12 | 14 |  |  |  |  |  | red_dress, santa_costume, 2girls, red_gloves, smile, christmas, belt, fur-trimmed_capelet, looking_at_viewer, red_capelet, solo_focus, hair_between_eyes, open_mouth, blush, fur-trimmed_dress |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | looking_at_viewer | cowboy_shot | simple_background | white_background | breasts | green_eyes | competition_swimsuit | navel | smile | white_bikini | blush | collarbone | hair_between_eyes | small_breasts | white_panties | underwear_only | day | outdoors | beach | cloud | medium_breasts | ocean | blue_sky | one-piece_swimsuit | slingshot_swimsuit | brown_jacket | brown_skirt | pleated_skirt | school_uniform | blazer | frilled_skirt | red_bowtie | shirt | long_sleeves | brown_cardigan | brown_thighhighs | open_mouth | ribbon | dated | one-hour_drawing_challenge | upper_body | ascot | sitting | 2girls | solo_focus | green_hair | aqua_eyes | skirt | thighhighs | turret | blue_bowtie | collared_shirt | white_shirt | black_jacket | black_skirt | sweater_vest | hair_ribbon | kneehighs | official_alternate_costume | school_bag | nipples | pussy | censored | nude | spread_legs | sweat | on_back | fake_animal_ears | playboy_bunny | rabbit_ears | strapless_leotard | detached_collar | wrist_cuffs | rabbit_tail | black_leotard | fake_tail | black_pantyhose | fishnet_pantyhose | red_dress | santa_costume | red_gloves | christmas | belt | fur-trimmed_capelet | red_capelet | fur-trimmed_dress |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:-------|:--------------------|:--------------|:--------------------|:-------------------|:----------|:-------------|:-----------------------|:--------|:--------|:---------------|:--------|:-------------|:--------------------|:----------------|:----------------|:-----------------|:------|:-----------|:--------|:--------|:-----------------|:--------|:-----------|:---------------------|:---------------------|:---------------|:--------------|:----------------|:-----------------|:---------|:----------------|:-------------|:--------|:---------------|:-----------------|:-------------------|:-------------|:---------|:--------|:-----------------------------|:-------------|:--------|:----------|:---------|:-------------|:-------------|:------------|:--------|:-------------|:---------|:--------------|:-----------------|:--------------|:---------------|:--------------|:---------------|:--------------|:------------|:-----------------------------|:-------------|:----------|:--------|:-----------|:-------|:--------------|:--------|:----------|:-------------------|:----------------|:--------------|:--------------------|:------------------|:--------------|:--------------|:----------------|:------------|:------------------|:--------------------|:------------|:----------------|:-------------|:------------|:-------|:----------------------|:--------------|:--------------------|
| 0 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 9 |  |  |  |  |  | X | X | X | X | X | X | | | | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | X | X | X | | | | | | X | X | X | | X | | X | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 17 |  |  |  |  |  | X | X | | X | X | X | | | | | X | | | | X | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | X | X | X | X | X | | X | | | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | X | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 13 |  |  |  |  |  | X | X | X | | X | X | | X | | | X | | | | X | | | | | | | | | | | | | X | | | X | X | | X | | | X | | X | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | X | X | X | | X | X | | | | | X | | X | | | | | | | | | | | | | | | | X | X | X | X | | | X | X | | X | X | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 9 |  |  |  |  |  | | | | | X | X | | X | | | X | | X | | | | | | | | | | | | | | | X | X | X | X | X | | X | X | | X | | X | | | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 6 |  |  |  |  |  | X | X | X | | | | | | | | X | | X | | | | | | | | | | | | | | | | | | X | | | | | | | | X | | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 8 |  |  |  |  |  | X | | | | X | | | | | | X | | X | | X | | | | | X | | | | | | | | | | X | X | X | | | | X | | | X | | | | | | | X | X | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 6 |  |  |  |  |  | X | X | X | | | | | | | X | | | X | | | X | | | | | | | X | | | | | | | | | | | | X | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | |
| 11 | 13 |  |  |  |  |  | X | | X | X | | X | | X | | | | | | | | | | | | | | | X | | | | | | | | | | | X | | | | | X | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | |
| 12 | 14 |  |  |  |  |  | | | X | | | | | | | | X | | X | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X |
|
CyberHarem/kumano_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T21:47:15+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T03:27:37+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kumano/熊野/熊野 (Kantai Collection)
===========================================
This is the dataset of kumano/熊野/熊野 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, long\_hair, ponytail, blue\_eyes, hair\_ornament', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
2c1d5c6884a0913ccd1f6c5add158d39125f4dea
|
Chinese version of [Samantha data](https://huggingface.co/datasets/ehartford/samantha-data)
Some changes, a few names are choosen instead of the default Theodore and Samantha. This should provide some kind of flexibity for changing names during inference
|
theblackcat102/her-zh-hant
|
[
"language:zh",
"region:us"
] |
2023-08-20T21:56:08+00:00
|
{"language": ["zh"]}
|
2023-08-25T07:57:07+00:00
|
[] |
[
"zh"
] |
TAGS
#language-Chinese #region-us
|
Chinese version of Samantha data
Some changes, a few names are choosen instead of the default Theodore and Samantha. This should provide some kind of flexibity for changing names during inference
|
[] |
[
"TAGS\n#language-Chinese #region-us \n"
] |
[
11
] |
[
"passage: TAGS\n#language-Chinese #region-us \n"
] |
63d0d2410b98a5c363d82cd4094b8c49fc93b0a2
|
# Dataset of kirishima/霧島 (Kantai Collection)
This is the dataset of kirishima/霧島 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `short_hair, black_hair, glasses, hairband, green-framed_eyewear, breasts, headgear, large_breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 533.32 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kirishima_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 336.85 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kirishima_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1071 | 655.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kirishima_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 482.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kirishima_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1071 | 868.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kirishima_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kirishima_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 9 |  |  |  |  |  | 1girl, adjusting_eyewear, blue_eyes, detached_sleeves, japanese_clothes, nontraditional_miko, smile, solo, bare_shoulders, looking_at_viewer, skirt |
| 1 | 32 |  |  |  |  |  | 1girl, detached_sleeves, japanese_clothes, nontraditional_miko, skirt, solo, thighhighs, bare_shoulders, thigh_boots, smile, adjusting_eyewear, pantyhose, turret, blue_eyes, cannon, ribbon_trim |
| 2 | 17 |  |  |  |  |  | 1girl, detached_sleeves, japanese_clothes, nontraditional_miko, ribbon-trimmed_sleeves, solo, looking_at_viewer, white_background, upper_body, simple_background, adjusting_eyewear, smile, bare_shoulders, grey_eyes, twitter_username |
| 3 | 12 |  |  |  |  |  | 1girl, collarbone, looking_at_viewer, navel, solo, cowboy_shot, black_bikini, cleavage, smile, white_background, day, side-tie_bikini_bottom, sky |
| 4 | 9 |  |  |  |  |  | 1girl, alternate_costume, solo, collarbone, green_shirt, looking_at_viewer, smile, simple_background, white_background, brown_jacket, cleavage, twitter_username |
| 5 | 10 |  |  |  |  |  | 1boy, 1girl, blush, hetero, penis, solo_focus, japanese_clothes, nipples, open_mouth, tongue, blue_eyes, facial, fellatio, bare_shoulders, detached_sleeves, mosaic_censoring, paizuri |
| 6 | 10 |  |  |  |  |  | 1boy, 1girl, hetero, nipples, open_mouth, sex, blush, solo_focus, vaginal, black_eyes, open_clothes, penis, censored, cowgirl_position, detached_sleeves, girl_on_top, semi-rimless_eyewear, thighhighs, medium_breasts, navel, no_panties, pussy, skirt |
| 7 | 13 |  |  |  |  |  | 1girl, smile, alternate_costume, looking_at_viewer, naval_uniform, solo, epaulettes, white_background, short_sleeves, red-framed_eyewear, cowboy_shot, peaked_cap, simple_background, skirt, white_headwear, white_shirt |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | adjusting_eyewear | blue_eyes | detached_sleeves | japanese_clothes | nontraditional_miko | smile | solo | bare_shoulders | looking_at_viewer | skirt | thighhighs | thigh_boots | pantyhose | turret | cannon | ribbon_trim | ribbon-trimmed_sleeves | white_background | upper_body | simple_background | grey_eyes | twitter_username | collarbone | navel | cowboy_shot | black_bikini | cleavage | day | side-tie_bikini_bottom | sky | alternate_costume | green_shirt | brown_jacket | 1boy | blush | hetero | penis | solo_focus | nipples | open_mouth | tongue | facial | fellatio | mosaic_censoring | paizuri | sex | vaginal | black_eyes | open_clothes | censored | cowgirl_position | girl_on_top | semi-rimless_eyewear | medium_breasts | no_panties | pussy | naval_uniform | epaulettes | short_sleeves | red-framed_eyewear | peaked_cap | white_headwear | white_shirt |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:------------|:-------------------|:-------------------|:----------------------|:--------|:-------|:-----------------|:--------------------|:--------|:-------------|:--------------|:------------|:---------|:---------|:--------------|:-------------------------|:-------------------|:-------------|:--------------------|:------------|:-------------------|:-------------|:--------|:--------------|:---------------|:-----------|:------|:-------------------------|:------|:--------------------|:--------------|:---------------|:-------|:--------|:---------|:--------|:-------------|:----------|:-------------|:---------|:---------|:-----------|:-------------------|:----------|:------|:----------|:-------------|:---------------|:-----------|:-------------------|:--------------|:-----------------------|:-----------------|:-------------|:--------|:----------------|:-------------|:----------------|:---------------------|:-------------|:-----------------|:--------------|
| 0 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 32 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 17 |  |  |  |  |  | X | X | | X | X | X | X | X | X | X | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 12 |  |  |  |  |  | X | | | | | | X | X | | X | | | | | | | | | X | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 9 |  |  |  |  |  | X | | | | | | X | X | | X | | | | | | | | | X | | X | | X | X | | | | X | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 10 |  |  |  |  |  | X | | X | X | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | |
| 6 | 10 |  |  |  |  |  | X | | | X | | | | | | | X | X | | | | | | | | | | | | | X | | | | | | | | | | X | X | X | X | X | X | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | |
| 7 | 13 |  |  |  |  |  | X | | | | | | X | X | | X | X | | | | | | | | X | | X | | | | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X |
|
CyberHarem/kirishima_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T22:03:28+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T00:04:21+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kirishima/霧島 (Kantai Collection)
===========================================
This is the dataset of kirishima/霧島 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'short\_hair, black\_hair, glasses, hairband, green-framed\_eyewear, breasts, headgear, large\_breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
8fdaf7631897d17cbf851ca2007e47b6a746adf8
|
My dataset for training SDXL & SD 1.5
|
raoulduke420/matt-training-img
|
[
"task_categories:feature-extraction",
"task_categories:image-classification",
"language:en",
"license:artistic-2.0",
"art",
"code",
"region:us"
] |
2023-08-20T22:21:25+00:00
|
{"language": ["en"], "license": "artistic-2.0", "task_categories": ["feature-extraction", "image-classification"], "pretty_name": "mattdilworth", "tags": ["art", "code"]}
|
2023-08-21T00:32:59+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-feature-extraction #task_categories-image-classification #language-English #license-artistic-2.0 #art #code #region-us
|
My dataset for training SDXL & SD 1.5
|
[] |
[
"TAGS\n#task_categories-feature-extraction #task_categories-image-classification #language-English #license-artistic-2.0 #art #code #region-us \n"
] |
[
45
] |
[
"passage: TAGS\n#task_categories-feature-extraction #task_categories-image-classification #language-English #license-artistic-2.0 #art #code #region-us \n"
] |
547a34107ef113077534e6c9139e6bd5f44f3db0
|
# AutoTrain Dataset for project: twitter-disaster-v2
## Dataset Description
This dataset has been automatically processed by AutoTrain for project twitter-disaster-v2.
### Languages
The BCP-47 code for the dataset's language is en.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"feat_id": 1,
"feat_keyword": null,
"feat_location": null,
"text": "Our Deeds are the Reason of this #earthquake May ALLAH Forgive us all",
"target": 1
},
{
"feat_id": 4,
"feat_keyword": null,
"feat_location": null,
"text": "Forest fire near La Ronge Sask. Canada",
"target": 1
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"feat_id": "Value(dtype='int64', id=None)",
"feat_keyword": "Value(dtype='string', id=None)",
"feat_location": "Value(dtype='string', id=None)",
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(names=['0', '1'], id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 7613 |
| valid | 0 |
|
startificial/autotrain-data-twitter-disaster-v2
|
[
"task_categories:text-classification",
"language:en",
"region:us"
] |
2023-08-20T22:22:24+00:00
|
{"language": ["en"], "task_categories": ["text-classification"]}
|
2023-08-20T22:23:34+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-text-classification #language-English #region-us
|
AutoTrain Dataset for project: twitter-disaster-v2
==================================================
Dataset Description
-------------------
This dataset has been automatically processed by AutoTrain for project twitter-disaster-v2.
### Languages
The BCP-47 code for the dataset's language is en.
Dataset Structure
-----------------
### Data Instances
A sample from this dataset looks as follows:
### Dataset Fields
The dataset has the following fields (also called "features"):
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
|
[
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
[
"TAGS\n#task_categories-text-classification #language-English #region-us \n",
"### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
[
21,
26,
17,
23,
27
] |
[
"passage: TAGS\n#task_categories-text-classification #language-English #region-us \n### Languages\n\n\nThe BCP-47 code for the dataset's language is en.\n\n\nDataset Structure\n-----------------### Data Instances\n\n\nA sample from this dataset looks as follows:### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
0832a3b647581d75de4a36f3936223e8f6253408
|
# Dataset of atlanta/アトランタ (Kantai Collection)
This is the dataset of atlanta/アトランタ (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, long_hair, two_side_up, breasts, large_breasts, grey_eyes, star_earrings, earrings, hat, black_headwear, garrison_cap, hair_ornament, single_earring`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 712.42 MiB | [Download](https://huggingface.co/datasets/CyberHarem/atlanta_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 373.28 MiB | [Download](https://huggingface.co/datasets/CyberHarem/atlanta_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1332 | 894.11 MiB | [Download](https://huggingface.co/datasets/CyberHarem/atlanta_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 624.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/atlanta_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1332 | 1.30 GiB | [Download](https://huggingface.co/datasets/CyberHarem/atlanta_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/atlanta_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 22 |  |  |  |  |  | 1girl, black_skirt, high-waist_skirt, jewelry, long_sleeves, partially_fingerless_gloves, solo, star_(symbol), suspender_skirt, white_shirt, white_gloves, dress_shirt, looking_at_viewer, simple_background, white_background, anchor_hair_ornament, blush, cowboy_shot, thigh_strap, bra_visible_through_clothes, garter_straps |
| 1 | 5 |  |  |  |  |  | 1girl, anchor_hair_ornament, black_footwear, black_skirt, boots, dress_shirt, garter_straps, high-waist_skirt, jewelry, long_sleeves, partially_fingerless_gloves, solo, star_(symbol), suspender_skirt, white_gloves, white_shirt, rudder_footwear, thigh_strap, white_background, simple_background, full_body, looking_at_viewer |
| 2 | 5 |  |  |  |  |  | 1boy, 1girl, black_skirt, blush, hetero, high-waist_skirt, jewelry, long_sleeves, partially_fingerless_gloves, penis, star_(symbol), suspender_skirt, vaginal, white_shirt, clothed_sex, solo_focus, anchor_hair_ornament, bar_censor, dress_shirt, spread_legs, thigh_strap, white_gloves |
| 3 | 12 |  |  |  |  |  | 1boy, 1girl, hetero, solo_focus, jewelry, long_sleeves, star_(symbol), white_shirt, blush, censored, nipples, paizuri, partially_fingerless_gloves, penis, breasts_squeezed_together, white_gloves, suspenders, cum, open_shirt |
| 4 | 15 |  |  |  |  |  | 1girl, solo, looking_at_viewer, jewelry, navel, star_(symbol), blush, simple_background, bikini, cleavage, cowboy_shot, white_background, collarbone, twitter_username, alternate_costume, white_shirt |
| 5 | 13 |  |  |  |  |  | 1boy, 1girl, hetero, solo_focus, blush, completely_nude, nipples, star_(symbol), penis, collarbone, jewelry, navel, sex, vaginal, open_mouth, sweat, bar_censor, cum_in_pussy, bangs, girl_on_top, looking_at_viewer, straddling |
| 6 | 5 |  |  |  |  |  | 1girl, jewelry, looking_at_viewer, solo, star_(symbol), underwear_only, black_panties, blush, simple_background, ass, black_bra, wariza, cleavage, thong, white_background |
| 7 | 16 |  |  |  |  |  | 1girl, solo, star_(symbol), black_sweater, long_sleeves, coat, blush, looking_at_viewer, anchor_hair_ornament, official_alternate_costume, ribbed_sweater, turtleneck_sweater, necklace, skirt, holding, simple_background |
| 8 | 6 |  |  |  |  |  | 1girl, jewelry, pregnant, solo, star_(symbol), white_panties, big_belly, underwear_only, gradient_background, nipples, topless, cowboy_shot, english_text, navel |
| 9 | 9 |  |  |  |  |  | 1girl, competition_swimsuit, solo, highleg_swimsuit, looking_at_viewer, covered_navel, cowboy_shot, star_(symbol), jewelry, black_one-piece_swimsuit, blush, collarbone, dated, simple_background, spread_legs, white_background |
| 10 | 28 |  |  |  |  |  | 1girl, black_panties, star_(symbol), white_gloves, crop_top, elbow_gloves, jewelry, shimakaze_(kancolle)_(cosplay), solo, highleg_panties, blush, navel, black_hairband, black_neckerchief, simple_background, blue_skirt, serafuku, white_background, pleated_skirt, striped_thighhighs, looking_at_viewer, microskirt, blue_sailor_collar, twitter_username, underboob, anchor_hair_ornament, cowboy_shot, miniskirt |
| 11 | 5 |  |  |  |  |  | 1girl, alternate_costume, black_gloves, blush, looking_at_viewer, solo, black_thighhighs, blue_eyes, elbow_gloves, latex_gloves, micro_bikini, nurse_cap, shiny_clothes, star_(symbol), bangs, black_bikini, garter_straps, holding_syringe, jewelry, underwear, ass, latex_legwear, sitting, thigh_boots, thighs |
| 12 | 21 |  |  |  |  |  | 1girl, official_alternate_costume, pom_pom_(clothes), red_headwear, santa_costume, santa_hat, solo, red_capelet, star_(symbol), dress, jewelry, long_sleeves, fur-trimmed_capelet, cleavage, thigh_strap, blush, simple_background, white_background, neck_bell, belt, christmas, black_footwear, sitting |
| 13 | 17 |  |  |  |  |  | 1girl, rabbit_ears, fake_animal_ears, playboy_bunny, solo, star_(symbol), alternate_costume, detached_collar, jewelry, wrist_cuffs, black_leotard, bowtie, looking_at_viewer, strapless_leotard, blush, rabbit_tail, fake_tail, simple_background, black_pantyhose, white_background, cleavage, cowboy_shot, gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_skirt | high-waist_skirt | jewelry | long_sleeves | partially_fingerless_gloves | solo | star_(symbol) | suspender_skirt | white_shirt | white_gloves | dress_shirt | looking_at_viewer | simple_background | white_background | anchor_hair_ornament | blush | cowboy_shot | thigh_strap | bra_visible_through_clothes | garter_straps | black_footwear | boots | rudder_footwear | full_body | 1boy | hetero | penis | vaginal | clothed_sex | solo_focus | bar_censor | spread_legs | censored | nipples | paizuri | breasts_squeezed_together | suspenders | cum | open_shirt | navel | bikini | cleavage | collarbone | twitter_username | alternate_costume | completely_nude | sex | open_mouth | sweat | cum_in_pussy | bangs | girl_on_top | straddling | underwear_only | black_panties | ass | black_bra | wariza | thong | black_sweater | coat | official_alternate_costume | ribbed_sweater | turtleneck_sweater | necklace | skirt | holding | pregnant | white_panties | big_belly | gradient_background | topless | english_text | competition_swimsuit | highleg_swimsuit | covered_navel | black_one-piece_swimsuit | dated | crop_top | elbow_gloves | shimakaze_(kancolle)_(cosplay) | highleg_panties | black_hairband | black_neckerchief | blue_skirt | serafuku | pleated_skirt | striped_thighhighs | microskirt | blue_sailor_collar | underboob | miniskirt | black_gloves | black_thighhighs | blue_eyes | latex_gloves | micro_bikini | nurse_cap | shiny_clothes | black_bikini | holding_syringe | underwear | latex_legwear | sitting | thigh_boots | thighs | pom_pom_(clothes) | red_headwear | santa_costume | santa_hat | red_capelet | dress | fur-trimmed_capelet | neck_bell | belt | christmas | rabbit_ears | fake_animal_ears | playboy_bunny | detached_collar | wrist_cuffs | black_leotard | bowtie | strapless_leotard | rabbit_tail | fake_tail | black_pantyhose | gloves |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------------|:-------------------|:----------|:---------------|:------------------------------|:-------|:----------------|:------------------|:--------------|:---------------|:--------------|:--------------------|:--------------------|:-------------------|:-----------------------|:--------|:--------------|:--------------|:------------------------------|:----------------|:-----------------|:--------|:------------------|:------------|:-------|:---------|:--------|:----------|:--------------|:-------------|:-------------|:--------------|:-----------|:----------|:----------|:----------------------------|:-------------|:------|:-------------|:--------|:---------|:-----------|:-------------|:-------------------|:--------------------|:------------------|:------|:-------------|:--------|:---------------|:--------|:--------------|:-------------|:-----------------|:----------------|:------|:------------|:---------|:--------|:----------------|:-------|:-----------------------------|:-----------------|:---------------------|:-----------|:--------|:----------|:-----------|:----------------|:------------|:----------------------|:----------|:---------------|:-----------------------|:-------------------|:----------------|:---------------------------|:--------|:-----------|:---------------|:---------------------------------|:------------------|:-----------------|:--------------------|:-------------|:-----------|:----------------|:---------------------|:-------------|:---------------------|:------------|:------------|:---------------|:-------------------|:------------|:---------------|:---------------|:------------|:----------------|:---------------|:------------------|:------------|:----------------|:----------|:--------------|:---------|:--------------------|:---------------|:----------------|:------------|:--------------|:--------|:----------------------|:------------|:-------|:------------|:--------------|:-------------------|:----------------|:------------------|:--------------|:----------------|:---------|:--------------------|:--------------|:------------|:------------------|:---------|
| 0 | 22 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | X | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | X | X | X | X | X | | X | X | X | X | X | | | | X | X | | X | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 12 |  |  |  |  |  | X | | | X | X | X | | X | | X | X | | | | | | X | | | | | | | | | X | X | X | | | X | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 15 |  |  |  |  |  | X | | | X | | | X | X | | X | | | X | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 13 |  |  |  |  |  | X | | | X | | | | X | | | | | X | | | | X | | | | | | | | | X | X | X | X | | X | X | | | X | | | | | | X | | | X | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | | | X | | | X | X | | | | | X | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 16 |  |  |  |  |  | X | | | | X | | X | X | | | | | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 6 |  |  |  |  |  | X | | | X | | | X | X | | | | | | | | | | X | | | | | | | | | | | | | | | | | X | | | | | | X | | | | | | | | | | | | | | X | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 9 |  |  |  |  |  | X | | | X | | | X | X | | | | | X | X | X | | X | X | | | | | | | | | | | | | | | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 28 |  |  |  |  |  | X | | | X | | | X | X | | | X | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | X | | | | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 11 | 5 |  |  |  |  |  | X | | | X | | | X | X | | | | | X | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | |
| 12 | 21 |  |  |  |  |  | X | | | X | X | | X | X | | | | | | X | X | | X | | X | | | X | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 13 | 17 |  |  |  |  |  | X | | | X | | | X | X | | | | | X | X | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/atlanta_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T22:32:57+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T14:38:34+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of atlanta/アトランタ (Kantai Collection)
============================================
This is the dataset of atlanta/アトランタ (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, long\_hair, two\_side\_up, breasts, large\_breasts, grey\_eyes, star\_earrings, earrings, hat, black\_headwear, garrison\_cap, hair\_ornament, single\_earring', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
7b69578861ffebcab0eae531c2732b3f91f70068
|
# Dataset of gotland/ゴトランド (Kantai Collection)
This is the dataset of gotland/ゴトランド (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `blue_hair, long_hair, mole, mole_under_eye, blue_eyes, hair_between_eyes, breasts, hair_bun, single_hair_bun`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 613.09 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gotland_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 348.78 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gotland_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1182 | 749.97 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gotland_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 542.71 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gotland_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1182 | 1.04 GiB | [Download](https://huggingface.co/datasets/CyberHarem/gotland_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/gotland_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 8 |  |  |  |  |  | 1girl, black_necktie, blue_skirt, collared_shirt, half_gloves, long_sleeves, looking_at_viewer, military_uniform, smile, solo, white_gloves, belt, simple_background, thigh_strap |
| 1 | 20 |  |  |  |  |  | 1girl, blue_sailor_collar, long_sleeves, military_uniform, solo, white_gloves, half_gloves, black_neckerchief, looking_at_viewer, simple_background, upper_body, white_background, blue_skirt, smile |
| 2 | 6 |  |  |  |  |  | 1girl, looking_at_viewer, sidelocks, solo, white_background, alternate_costume, simple_background, upper_body, blush, long_sleeves, smile, pink_shirt |
| 3 | 9 |  |  |  |  |  | 1girl, solo, employee_uniform, long_sleeves, vertical-striped_shirt, blue_shirt, looking_at_viewer, smile, heart, skirt, blush, collared_shirt, thighhighs |
| 4 | 19 |  |  |  |  |  | 1girl, santa_hat, long_sleeves, santa_costume, solo, grey_gloves, red_headwear, white_thighhighs, christmas, sheep, looking_at_viewer, smile, blush, fur_trim, open_mouth, red_dress, sack, simple_background |
| 5 | 9 |  |  |  |  |  | 1girl, solo, blue_one-piece_swimsuit, competition_swimsuit, cowboy_shot, looking_at_viewer, blush, highleg_swimsuit, ponytail, smile, wet, ass, open_mouth, looking_back, medium_breasts, water |
| 6 | 17 |  |  |  |  |  | 1girl, hair_flower, solo, looking_at_viewer, medium_breasts, navel, collarbone, smile, blush, brown_bikini, ponytail, cleavage, sarong, bracelet, necklace, open_mouth, cowboy_shot, simple_background, thigh_strap |
| 7 | 5 |  |  |  |  |  | 1girl, cleavage, large_breasts, looking_at_viewer, simple_background, solo, white_background, blue_bikini, cowboy_shot, side-tie_bikini_bottom, twitter_username, collarbone, navel, sitting, smile, dated, groin, one-hour_drawing_challenge |
| 8 | 7 |  |  |  |  |  | 1girl, long_sleeves, solo, blue_coat, blush, closed_mouth, gift_box, holding_gift, official_alternate_costume, smile, looking_at_viewer, open_coat, simple_background, valentine, white_background, black_headwear, blue_dress, boots, gradient_background, hat, heart-shaped_chocolate, high_heels, nail_polish |
| 9 | 6 |  |  |  |  |  | 1girl, looking_at_viewer, pleated_skirt, serafuku, solo, alternate_costume, blue_sailor_collar, blue_skirt, neckerchief, shirt, smile, black_skirt, kneehighs, short_sleeves, white_background |
| 10 | 5 |  |  |  |  |  | 1girl, black_gloves, blue_skirt, cropped_jacket, midriff, navel, race_queen, solo, white_jacket, white_panties, cleavage, cowboy_shot, half_gloves, headphones, headset, highleg_panties, large_breasts, looking_at_viewer, bandeau, blue_sky, cloud, day, miniskirt, official_alternate_costume, outdoors, ponytail, simple_background, standing, white_background |
| 11 | 13 |  |  |  |  |  | 1girl, blue_skirt, cropped_jacket, headphones, looking_at_viewer, midriff, race_queen, solo, white_jacket, cleavage, headset, miniskirt, navel, smile, bandeau, black_gloves, cowboy_shot, official_alternate_costume, half_gloves, microphone, one_eye_closed, thigh_strap, holding, large_breasts, open_mouth, ponytail, umbrella |
| 12 | 5 |  |  |  |  |  | 1girl, blue_skirt, cleavage, looking_at_viewer, medium_breasts, midriff, miniskirt, navel, race_queen, smile, thighhighs, white_gloves, bandeau, cropped_jacket, garrison_cap, official_alternate_costume, solo, thigh_boots, white_jacket, blue_headwear, one_eye_closed, checkered_background |
| 13 | 5 |  |  |  |  |  | 1girl, enmaided, frilled_apron, looking_at_viewer, maid_apron, maid_headdress, solo, white_apron, simple_background, black_dress, smile, twitter_username, white_background, blue_background, cowboy_shot, juliet_sleeves, one_eye_closed, short_sleeves, sidelocks, white_thighhighs, wrist_cuffs, zettai_ryouiki |
| 14 | 7 |  |  |  |  |  | 1girl, alternate_costume, long_sleeves, looking_at_viewer, obi, solo, blue_kimono, floral_print, holding, smile, wide_sleeves, yukata, blush, hair_flower, open_mouth, print_kimono, upper_body |
| 15 | 11 |  |  |  |  |  | 1girl, fake_animal_ears, playboy_bunny, rabbit_ears, solo, looking_at_viewer, detached_collar, strapless_leotard, medium_breasts, ponytail, wrist_cuffs, alternate_costume, bowtie, cleavage, cowboy_shot, black_leotard, black_pantyhose, blue_leotard, rabbit_tail, simple_background, white_background, drinking_glass, fake_tail, large_breasts |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_necktie | blue_skirt | collared_shirt | half_gloves | long_sleeves | looking_at_viewer | military_uniform | smile | solo | white_gloves | belt | simple_background | thigh_strap | blue_sailor_collar | black_neckerchief | upper_body | white_background | sidelocks | alternate_costume | blush | pink_shirt | employee_uniform | vertical-striped_shirt | blue_shirt | heart | skirt | thighhighs | santa_hat | santa_costume | grey_gloves | red_headwear | white_thighhighs | christmas | sheep | fur_trim | open_mouth | red_dress | sack | blue_one-piece_swimsuit | competition_swimsuit | cowboy_shot | highleg_swimsuit | ponytail | wet | ass | looking_back | medium_breasts | water | hair_flower | navel | collarbone | brown_bikini | cleavage | sarong | bracelet | necklace | large_breasts | blue_bikini | side-tie_bikini_bottom | twitter_username | sitting | dated | groin | one-hour_drawing_challenge | blue_coat | closed_mouth | gift_box | holding_gift | official_alternate_costume | open_coat | valentine | black_headwear | blue_dress | boots | gradient_background | hat | heart-shaped_chocolate | high_heels | nail_polish | pleated_skirt | serafuku | neckerchief | shirt | black_skirt | kneehighs | short_sleeves | black_gloves | cropped_jacket | midriff | race_queen | white_jacket | white_panties | headphones | headset | highleg_panties | bandeau | blue_sky | cloud | day | miniskirt | outdoors | standing | microphone | one_eye_closed | holding | umbrella | garrison_cap | thigh_boots | blue_headwear | checkered_background | enmaided | frilled_apron | maid_apron | maid_headdress | white_apron | black_dress | blue_background | juliet_sleeves | wrist_cuffs | zettai_ryouiki | obi | blue_kimono | floral_print | wide_sleeves | yukata | print_kimono | fake_animal_ears | playboy_bunny | rabbit_ears | detached_collar | strapless_leotard | bowtie | black_leotard | black_pantyhose | blue_leotard | rabbit_tail | drinking_glass | fake_tail |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:----------------|:-------------|:-----------------|:--------------|:---------------|:--------------------|:-------------------|:--------|:-------|:---------------|:-------|:--------------------|:--------------|:---------------------|:--------------------|:-------------|:-------------------|:------------|:--------------------|:--------|:-------------|:-------------------|:-------------------------|:-------------|:--------|:--------|:-------------|:------------|:----------------|:--------------|:---------------|:-------------------|:------------|:--------|:-----------|:-------------|:------------|:-------|:--------------------------|:-----------------------|:--------------|:-------------------|:-----------|:------|:------|:---------------|:-----------------|:--------|:--------------|:--------|:-------------|:---------------|:-----------|:---------|:-----------|:-----------|:----------------|:--------------|:-------------------------|:-------------------|:----------|:--------|:--------|:-----------------------------|:------------|:---------------|:-----------|:---------------|:-----------------------------|:------------|:------------|:-----------------|:-------------|:--------|:----------------------|:------|:-------------------------|:-------------|:--------------|:----------------|:-----------|:--------------|:--------|:--------------|:------------|:----------------|:---------------|:-----------------|:----------|:-------------|:---------------|:----------------|:-------------|:----------|:------------------|:----------|:-----------|:--------|:------|:------------|:-----------|:-----------|:-------------|:-----------------|:----------|:-----------|:---------------|:--------------|:----------------|:-----------------------|:-----------|:----------------|:-------------|:-----------------|:--------------|:--------------|:------------------|:-----------------|:--------------|:-----------------|:------|:--------------|:---------------|:---------------|:---------|:---------------|:-------------------|:----------------|:--------------|:------------------|:--------------------|:---------|:----------------|:------------------|:---------------|:--------------|:-----------------|:------------|
| 0 | 8 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 20 |  |  |  |  |  | X | | X | | X | X | X | X | X | X | X | | X | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | | | | | X | X | | X | X | | | X | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 9 |  |  |  |  |  | X | | | X | | X | X | | X | X | | | | | | | | | | | X | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 19 |  |  |  |  |  | X | | | | | X | X | | X | X | | | X | | | | | | | | X | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 9 |  |  |  |  |  | X | | | | | | X | | X | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 17 |  |  |  |  |  | X | | | | | | X | | X | X | | | X | X | | | | | | | X | | | | | | | | | | | | | | | | X | | | | | X | | X | | | | X | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 5 |  |  |  |  |  | X | | | | | | X | | X | X | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | X | X | | X | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | | | | X | X | | X | X | | | X | | | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 6 |  |  |  |  |  | X | | X | | | | X | | X | X | | | | | X | | | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 5 |  |  |  |  |  | X | | X | | X | | X | | | X | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | | | X | | | X | | | | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 11 | 13 |  |  |  |  |  | X | | X | | X | | X | | X | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | X | | | | | X | | X | | | | | | | X | | | X | | | | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | X | X | X | X | X | | X | X | | X | | | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 12 | 5 |  |  |  |  |  | X | | X | | | | X | | X | X | X | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | X | | | X | | | X | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | | | | | X | | | | X | | | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 13 | 5 |  |  |  |  |  | X | | | | | | X | | X | X | | | X | | | | | X | X | | | | | | | | | | | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | X | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | |
| 14 | 7 |  |  |  |  |  | X | | | | | X | X | | X | X | | | | | | | X | | | X | X | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | |
| 15 | 11 |  |  |  |  |  | X | | | | | | X | | | X | | | X | | | | | X | | X | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | X | | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/gotland_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T22:54:56+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T16:29:32+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of gotland/ゴトランド (Kantai Collection)
============================================
This is the dataset of gotland/ゴトランド (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'blue\_hair, long\_hair, mole, mole\_under\_eye, blue\_eyes, hair\_between\_eyes, breasts, hair\_bun, single\_hair\_bun', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
91b8736dc08412f8230332fcb3fb504076f5464f
|
# Subreddit r/maau Dataset
This dataset contains a collection of comments and responses from the r/maau subreddit, centered around various topics and discussions. The dataset is intended to be used for natural language processing tasks, such as question-answering and dialogue generation. Each entry in the dataset consists of an instruction, context, response, and category.
## Dataset Information
- **Name:** Subreddit r/maau Dataset
- **Format:** JSON Lines
- **Size:** 5.6k entries
- **License:** [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/)
- **Language:** Spanish
## Instructions
The dataset is structured as follows:
```json
{"instruction": "instruction_text", "context": "context_text", "response": "response_text", "category": "category_name"}
```
- `instruction`: The instruction or query provided by a user in the subreddit.
- `context`: Additional context or information related to the instruction (if available).
- `response`: The response or answer to the instruction.
- `category`: The category or type of the interaction, often indicating the nature of the discussion.
## Example Entries
1. **Instruction:** "yo cuando 366 días del año"
- **Context:** ""
- **Response:** "El siguiente año es bisiesto"
- **Category:** "open_qa"
2. **Instruction:** "El siguiente año es bisiesto"
- **Context:** ""
- **Response:** "pero no este"
- **Category:** "open_qa"
3. **Instruction:** "pero no este"
- **Context:** ""
- **Response:** "Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día"
- **Category:** "open_qa"
4. **Instruction:** "Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día"
- **Context:** ""
- **Response:** "pero por lo general si hablas de un año te refieres a 365 días"
- **Category:** "open_qa"
5. **Instruction:** "Espera ese es scott??"
- **Context:** ""
- **Response:** "Sip ya ta viejito"
- **Category:** "open_qa"
## Potential Use Cases
- **Question-Answering:** Use the dataset to train models to answer questions based on the given instructions and contexts.
- **Dialogue Generation:** Train chatbots or dialogue systems using the dataset's conversational structure.
- **Sentiment Analysis:** Analyze the sentiment of responses in various categories.
- **Language Understanding:** Build models to understand the language used in the subreddit discussions.
## Citation
If you use this dataset in your research or projects, please consider citing it as follows:
```bibtex
@dataset{subreddit-maau-dataset,
title = {Subreddit r/maau Dataset},
author = {ElWapoteDev},
year = {2023},
publisher = {HuggingFace},
howpublished = {{https://huggingface.co/datasets/ElWapoteDev/subreddit-maau}},
}
```
|
ElWapoteDev/subreddit-maau
|
[
"region:us"
] |
2023-08-20T23:10:43+00:00
|
{}
|
2023-08-21T00:56:00+00:00
|
[] |
[] |
TAGS
#region-us
|
# Subreddit r/maau Dataset
This dataset contains a collection of comments and responses from the r/maau subreddit, centered around various topics and discussions. The dataset is intended to be used for natural language processing tasks, such as question-answering and dialogue generation. Each entry in the dataset consists of an instruction, context, response, and category.
## Dataset Information
- Name: Subreddit r/maau Dataset
- Format: JSON Lines
- Size: 5.6k entries
- License: Creative Commons Attribution-ShareAlike 4.0 International License
- Language: Spanish
## Instructions
The dataset is structured as follows:
- 'instruction': The instruction or query provided by a user in the subreddit.
- 'context': Additional context or information related to the instruction (if available).
- 'response': The response or answer to the instruction.
- 'category': The category or type of the interaction, often indicating the nature of the discussion.
## Example Entries
1. Instruction: "yo cuando 366 días del año"
- Context: ""
- Response: "El siguiente año es bisiesto"
- Category: "open_qa"
2. Instruction: "El siguiente año es bisiesto"
- Context: ""
- Response: "pero no este"
- Category: "open_qa"
3. Instruction: "pero no este"
- Context: ""
- Response: "Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día"
- Category: "open_qa"
4. Instruction: "Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día"
- Context: ""
- Response: "pero por lo general si hablas de un año te refieres a 365 días"
- Category: "open_qa"
5. Instruction: "Espera ese es scott??"
- Context: ""
- Response: "Sip ya ta viejito"
- Category: "open_qa"
## Potential Use Cases
- Question-Answering: Use the dataset to train models to answer questions based on the given instructions and contexts.
- Dialogue Generation: Train chatbots or dialogue systems using the dataset's conversational structure.
- Sentiment Analysis: Analyze the sentiment of responses in various categories.
- Language Understanding: Build models to understand the language used in the subreddit discussions.
If you use this dataset in your research or projects, please consider citing it as follows:
|
[
"# Subreddit r/maau Dataset\n\nThis dataset contains a collection of comments and responses from the r/maau subreddit, centered around various topics and discussions. The dataset is intended to be used for natural language processing tasks, such as question-answering and dialogue generation. Each entry in the dataset consists of an instruction, context, response, and category.",
"## Dataset Information\n\n- Name: Subreddit r/maau Dataset\n- Format: JSON Lines\n- Size: 5.6k entries\n- License: Creative Commons Attribution-ShareAlike 4.0 International License\n- Language: Spanish",
"## Instructions\n\nThe dataset is structured as follows:\n\n\n\n\n- 'instruction': The instruction or query provided by a user in the subreddit.\n- 'context': Additional context or information related to the instruction (if available).\n- 'response': The response or answer to the instruction.\n- 'category': The category or type of the interaction, often indicating the nature of the discussion.",
"## Example Entries\n\n1. Instruction: \"yo cuando 366 días del año\"\n - Context: \"\"\n - Response: \"El siguiente año es bisiesto\"\n - Category: \"open_qa\"\n\n2. Instruction: \"El siguiente año es bisiesto\"\n - Context: \"\"\n - Response: \"pero no este\"\n - Category: \"open_qa\"\n\n3. Instruction: \"pero no este\"\n - Context: \"\"\n - Response: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Category: \"open_qa\"\n\n4. Instruction: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Context: \"\"\n - Response: \"pero por lo general si hablas de un año te refieres a 365 días\"\n - Category: \"open_qa\"\n\n5. Instruction: \"Espera ese es scott??\"\n - Context: \"\"\n - Response: \"Sip ya ta viejito\"\n - Category: \"open_qa\"",
"## Potential Use Cases\n\n- Question-Answering: Use the dataset to train models to answer questions based on the given instructions and contexts.\n- Dialogue Generation: Train chatbots or dialogue systems using the dataset's conversational structure.\n- Sentiment Analysis: Analyze the sentiment of responses in various categories.\n- Language Understanding: Build models to understand the language used in the subreddit discussions.\n\nIf you use this dataset in your research or projects, please consider citing it as follows:"
] |
[
"TAGS\n#region-us \n",
"# Subreddit r/maau Dataset\n\nThis dataset contains a collection of comments and responses from the r/maau subreddit, centered around various topics and discussions. The dataset is intended to be used for natural language processing tasks, such as question-answering and dialogue generation. Each entry in the dataset consists of an instruction, context, response, and category.",
"## Dataset Information\n\n- Name: Subreddit r/maau Dataset\n- Format: JSON Lines\n- Size: 5.6k entries\n- License: Creative Commons Attribution-ShareAlike 4.0 International License\n- Language: Spanish",
"## Instructions\n\nThe dataset is structured as follows:\n\n\n\n\n- 'instruction': The instruction or query provided by a user in the subreddit.\n- 'context': Additional context or information related to the instruction (if available).\n- 'response': The response or answer to the instruction.\n- 'category': The category or type of the interaction, often indicating the nature of the discussion.",
"## Example Entries\n\n1. Instruction: \"yo cuando 366 días del año\"\n - Context: \"\"\n - Response: \"El siguiente año es bisiesto\"\n - Category: \"open_qa\"\n\n2. Instruction: \"El siguiente año es bisiesto\"\n - Context: \"\"\n - Response: \"pero no este\"\n - Category: \"open_qa\"\n\n3. Instruction: \"pero no este\"\n - Context: \"\"\n - Response: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Category: \"open_qa\"\n\n4. Instruction: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Context: \"\"\n - Response: \"pero por lo general si hablas de un año te refieres a 365 días\"\n - Category: \"open_qa\"\n\n5. Instruction: \"Espera ese es scott??\"\n - Context: \"\"\n - Response: \"Sip ya ta viejito\"\n - Category: \"open_qa\"",
"## Potential Use Cases\n\n- Question-Answering: Use the dataset to train models to answer questions based on the given instructions and contexts.\n- Dialogue Generation: Train chatbots or dialogue systems using the dataset's conversational structure.\n- Sentiment Analysis: Analyze the sentiment of responses in various categories.\n- Language Understanding: Build models to understand the language used in the subreddit discussions.\n\nIf you use this dataset in your research or projects, please consider citing it as follows:"
] |
[
6,
88,
46,
95,
225,
114
] |
[
"passage: TAGS\n#region-us \n# Subreddit r/maau Dataset\n\nThis dataset contains a collection of comments and responses from the r/maau subreddit, centered around various topics and discussions. The dataset is intended to be used for natural language processing tasks, such as question-answering and dialogue generation. Each entry in the dataset consists of an instruction, context, response, and category.## Dataset Information\n\n- Name: Subreddit r/maau Dataset\n- Format: JSON Lines\n- Size: 5.6k entries\n- License: Creative Commons Attribution-ShareAlike 4.0 International License\n- Language: Spanish## Instructions\n\nThe dataset is structured as follows:\n\n\n\n\n- 'instruction': The instruction or query provided by a user in the subreddit.\n- 'context': Additional context or information related to the instruction (if available).\n- 'response': The response or answer to the instruction.\n- 'category': The category or type of the interaction, often indicating the nature of the discussion.## Example Entries\n\n1. Instruction: \"yo cuando 366 días del año\"\n - Context: \"\"\n - Response: \"El siguiente año es bisiesto\"\n - Category: \"open_qa\"\n\n2. Instruction: \"El siguiente año es bisiesto\"\n - Context: \"\"\n - Response: \"pero no este\"\n - Category: \"open_qa\"\n\n3. Instruction: \"pero no este\"\n - Context: \"\"\n - Response: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Category: \"open_qa\"\n\n4. Instruction: \"Pero el reto termina el 4 de junio nor lo cual de ahuevo se suma un día\"\n - Context: \"\"\n - Response: \"pero por lo general si hablas de un año te refieres a 365 días\"\n - Category: \"open_qa\"\n\n5. Instruction: \"Espera ese es scott??\"\n - Context: \"\"\n - Response: \"Sip ya ta viejito\"\n - Category: \"open_qa\""
] |
81901c46a4aeaa616594064396e9cd80b6e18ae8
|
# Dataset of furutaka/古鷹 (Kantai Collection)
This is the dataset of furutaka/古鷹 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, short_hair, yellow_eyes, glowing_eye, heterochromia, hair_ornament, hairclip, brown_eyes, breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 432.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/furutaka_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 300.75 MiB | [Download](https://huggingface.co/datasets/CyberHarem/furutaka_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1118 | 610.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/furutaka_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 403.76 MiB | [Download](https://huggingface.co/datasets/CyberHarem/furutaka_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1118 | 777.57 MiB | [Download](https://huggingface.co/datasets/CyberHarem/furutaka_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/furutaka_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, brown_sweater, glowing, official_alternate_costume, looking_at_viewer, smile, solo, open_mouth, white_shirt, collared_shirt, grey_skirt, heart, simple_background, upper_body |
| 1 | 11 |  |  |  |  |  | 1girl, glowing, serafuku, solo, upper_body, looking_at_viewer, red_neckerchief, blue_sailor_collar, smile, white_background, simple_background |
| 2 | 12 |  |  |  |  |  | 1girl, glowing, serafuku, single_elbow_glove, solo, looking_at_viewer, red_neckerchief, black_gloves, blush, bodysuit, blue_sailor_collar, upper_body, open_mouth, simple_background, short_sleeves, smile, white_background |
| 3 | 10 |  |  |  |  |  | 1girl, blue_skirt, bodysuit, pleated_skirt, red_neckerchief, serafuku, single_elbow_glove, single_thighhigh, solo, blue_sailor_collar, cowboy_shot, glowing, black_gloves, black_thighhighs, covered_navel, simple_background, smile, white_background, hair_between_eyes, looking_at_viewer, blush, short_sleeves |
| 4 | 7 |  |  |  |  |  | 1girl, blue_skirt, glowing, pleated_skirt, serafuku, single_thighhigh, solo, blue_sailor_collar, bodysuit, single_kneehigh, full_body, red_neckerchief, single_elbow_glove, uneven_legwear, white_background, simple_background, smile, black_gloves, looking_at_viewer, sitting |
| 5 | 6 |  |  |  |  |  | 1girl, blue_kimono, obi, smile, hair_between_eyes, solo, yukata, floral_print, looking_at_viewer, official_alternate_costume, wide_sleeves, dated, glowing, hair_flower, open_mouth, twitter_username, upper_body |
| 6 | 7 |  |  |  |  |  | cowboy_shot, 1girl, cleavage, glowing, looking_at_viewer, solo, smile, blue_bikini, collarbone, large_breasts, leaning_forward, medium_breasts, navel, simple_background |
| 7 | 11 |  |  |  |  |  | 1boy, 1girl, blush, hetero, nipples, solo_focus, cum_in_pussy, penis, sex, vaginal, censored, heart, medium_breasts, nude, open_mouth, sweat, glowing, navel, smile, lying, spread_legs |
| 8 | 7 |  |  |  |  |  | detached_collar, fake_animal_ears, glowing, playboy_bunny, rabbit_ears, strapless_leotard, wrist_cuffs, 1girl, black_leotard, solo, cleavage, cowboy_shot, medium_breasts, white_background, alternate_costume, black_bowtie, black_pantyhose, brown_pantyhose, fake_tail, rabbit_tail, smile, twitter_username |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | brown_sweater | glowing | official_alternate_costume | looking_at_viewer | smile | solo | open_mouth | white_shirt | collared_shirt | grey_skirt | heart | simple_background | upper_body | serafuku | red_neckerchief | blue_sailor_collar | white_background | single_elbow_glove | black_gloves | blush | bodysuit | short_sleeves | blue_skirt | pleated_skirt | single_thighhigh | cowboy_shot | black_thighhighs | covered_navel | hair_between_eyes | single_kneehigh | full_body | uneven_legwear | sitting | blue_kimono | obi | yukata | floral_print | wide_sleeves | dated | hair_flower | twitter_username | cleavage | blue_bikini | collarbone | large_breasts | leaning_forward | medium_breasts | navel | 1boy | hetero | nipples | solo_focus | cum_in_pussy | penis | sex | vaginal | censored | nude | sweat | lying | spread_legs | detached_collar | fake_animal_ears | playboy_bunny | rabbit_ears | strapless_leotard | wrist_cuffs | black_leotard | alternate_costume | black_bowtie | black_pantyhose | brown_pantyhose | fake_tail | rabbit_tail |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:----------------|:----------|:-----------------------------|:--------------------|:--------|:-------|:-------------|:--------------|:-----------------|:-------------|:--------|:--------------------|:-------------|:-----------|:------------------|:---------------------|:-------------------|:---------------------|:---------------|:--------|:-----------|:----------------|:-------------|:----------------|:-------------------|:--------------|:-------------------|:----------------|:--------------------|:------------------|:------------|:-----------------|:----------|:--------------|:------|:---------|:---------------|:---------------|:--------|:--------------|:-------------------|:-----------|:--------------|:-------------|:----------------|:------------------|:-----------------|:--------|:-------|:---------|:----------|:-------------|:---------------|:--------|:------|:----------|:-----------|:-------|:--------|:--------|:--------------|:------------------|:-------------------|:----------------|:--------------|:--------------------|:--------------|:----------------|:--------------------|:---------------|:------------------|:------------------|:------------|:--------------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 11 |  |  |  |  |  | X | | X | | X | X | X | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 12 |  |  |  |  |  | X | | X | | X | X | X | X | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 10 |  |  |  |  |  | X | | X | | X | X | X | | | | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 7 |  |  |  |  |  | X | | X | | X | X | X | | | | | | X | | X | X | X | X | X | X | | X | | X | X | X | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | | X | X | X | X | X | X | | | | | | X | | | | | | | | | | | | | | | | X | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | | X | | X | X | X | | | | | | X | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 11 |  |  |  |  |  | X | | X | | | X | | X | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | X | | | X | X | | | | | | | | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | X | X | | | | | X | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/furutaka_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T23:16:23+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T09:09:44+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of furutaka/古鷹 (Kantai Collection)
==========================================
This is the dataset of furutaka/古鷹 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, short\_hair, yellow\_eyes, glowing\_eye, heterochromia, hair\_ornament, hairclip, brown\_eyes, breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
dc0287e7ee671992188dd306e62d4214d7f9aed9
|
# MAAU Subreddit Memes Dataset
## Table of Contents
- [Introduction](#introduction)
- [Dataset Description](#dataset-description)
- [Data Collection](#data-collection)
- [Dataset Structure](#dataset-structure)
- [Usage](#usage)
- [Citation](#citation)
- [Acknowledgments](#acknowledgments)
## Introduction
Welcome to the MAAU Subreddit Memes Dataset! This dataset contains a collection of comments and responses from the subreddit [r/MAAU](https://www.reddit.com/r/MAAU/). The subreddit focuses on humorous and lighthearted content, primarily centered around memes. The dataset is intended to be a valuable resource for natural language processing (NLP) tasks related to Spanish language text analysis, sentiment analysis, and meme-related research.
## Dataset Description
The MAAU Subreddit Memes Dataset is a compilation of comments and responses from the [r/MAAU](https://www.reddit.com/r/MAAU/) subreddit. The subreddit is dedicated to sharing and discussing humorous content, including memes, jokes, and satirical posts. The dataset is provided in the Parquet format, making it efficient for storage and retrieval.
## Data Collection
The dataset was collected using a Python script that fetches posts and comments from the [r/MAAU](https://www.reddit.com/r/MAAU/) subreddit. The Python script utilized the Reddit API to access the desired content. The data collection process involved retrieving a variety of comments and responses in Spanish that showcase the unique humor and style of the subreddit.
## Dataset Structure
The dataset consists of text entries representing comments and responses from the [r/MAAU](https://www.reddit.com/r/MAAU/) subreddit. Each entry is enclosed within a pair of tags `<s>` and `</s>`, denoting the beginning and end of a comment or response. Below is an example of the dataset structure:
```txt
<s>[INST] Todo, ya fallamos como especie, no hay nada que podamos hacer para detenerlo [/INST] Mejor nos extingamos</s>
<s>[INST] Awebo que ya inicie una 3ra Guerra Mundial [/INST] Ya quiero ver los COD que saldran gracias a eso </s>
<s>[INST] A m me reportaron un post por delito de odio xd era un delfn dibujando una esvstica (basado) [/INST] si bro que gracioso, apoco si tiln sigue contndonos</s>
```
The dataset is provided in the Parquet format, ensuring efficient storage and easy integration with various data processing frameworks.
## Usage
The MAAU Subreddit Memes Dataset can be used for various NLP tasks, including but not limited to:
- Sentiment analysis of meme comments.
- Humor detection and classification.
- Language generation and text generation.
- Style analysis of informal online text.
Researchers and developers are encouraged to explore and experiment with the dataset to derive insights and create innovative NLP applications.
## Citation
If you use the MAAU Subreddit Memes Dataset in your research or projects, please consider citing it as follows:
```bibtex
@dataset{maau-memes-dataset,
title = {MAAU Subreddit Memes Dataset},
author = {ElWapoteDev},
year = {2023},
publisher = {HuggingFace},
howpublished = {https://huggingface.co/datasets/ElWapoteDev/parquet-subreddit-maau},
}
```
## Acknowledgments
We would like to express our gratitude to the members of the [r/MAAU](https://www.reddit.com/r/MAAU/) subreddit for creating and sharing the content that makes this dataset possible. Additionally, we thank the HuggingFace community for their support in hosting and sharing the dataset.
---
*Disclaimer: This dataset is for research and educational purposes only. The content is generated by users of the [r/MAAU](https://www.reddit.com/r/MAAU/) subreddit and may contain humor, satire, and unconventional language. Use discretion when analyzing and interpreting the data.*
|
ElWapoteDev/parquet-subreddit-maau
|
[
"region:us"
] |
2023-08-20T23:42:43+00:00
|
{}
|
2023-08-20T23:55:40+00:00
|
[] |
[] |
TAGS
#region-us
|
# MAAU Subreddit Memes Dataset
!MAAU Subreddit
## Table of Contents
- Introduction
- Dataset Description
- Data Collection
- Dataset Structure
- Usage
- Citation
- Acknowledgments
## Introduction
Welcome to the MAAU Subreddit Memes Dataset! This dataset contains a collection of comments and responses from the subreddit r/MAAU. The subreddit focuses on humorous and lighthearted content, primarily centered around memes. The dataset is intended to be a valuable resource for natural language processing (NLP) tasks related to Spanish language text analysis, sentiment analysis, and meme-related research.
## Dataset Description
The MAAU Subreddit Memes Dataset is a compilation of comments and responses from the r/MAAU subreddit. The subreddit is dedicated to sharing and discussing humorous content, including memes, jokes, and satirical posts. The dataset is provided in the Parquet format, making it efficient for storage and retrieval.
## Data Collection
The dataset was collected using a Python script that fetches posts and comments from the r/MAAU subreddit. The Python script utilized the Reddit API to access the desired content. The data collection process involved retrieving a variety of comments and responses in Spanish that showcase the unique humor and style of the subreddit.
## Dataset Structure
The dataset consists of text entries representing comments and responses from the r/MAAU subreddit. Each entry is enclosed within a pair of tags '<s>' and '</s>', denoting the beginning and end of a comment or response. Below is an example of the dataset structure:
The dataset is provided in the Parquet format, ensuring efficient storage and easy integration with various data processing frameworks.
## Usage
The MAAU Subreddit Memes Dataset can be used for various NLP tasks, including but not limited to:
- Sentiment analysis of meme comments.
- Humor detection and classification.
- Language generation and text generation.
- Style analysis of informal online text.
Researchers and developers are encouraged to explore and experiment with the dataset to derive insights and create innovative NLP applications.
If you use the MAAU Subreddit Memes Dataset in your research or projects, please consider citing it as follows:
## Acknowledgments
We would like to express our gratitude to the members of the r/MAAU subreddit for creating and sharing the content that makes this dataset possible. Additionally, we thank the HuggingFace community for their support in hosting and sharing the dataset.
---
*Disclaimer: This dataset is for research and educational purposes only. The content is generated by users of the r/MAAU subreddit and may contain humor, satire, and unconventional language. Use discretion when analyzing and interpreting the data.*
|
[
"# MAAU Subreddit Memes Dataset\n\n!MAAU Subreddit",
"## Table of Contents\n\n- Introduction\n- Dataset Description\n- Data Collection\n- Dataset Structure\n- Usage\n- Citation\n- Acknowledgments",
"## Introduction\n\nWelcome to the MAAU Subreddit Memes Dataset! This dataset contains a collection of comments and responses from the subreddit r/MAAU. The subreddit focuses on humorous and lighthearted content, primarily centered around memes. The dataset is intended to be a valuable resource for natural language processing (NLP) tasks related to Spanish language text analysis, sentiment analysis, and meme-related research.",
"## Dataset Description\n\nThe MAAU Subreddit Memes Dataset is a compilation of comments and responses from the r/MAAU subreddit. The subreddit is dedicated to sharing and discussing humorous content, including memes, jokes, and satirical posts. The dataset is provided in the Parquet format, making it efficient for storage and retrieval.",
"## Data Collection\n\nThe dataset was collected using a Python script that fetches posts and comments from the r/MAAU subreddit. The Python script utilized the Reddit API to access the desired content. The data collection process involved retrieving a variety of comments and responses in Spanish that showcase the unique humor and style of the subreddit.",
"## Dataset Structure\n\nThe dataset consists of text entries representing comments and responses from the r/MAAU subreddit. Each entry is enclosed within a pair of tags '<s>' and '</s>', denoting the beginning and end of a comment or response. Below is an example of the dataset structure:\n\n\n\nThe dataset is provided in the Parquet format, ensuring efficient storage and easy integration with various data processing frameworks.",
"## Usage\n\nThe MAAU Subreddit Memes Dataset can be used for various NLP tasks, including but not limited to:\n\n- Sentiment analysis of meme comments.\n- Humor detection and classification.\n- Language generation and text generation.\n- Style analysis of informal online text.\n\nResearchers and developers are encouraged to explore and experiment with the dataset to derive insights and create innovative NLP applications.\n\nIf you use the MAAU Subreddit Memes Dataset in your research or projects, please consider citing it as follows:",
"## Acknowledgments\n\nWe would like to express our gratitude to the members of the r/MAAU subreddit for creating and sharing the content that makes this dataset possible. Additionally, we thank the HuggingFace community for their support in hosting and sharing the dataset.\n\n---\n\n*Disclaimer: This dataset is for research and educational purposes only. The content is generated by users of the r/MAAU subreddit and may contain humor, satire, and unconventional language. Use discretion when analyzing and interpreting the data.*"
] |
[
"TAGS\n#region-us \n",
"# MAAU Subreddit Memes Dataset\n\n!MAAU Subreddit",
"## Table of Contents\n\n- Introduction\n- Dataset Description\n- Data Collection\n- Dataset Structure\n- Usage\n- Citation\n- Acknowledgments",
"## Introduction\n\nWelcome to the MAAU Subreddit Memes Dataset! This dataset contains a collection of comments and responses from the subreddit r/MAAU. The subreddit focuses on humorous and lighthearted content, primarily centered around memes. The dataset is intended to be a valuable resource for natural language processing (NLP) tasks related to Spanish language text analysis, sentiment analysis, and meme-related research.",
"## Dataset Description\n\nThe MAAU Subreddit Memes Dataset is a compilation of comments and responses from the r/MAAU subreddit. The subreddit is dedicated to sharing and discussing humorous content, including memes, jokes, and satirical posts. The dataset is provided in the Parquet format, making it efficient for storage and retrieval.",
"## Data Collection\n\nThe dataset was collected using a Python script that fetches posts and comments from the r/MAAU subreddit. The Python script utilized the Reddit API to access the desired content. The data collection process involved retrieving a variety of comments and responses in Spanish that showcase the unique humor and style of the subreddit.",
"## Dataset Structure\n\nThe dataset consists of text entries representing comments and responses from the r/MAAU subreddit. Each entry is enclosed within a pair of tags '<s>' and '</s>', denoting the beginning and end of a comment or response. Below is an example of the dataset structure:\n\n\n\nThe dataset is provided in the Parquet format, ensuring efficient storage and easy integration with various data processing frameworks.",
"## Usage\n\nThe MAAU Subreddit Memes Dataset can be used for various NLP tasks, including but not limited to:\n\n- Sentiment analysis of meme comments.\n- Humor detection and classification.\n- Language generation and text generation.\n- Style analysis of informal online text.\n\nResearchers and developers are encouraged to explore and experiment with the dataset to derive insights and create innovative NLP applications.\n\nIf you use the MAAU Subreddit Memes Dataset in your research or projects, please consider citing it as follows:",
"## Acknowledgments\n\nWe would like to express our gratitude to the members of the r/MAAU subreddit for creating and sharing the content that makes this dataset possible. Additionally, we thank the HuggingFace community for their support in hosting and sharing the dataset.\n\n---\n\n*Disclaimer: This dataset is for research and educational purposes only. The content is generated by users of the r/MAAU subreddit and may contain humor, satire, and unconventional language. Use discretion when analyzing and interpreting the data.*"
] |
[
6,
16,
33,
98,
82,
75,
101,
116,
126
] |
[
"passage: TAGS\n#region-us \n# MAAU Subreddit Memes Dataset\n\n!MAAU Subreddit## Table of Contents\n\n- Introduction\n- Dataset Description\n- Data Collection\n- Dataset Structure\n- Usage\n- Citation\n- Acknowledgments## Introduction\n\nWelcome to the MAAU Subreddit Memes Dataset! This dataset contains a collection of comments and responses from the subreddit r/MAAU. The subreddit focuses on humorous and lighthearted content, primarily centered around memes. The dataset is intended to be a valuable resource for natural language processing (NLP) tasks related to Spanish language text analysis, sentiment analysis, and meme-related research.## Dataset Description\n\nThe MAAU Subreddit Memes Dataset is a compilation of comments and responses from the r/MAAU subreddit. The subreddit is dedicated to sharing and discussing humorous content, including memes, jokes, and satirical posts. The dataset is provided in the Parquet format, making it efficient for storage and retrieval.## Data Collection\n\nThe dataset was collected using a Python script that fetches posts and comments from the r/MAAU subreddit. The Python script utilized the Reddit API to access the desired content. The data collection process involved retrieving a variety of comments and responses in Spanish that showcase the unique humor and style of the subreddit.## Dataset Structure\n\nThe dataset consists of text entries representing comments and responses from the r/MAAU subreddit. Each entry is enclosed within a pair of tags '<s>' and '</s>', denoting the beginning and end of a comment or response. Below is an example of the dataset structure:\n\n\n\nThe dataset is provided in the Parquet format, ensuring efficient storage and easy integration with various data processing frameworks."
] |
ba39c1f5cec47894aaf75a553f5599ecbf8e5445
|
# Dataset of hiryuu/飛龍 (Kantai Collection)
This is the dataset of hiryuu/飛龍 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `short_hair, brown_hair, brown_eyes, breasts, one_side_up, large_breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 455.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hiryuu_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 303.94 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hiryuu_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1099 | 600.08 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hiryuu_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 420.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hiryuu_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1099 | 785.84 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hiryuu_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/hiryuu_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 5 |  |  |  |  |  | 1girl, cowboy_shot, hakama_short_skirt, solo, green_hakama, looking_at_viewer, orange_kimono, smile, open_mouth, simple_background, yellow_kimono, index_finger_raised, one-hour_drawing_challenge, white_background |
| 1 | 7 |  |  |  |  |  | 2girls, green_hakama, hakama_short_skirt, wide_sleeves, blush, simple_background, smile, white_background, open_mouth, orange_kimono, solo_focus, yellow_kimono, cowboy_shot, looking_at_viewer, long_sleeves |
| 2 | 26 |  |  |  |  |  | flight_deck, arrow_(projectile), quiver, 1girl, solo, hakama_short_skirt, wide_sleeves, yugake, green_hakama, hachimaki, single_glove, holding_bow_(weapon), brown_gloves, cowboy_shot, looking_at_viewer, yellow_kimono |
| 3 | 5 |  |  |  |  |  | 1girl, arrow_(projectile), bow_(weapon), japanese_clothes, kyuudou, single_glove, skirt, solo, yugake, flight_deck, looking_at_viewer, quiver, open_mouth, wide_sleeves |
| 4 | 6 |  |  |  |  |  | 1girl, simple_background, solo, upper_body, looking_at_viewer, necklace, official_alternate_costume, open_mouth, ribbed_sweater, smile, collarbone, long_sleeves, twitter_username, white_background, yellow_sweater |
| 5 | 14 |  |  |  |  |  | 1girl, green_pants, official_alternate_costume, solo, jacket_around_waist, orange_sweater, ribbed_sweater, smile, looking_at_viewer, necklace, long_sleeves, open_mouth, plaid_jacket, simple_background, yellow_sweater, bag, blush, cowboy_shot, white_background |
| 6 | 7 |  |  |  |  |  | 1girl, alternate_costume, employee_uniform, looking_at_viewer, smile, solo, red_skirt, name_tag, open_mouth, blush, cowboy_shot, short_sleeves, simple_background, waitress, white_background, japanese_clothes, pleated_skirt |
| 7 | 8 |  |  |  |  |  | 1girl, clothes_writing, solo, black_skirt, looking_at_viewer, short_sleeves, smile, bag, official_alternate_costume, open_mouth, simple_background, yellow_shirt, white_background, wristwatch, orange_shirt |
| 8 | 14 |  |  |  |  |  | 1girl, solo, looking_at_viewer, navel, smile, cleavage, cowboy_shot, open_mouth, orange_bikini, cloud, day, outdoors, side-tie_bikini_bottom, blush, collarbone, blue_sky, simple_background, striped, yellow_bikini |
| 9 | 23 |  |  |  |  |  | 1girl, highleg_swimsuit, looking_at_viewer, blush, bangs, collarbone, smile, competition_swimsuit, simple_background, solo, standing, open_mouth, alternate_costume, bare_shoulders, black_one-piece_swimsuit, covered_navel, cowboy_shot, thighs, white_background, cleavage |
| 10 | 8 |  |  |  |  |  | hetero, nipples, 1boy, 1girl, blush, japanese_clothes, open_mouth, penis, smile, paizuri, solo_focus, bar_censor, cum_on_breasts |
| 11 | 7 |  |  |  |  |  | 1girl, detached_collar, fake_animal_ears, playboy_bunny, rabbit_ears, solo, cleavage, looking_at_viewer, wrist_cuffs, bowtie, strapless_leotard, black_pantyhose, blush, simple_background, smile, alternate_costume, black_leotard, open_mouth, yellow_leotard |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | cowboy_shot | hakama_short_skirt | solo | green_hakama | looking_at_viewer | orange_kimono | smile | open_mouth | simple_background | yellow_kimono | index_finger_raised | one-hour_drawing_challenge | white_background | 2girls | wide_sleeves | blush | solo_focus | long_sleeves | flight_deck | arrow_(projectile) | quiver | yugake | hachimaki | single_glove | holding_bow_(weapon) | brown_gloves | bow_(weapon) | japanese_clothes | kyuudou | skirt | upper_body | necklace | official_alternate_costume | ribbed_sweater | collarbone | twitter_username | yellow_sweater | green_pants | jacket_around_waist | orange_sweater | plaid_jacket | bag | alternate_costume | employee_uniform | red_skirt | name_tag | short_sleeves | waitress | pleated_skirt | clothes_writing | black_skirt | yellow_shirt | wristwatch | orange_shirt | navel | cleavage | orange_bikini | cloud | day | outdoors | side-tie_bikini_bottom | blue_sky | striped | yellow_bikini | highleg_swimsuit | bangs | competition_swimsuit | standing | bare_shoulders | black_one-piece_swimsuit | covered_navel | thighs | hetero | nipples | 1boy | penis | paizuri | bar_censor | cum_on_breasts | detached_collar | fake_animal_ears | playboy_bunny | rabbit_ears | wrist_cuffs | bowtie | strapless_leotard | black_pantyhose | black_leotard | yellow_leotard |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------------|:---------------------|:-------|:---------------|:--------------------|:----------------|:--------|:-------------|:--------------------|:----------------|:----------------------|:-----------------------------|:-------------------|:---------|:---------------|:--------|:-------------|:---------------|:--------------|:---------------------|:---------|:---------|:------------|:---------------|:-----------------------|:---------------|:---------------|:-------------------|:----------|:--------|:-------------|:-----------|:-----------------------------|:-----------------|:-------------|:-------------------|:-----------------|:--------------|:----------------------|:-----------------|:---------------|:------|:--------------------|:-------------------|:------------|:-----------|:----------------|:-----------|:----------------|:------------------|:--------------|:---------------|:-------------|:---------------|:--------|:-----------|:----------------|:--------|:------|:-----------|:-------------------------|:-----------|:----------|:----------------|:-------------------|:--------|:-----------------------|:-----------|:-----------------|:---------------------------|:----------------|:---------|:---------|:----------|:-------|:--------|:----------|:-------------|:-----------------|:------------------|:-------------------|:----------------|:--------------|:--------------|:---------|:--------------------|:------------------|:----------------|:-----------------|
| 0 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 7 |  |  |  |  |  | | X | X | | X | X | X | X | X | X | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 26 |  |  |  |  |  | X | X | X | X | X | X | | | | | X | | | | | X | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | | | X | | X | | | X | | | | | | | X | | | | X | X | X | X | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | | | X | | X | | X | X | X | | | | X | | | | | X | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 14 |  |  |  |  |  | X | X | | X | | X | | X | X | X | | | | X | | | X | | X | | | | | | | | | | | | | | X | X | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | X | | X | | X | | X | X | X | | | | X | | | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 8 |  |  |  |  |  | X | | | X | | X | | X | X | X | | | | X | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | X | | | | | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 14 |  |  |  |  |  | X | X | | X | | X | | X | X | X | | | | | | | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 23 |  |  |  |  |  | X | X | | X | | X | | X | X | X | | | | X | | | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | |
| 10 | 8 |  |  |  |  |  | X | | | | | | | X | X | | | | | | | | X | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | |
| 11 | 7 |  |  |  |  |  | X | | | X | | X | | X | X | X | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/hiryuu_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-20T23:50:33+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T05:03:28+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of hiryuu/飛龍 (Kantai Collection)
========================================
This is the dataset of hiryuu/飛龍 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'short\_hair, brown\_hair, brown\_eyes, breasts, one\_side\_up, large\_breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
8d5a45a9179279b321f6fa77e43825dbd9a0cbd5
|
# Dataset of hagikaze/萩風 (Kantai Collection)
This is the dataset of hagikaze/萩風 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, purple_hair, ahoge, one_side_up, brown_eyes, breasts, ribbon, red_ribbon, neck_ribbon, medium_breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 464.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hagikaze_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 312.55 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hagikaze_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1166 | 657.42 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hagikaze_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 427.84 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hagikaze_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1166 | 846.92 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hagikaze_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/hagikaze_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 18 |  |  |  |  |  | 1girl, black_skirt, black_vest, pleated_skirt, short_sleeves, solo, white_gloves, white_shirt, simple_background, white_background, blouse, looking_at_viewer, school_uniform, twitter_username, smile, cowboy_shot, one-hour_drawing_challenge, blush, open_mouth |
| 1 | 5 |  |  |  |  |  | 1girl, black_skirt, black_vest, blouse, full_body, grey_socks, kneehighs, pleated_skirt, short_sleeves, simple_background, solo, white_background, white_gloves, white_shirt, school_uniform, black_footwear, chibi, loafers, looking_at_viewer, smile, standing |
| 2 | 6 |  |  |  |  |  | 1girl, black_skirt, black_vest, blouse, pleated_skirt, purple_panties, short_sleeves, solo, white_shirt, white_gloves, lifted_by_self, skirt_lift, dress_shirt, sitting |
| 3 | 9 |  |  |  |  |  | 1girl, black_vest, blouse, gradient_background, short_sleeves, solo, upper_body, white_gloves, white_shirt, looking_at_viewer, open_mouth, dated, one-hour_drawing_challenge, red_background, blush, school_uniform |
| 4 | 12 |  |  |  |  |  | 1girl, navel, simple_background, solo, underwear_only, blush, cleavage, collarbone, looking_at_viewer, white_background, purple_panties, twitter_username, purple_bra, cowboy_shot, large_breasts, open_mouth, one-hour_drawing_challenge, smile, bare_shoulders, groin, white_gloves, yellow_eyes |
| 5 | 5 |  |  |  |  |  | 1girl, blush, collarbone, large_breasts, looking_at_viewer, solo, cleavage, smile, dated, purple_bikini, purple_eyes, alternate_costume, cowboy_shot, navel, one-hour_drawing_challenge, simple_background, twitter_username, white_background |
| 6 | 11 |  |  |  |  |  | 1girl, black_dress, simple_background, solo, enmaided, looking_at_viewer, white_apron, blush, maid_apron, frilled_apron, white_background, maid_headdress, open_mouth, short_sleeves, smile, white_gloves, cleavage, hair_between_eyes, one-hour_drawing_challenge, thighhighs, twitter_username |
| 7 | 9 |  |  |  |  |  | detached_collar, playboy_bunny, rabbit_ears, 1girl, fake_animal_ears, solo, looking_at_viewer, strapless_leotard, wrist_cuffs, blush, cleavage, open_mouth, smile, alternate_costume, black_leotard, bowtie, fishnet_pantyhose, large_breasts, simple_background, white_background, bare_shoulders, covered_navel, rabbit_tail |
| 8 | 7 |  |  |  |  |  | 1girl, alternate_costume, obi, solo, yukata, looking_at_viewer, smile, alternate_hairstyle, blue_kimono, ponytail, simple_background, white_background, hairclip, open_mouth, bag, blush, dated, full_body, long_sleeves, sandals, twitter_username, wide_sleeves, yellow_eyes |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_skirt | black_vest | pleated_skirt | short_sleeves | solo | white_gloves | white_shirt | simple_background | white_background | blouse | looking_at_viewer | school_uniform | twitter_username | smile | cowboy_shot | one-hour_drawing_challenge | blush | open_mouth | full_body | grey_socks | kneehighs | black_footwear | chibi | loafers | standing | purple_panties | lifted_by_self | skirt_lift | dress_shirt | sitting | gradient_background | upper_body | dated | red_background | navel | underwear_only | cleavage | collarbone | purple_bra | large_breasts | bare_shoulders | groin | yellow_eyes | purple_bikini | purple_eyes | alternate_costume | black_dress | enmaided | white_apron | maid_apron | frilled_apron | maid_headdress | hair_between_eyes | thighhighs | detached_collar | playboy_bunny | rabbit_ears | fake_animal_ears | strapless_leotard | wrist_cuffs | black_leotard | bowtie | fishnet_pantyhose | covered_navel | rabbit_tail | obi | yukata | alternate_hairstyle | blue_kimono | ponytail | hairclip | bag | long_sleeves | sandals | wide_sleeves |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------|:-------------|:----------------|:----------------|:-------|:---------------|:--------------|:--------------------|:-------------------|:---------|:--------------------|:-----------------|:-------------------|:--------|:--------------|:-----------------------------|:--------|:-------------|:------------|:-------------|:------------|:-----------------|:--------|:----------|:-----------|:-----------------|:-----------------|:-------------|:--------------|:----------|:----------------------|:-------------|:--------|:-----------------|:--------|:-----------------|:-----------|:-------------|:-------------|:----------------|:-----------------|:--------|:--------------|:----------------|:--------------|:--------------------|:--------------|:-----------|:--------------|:-------------|:----------------|:-----------------|:--------------------|:-------------|:------------------|:----------------|:--------------|:-------------------|:--------------------|:--------------|:----------------|:---------|:--------------------|:----------------|:--------------|:------|:---------|:----------------------|:--------------|:-----------|:-----------|:------|:---------------|:----------|:---------------|
| 0 | 18 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | | X | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 9 |  |  |  |  |  | X | | X | | X | X | X | X | | | X | X | X | | | | X | X | X | | | | | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 12 |  |  |  |  |  | X | | | | | X | X | | X | X | | X | | X | X | X | X | X | X | | | | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 5 |  |  |  |  |  | X | | | | | X | | | X | X | | X | | X | X | X | X | X | | | | | | | | | | | | | | | | X | | X | | X | X | | X | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 11 |  |  |  |  |  | X | | | | X | X | X | | X | X | | X | | X | X | | X | X | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 7 | 9 |  |  |  |  |  | X | | | | | X | | | X | X | | X | | | X | | | X | X | | | | | | | | | | | | | | | | | | | X | | | X | X | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | | | | X | | | X | X | | X | | X | X | | | X | X | X | | | | | | | | | | | | | | X | | | | | | | | | | X | | | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/hagikaze_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T00:03:00+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T17:01:11+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of hagikaze/萩風 (Kantai Collection)
==========================================
This is the dataset of hagikaze/萩風 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, purple\_hair, ahoge, one\_side\_up, brown\_eyes, breasts, ribbon, red\_ribbon, neck\_ribbon, medium\_breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
ab9b12d4f300a4f5b0ff6a4ced06b1549336d817
|
# Dataset Card for "high_all_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Jing24/high_all_train
|
[
"region:us"
] |
2023-08-21T00:12:19+00:00
|
{"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answers", "struct": [{"name": "answer_start", "sequence": "int64"}, {"name": "text", "sequence": "string"}]}], "splits": [{"name": "train", "num_bytes": 79675205, "num_examples": 87599}], "download_size": 14372991, "dataset_size": 79675205}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]}
|
2023-08-21T14:48:46+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "high_all_train"
More Information needed
|
[
"# Dataset Card for \"high_all_train\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"high_all_train\"\n\nMore Information needed"
] |
[
6,
16
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"high_all_train\"\n\nMore Information needed"
] |
f69a33b38daf4902551ae639ae4f5e22c9b41e27
|
# Dataset Card for "russian_lyrics_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
dim/russian_lyrics_prompts
|
[
"region:us"
] |
2023-08-21T00:23:41+00:00
|
{"dataset_info": {"features": [{"name": "prompt", "dtype": "string"}, {"name": "solution", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 18504, "num_examples": 43}], "download_size": 14764, "dataset_size": 18504}}
|
2023-08-21T00:23:59+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "russian_lyrics_prompts"
More Information needed
|
[
"# Dataset Card for \"russian_lyrics_prompts\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"russian_lyrics_prompts\"\n\nMore Information needed"
] |
[
6,
20
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"russian_lyrics_prompts\"\n\nMore Information needed"
] |
43adf45d2f6d46c48c1c5e692e43faaecb056bb3
|
# Dataset of akashi/明石/明石 (Kantai Collection)
This is the dataset of akashi/明石/明石 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `pink_hair, long_hair, hair_ribbon, ribbon, green_eyes, tress_ribbon, breasts, large_breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 529.57 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akashi_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 330.72 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akashi_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1150 | 669.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akashi_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 481.80 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akashi_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1150 | 902.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akashi_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/akashi_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 32 |  |  |  |  |  | 1girl, looking_at_viewer, solo, side-tie_bikini_bottom, cowboy_shot, navel, simple_background, cleavage, white_background, smile, white_bikini, medium_breasts, standing |
| 1 | 19 |  |  |  |  |  | 1girl, serafuku, solo, skirt, hip_vent, looking_at_viewer, blush, smile, thighhighs, open_mouth |
| 2 | 28 |  |  |  |  |  | 1girl, serafuku, solo, blue_skirt, long_sleeves, looking_at_viewer, pleated_skirt, simple_background, blue_sailor_collar, white_background, hip_vent, dated, smile, black_pantyhose, thighhighs |
| 3 | 11 |  |  |  |  |  | 1girl, looking_at_viewer, serafuku, simple_background, solo, blue_sailor_collar, upper_body, white_background, long_sleeves, smile, open_mouth |
| 4 | 6 |  |  |  |  |  | 1boy, blue_skirt, blush, hetero, pleated_skirt, serafuku, 1girl, hair_between_eyes, open_mouth, short_over_long_sleeves, solo_focus, thighhighs, blue_sailor_collar, red_ribbon, mosaic_censoring, penis, shirt, simple_background, underwear, white_background |
| 5 | 14 |  |  |  |  |  | 1girl, hat, solo, smile, alternate_costume, looking_at_viewer, blush, long_sleeves, white_dress, white_headwear, hair_between_eyes, simple_background, open_mouth, bag, white_background, cowboy_shot, holding |
| 6 | 7 |  |  |  |  |  | smile, 1girl, bag, blue_shirt, casual, full_body, looking_at_viewer, open_mouth, short_sleeves, solo, standing, white_pants, black_footwear, collarbone, belt, high_heels, official_alternate_costume, simple_background, very_long_hair |
| 7 | 13 |  |  |  |  |  | 1girl, blush, hetero, solo_focus, 1boy, nipples, nude, open_mouth, sex, censored, penis, hair_between_eyes, navel, sweat |
| 8 | 9 |  |  |  |  |  | 1boy, 1girl, blush, hetero, penis, solo_focus, serafuku, censored, fellatio, looking_at_viewer, cum_in_mouth, heart, tongue_out |
| 9 | 6 |  |  |  |  |  | 1girl, enmaided, frilled_apron, maid_headdress, white_apron, black_dress, looking_at_viewer, solo, blush, dated, maid_apron, waist_apron, cowboy_shot, hair_between_eyes, one-hour_drawing_challenge, puffy_short_sleeves, simple_background, white_background, white_thighhighs |
| 10 | 5 |  |  |  |  |  | 1girl, black_pantyhose, fake_animal_ears, looking_at_viewer, medium_breasts, playboy_bunny, rabbit_ears, solo, strapless_leotard, black_leotard, cleavage, detached_collar, smile, wrist_cuffs, covered_navel, dated, one-hour_drawing_challenge, red_bowtie, white_background, alternate_costume, cowboy_shot, high_heels, open_mouth, simple_background, sitting |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | solo | side-tie_bikini_bottom | cowboy_shot | navel | simple_background | cleavage | white_background | smile | white_bikini | medium_breasts | standing | serafuku | skirt | hip_vent | blush | thighhighs | open_mouth | blue_skirt | long_sleeves | pleated_skirt | blue_sailor_collar | dated | black_pantyhose | upper_body | 1boy | hetero | hair_between_eyes | short_over_long_sleeves | solo_focus | red_ribbon | mosaic_censoring | penis | shirt | underwear | hat | alternate_costume | white_dress | white_headwear | bag | holding | blue_shirt | casual | full_body | short_sleeves | white_pants | black_footwear | collarbone | belt | high_heels | official_alternate_costume | very_long_hair | nipples | nude | sex | censored | sweat | fellatio | cum_in_mouth | heart | tongue_out | enmaided | frilled_apron | maid_headdress | white_apron | black_dress | maid_apron | waist_apron | one-hour_drawing_challenge | puffy_short_sleeves | white_thighhighs | fake_animal_ears | playboy_bunny | rabbit_ears | strapless_leotard | black_leotard | detached_collar | wrist_cuffs | covered_navel | red_bowtie | sitting |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------------------|:-------|:-------------------------|:--------------|:--------|:--------------------|:-----------|:-------------------|:--------|:---------------|:-----------------|:-----------|:-----------|:--------|:-----------|:--------|:-------------|:-------------|:-------------|:---------------|:----------------|:---------------------|:--------|:------------------|:-------------|:-------|:---------|:--------------------|:--------------------------|:-------------|:-------------|:-------------------|:--------|:--------|:------------|:------|:--------------------|:--------------|:-----------------|:------|:----------|:-------------|:---------|:------------|:----------------|:--------------|:-----------------|:-------------|:-------|:-------------|:-----------------------------|:-----------------|:----------|:-------|:------|:-----------|:--------|:-----------|:---------------|:--------|:-------------|:-----------|:----------------|:-----------------|:--------------|:--------------|:-------------|:--------------|:-----------------------------|:----------------------|:-------------------|:-------------------|:----------------|:--------------|:--------------------|:----------------|:------------------|:--------------|:----------------|:-------------|:----------|
| 0 | 32 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 19 |  |  |  |  |  | X | X | X | | | | | | | X | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 28 |  |  |  |  |  | X | X | X | | | | X | | X | X | | | | X | | X | | X | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 11 |  |  |  |  |  | X | X | X | | | | X | | X | X | | | | X | | | | | X | | X | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | | | | | | X | | X | | | | | X | | | X | X | X | X | | X | X | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 14 |  |  |  |  |  | X | X | X | | X | | X | | X | X | | | | | | | X | | X | | X | | | | | | | | X | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | X | X | | | | X | | | X | | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 13 |  |  |  |  |  | X | | | | | X | | | | | | | | | | | X | | X | | | | | | | | X | X | X | | X | | | X | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 9 |  |  |  |  |  | X | X | | | | | | | | | | | | X | | | X | | | | | | | | | | X | X | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | X | | X | X | X | X | | | | | | | | | | | | | | | | | | | | |
| 9 | 6 |  |  |  |  |  | X | X | X | | X | | X | | X | | | | | | | | X | | | | | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | |
| 10 | 5 |  |  |  |  |  | X | X | X | | X | | X | X | X | X | | X | | | | | | | X | | | | | X | X | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/akashi_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T00:39:46+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T01:42:44+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of akashi/明石/明石 (Kantai Collection)
===========================================
This is the dataset of akashi/明石/明石 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'pink\_hair, long\_hair, hair\_ribbon, ribbon, green\_eyes, tress\_ribbon, breasts, large\_breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
59d0b91bb5b25e1e7d1e0bcdbdfc07e9b9c2a63c
|
# Dataset of jintsuu/神通/神通 (Kantai Collection)
This is the dataset of jintsuu/神通/神通 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, long_hair, brown_eyes, hair_intakes, headband, half_updo, breasts, bow`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 453.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/jintsuu_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 309.05 MiB | [Download](https://huggingface.co/datasets/CyberHarem/jintsuu_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1034 | 600.61 MiB | [Download](https://huggingface.co/datasets/CyberHarem/jintsuu_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 416.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/jintsuu_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1034 | 770.95 MiB | [Download](https://huggingface.co/datasets/CyberHarem/jintsuu_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/jintsuu_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, detached_sleeves, double-breasted, forehead_protector, looking_at_viewer, serafuku, solo, upper_body, elbow_gloves, sarashi |
| 1 | 19 |  |  |  |  |  | 1girl, serafuku, solo, forehead_protector, looking_at_viewer, upper_body, elbow_gloves, white_sailor_collar, smile, detached_sleeves, black_neckerchief, hachimaki, simple_background, white_background, black_gloves, double-breasted, sarashi, twitter_username |
| 2 | 5 |  |  |  |  |  | 1girl, forehead_protector, serafuku, solo, upper_body, elbow_gloves, simple_background, white_background, detached_sleeves, hachimaki, hair_bow |
| 3 | 6 |  |  |  |  |  | 1girl, elbow_gloves, forehead_protector, hachimaki, serafuku, solo, black_gloves, holding_sword, simple_background, white_thighhighs, white_background, white_sailor_collar, detached_sleeves, full_body, green_bow, katana, looking_at_viewer, pleated_skirt |
| 4 | 8 |  |  |  |  |  | serafuku, 2girls, elbow_gloves, forehead_protector, skirt, detached_sleeves, hachimaki |
| 5 | 5 |  |  |  |  |  | black_gloves, blush, elbow_gloves, forehead_protector, minigirl, serafuku, simple_background, size_difference, white_background, 2girls, giantess, 3girls, solo_focus, cowboy_shot, hachimaki, looking_at_viewer, open_mouth, pleated_skirt, thighhighs |
| 6 | 6 |  |  |  |  |  | 1girl, ponytail, smile, solo, uchiwa, yukata, looking_at_viewer, obi, blush, hair_ribbon |
| 7 | 10 |  |  |  |  |  | 1girl, alternate_costume, hair_bow, long_sleeves, ribbon, smile, solo, white_shirt, blue_skirt, blush, looking_at_viewer, collared_shirt, high-waist_skirt, center_frills, virgin_killer_outfit, open_mouth, black_pantyhose, red_bow, white_background |
| 8 | 7 |  |  |  |  |  | detached_collar, fake_animal_ears, playboy_bunny, rabbit_ears, 1girl, cleavage, simple_background, solo, strapless_leotard, looking_at_viewer, wrist_cuffs, green_bow, high_heels, large_breasts, medium_breasts, white_background, black_bowtie, black_pantyhose, blush, cowboy_shot, rabbit_tail, red_leotard |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | detached_sleeves | double-breasted | forehead_protector | looking_at_viewer | serafuku | solo | upper_body | elbow_gloves | sarashi | white_sailor_collar | smile | black_neckerchief | hachimaki | simple_background | white_background | black_gloves | twitter_username | hair_bow | holding_sword | white_thighhighs | full_body | green_bow | katana | pleated_skirt | 2girls | skirt | blush | minigirl | size_difference | giantess | 3girls | solo_focus | cowboy_shot | open_mouth | thighhighs | ponytail | uchiwa | yukata | obi | hair_ribbon | alternate_costume | long_sleeves | ribbon | white_shirt | blue_skirt | collared_shirt | high-waist_skirt | center_frills | virgin_killer_outfit | black_pantyhose | red_bow | detached_collar | fake_animal_ears | playboy_bunny | rabbit_ears | cleavage | strapless_leotard | wrist_cuffs | high_heels | large_breasts | medium_breasts | black_bowtie | rabbit_tail | red_leotard |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------------|:------------------|:---------------------|:--------------------|:-----------|:-------|:-------------|:---------------|:----------|:----------------------|:--------|:--------------------|:------------|:--------------------|:-------------------|:---------------|:-------------------|:-----------|:----------------|:-------------------|:------------|:------------|:---------|:----------------|:---------|:--------|:--------|:-----------|:------------------|:-----------|:---------|:-------------|:--------------|:-------------|:-------------|:-----------|:---------|:---------|:------|:--------------|:--------------------|:---------------|:---------|:--------------|:-------------|:-----------------|:-------------------|:----------------|:-----------------------|:------------------|:----------|:------------------|:-------------------|:----------------|:--------------|:-----------|:--------------------|:--------------|:-------------|:----------------|:-----------------|:---------------|:--------------|:--------------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 19 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | X | | X | | X | X | X | X | | | | | X | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | X | | X | X | X | X | | X | | X | | | X | X | X | X | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 8 |  |  |  |  |  | | X | | X | | X | | | X | | | | | X | | | | | | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 5 |  |  |  |  |  | | | | X | X | X | | | X | | | | | X | X | X | X | | | | | | | | X | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | X | | | | X | | X | | | | | X | | | | | | | | | | | | | | | | X | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 10 |  |  |  |  |  | X | | | | X | | X | | | | | X | | | | X | | | X | | | | | | | | | X | | | | | | | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | | | X | | X | | | | | | | | X | X | | | | | | | X | | | | | X | | | | | | X | | | | | | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/jintsuu_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T00:49:26+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T04:51:42+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of jintsuu/神通/神通 (Kantai Collection)
============================================
This is the dataset of jintsuu/神通/神通 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, long\_hair, brown\_eyes, hair\_intakes, headband, half\_updo, breasts, bow', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
b1a475b720a83f48225e2f033b71bcbc8b7706f6
|
# Dataset of kiyoshimo/清霜/清霜 (Kantai Collection)
This is the dataset of kiyoshimo/清霜/清霜 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, grey_hair, ahoge, twintails, low_twintails, hair_between_eyes, very_long_hair, grey_eyes, bow`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 445.33 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kiyoshimo_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 290.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kiyoshimo_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1044 | 575.28 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kiyoshimo_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 405.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kiyoshimo_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1044 | 751.84 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kiyoshimo_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kiyoshimo_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, bowtie, dress, grey_pantyhose, long_sleeves, looking_at_viewer, school_uniform, solo, white_shirt, halterneck, smile, white_background, multicolored_hair, simple_background |
| 1 | 8 |  |  |  |  |  | 1girl, bowtie, dress, looking_at_viewer, school_uniform, simple_background, solo, white_shirt, single_hair_bun, smile, white_background, halterneck, long_sleeves, upper_body, blush, one-hour_drawing_challenge, open_mouth, twitter_username |
| 2 | 8 |  |  |  |  |  | 1girl, bowtie, long_sleeves, school_uniform, solo, white_shirt, grey_pantyhose, looking_at_viewer, open_mouth, white_background, simple_background, :d, machinery, sleeveless_dress, turret, blush, teeth |
| 3 | 15 |  |  |  |  |  | 1girl, bowtie, grey_pantyhose, school_uniform, solo, white_shirt, halterneck, full_body, lace-up_boots, long_sleeves, single_hair_bun, smile, standing, looking_at_viewer, open_mouth, white_background, chibi, purple_dress, simple_background |
| 4 | 5 |  |  |  |  |  | blush, looking_at_viewer, navel, nipples, nude, pussy, small_breasts, 1girl, solo, uncensored, cleft_of_venus, open_mouth, :d, blue_eyes, collarbone, hair_ribbon, loli, purple_eyes, standing |
| 5 | 7 |  |  |  |  |  | 1girl, alternate_costume, blue_hair, full_body, looking_at_viewer, multicolored_hair, solo, simple_background, smile, white_socks, twitter_username, white_background, bag, holding, long_sleeves, standing, white_shirt, black_footwear, dress, flower, mary_janes, open_mouth |
| 6 | 7 |  |  |  |  |  | 1girl, blush, looking_at_viewer, nipples, panty_pull, polka_dot_panties, small_breasts, solo, green_panties, navel, pussy, smile, pantyhose_pull, bow_panties, bra_lift, dakimakura_(medium), grey_pantyhose, on_back, open_shirt |
| 7 | 11 |  |  |  |  |  | 1girl, detached_collar, fake_animal_ears, playboy_bunny, rabbit_ears, wrist_cuffs, purple_leotard, solo, strapless_leotard, grey_pantyhose, small_breasts, white_background, rabbit_tail, simple_background, aqua_bowtie, covered_navel, fishnet_pantyhose, highleg_leotard, smile, thighband_pantyhose, adapted_costume, full_body, purple_footwear, cowboy_shot, dated, hair_bun, looking_at_viewer, rudder_footwear |
| 8 | 9 |  |  |  |  |  | alternate_costume, kimono, looking_at_viewer, 1girl, floral_print, hair_flower, solo, wide_sleeves, obi, blue_hair, blush, happy_new_year, long_sleeves, multicolored_hair, open_mouth, twitter_username, :d, upper_body |
| 9 | 11 |  |  |  |  |  | 1girl, solo, looking_at_viewer, single_hair_bun, smile, simple_background, white_background, collarbone, covered_navel, highleg_swimsuit, small_breasts, alternate_costume, competition_swimsuit, flat_chest, standing, barefoot, cowboy_shot, open_mouth, ass_visible_through_thighs, full_body |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bowtie | dress | grey_pantyhose | long_sleeves | looking_at_viewer | school_uniform | solo | white_shirt | halterneck | smile | white_background | multicolored_hair | simple_background | single_hair_bun | upper_body | blush | one-hour_drawing_challenge | open_mouth | twitter_username | :d | machinery | sleeveless_dress | turret | teeth | full_body | lace-up_boots | standing | chibi | purple_dress | navel | nipples | nude | pussy | small_breasts | uncensored | cleft_of_venus | blue_eyes | collarbone | hair_ribbon | loli | purple_eyes | alternate_costume | blue_hair | white_socks | bag | holding | black_footwear | flower | mary_janes | panty_pull | polka_dot_panties | green_panties | pantyhose_pull | bow_panties | bra_lift | dakimakura_(medium) | on_back | open_shirt | detached_collar | fake_animal_ears | playboy_bunny | rabbit_ears | wrist_cuffs | purple_leotard | strapless_leotard | rabbit_tail | aqua_bowtie | covered_navel | fishnet_pantyhose | highleg_leotard | thighband_pantyhose | adapted_costume | purple_footwear | cowboy_shot | dated | hair_bun | rudder_footwear | kimono | floral_print | hair_flower | wide_sleeves | obi | happy_new_year | highleg_swimsuit | competition_swimsuit | flat_chest | barefoot | ass_visible_through_thighs |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------|:--------|:-----------------|:---------------|:--------------------|:-----------------|:-------|:--------------|:-------------|:--------|:-------------------|:--------------------|:--------------------|:------------------|:-------------|:--------|:-----------------------------|:-------------|:-------------------|:-----|:------------|:-------------------|:---------|:--------|:------------|:----------------|:-----------|:--------|:---------------|:--------|:----------|:-------|:--------|:----------------|:-------------|:-----------------|:------------|:-------------|:--------------|:-------|:--------------|:--------------------|:------------|:--------------|:------|:----------|:-----------------|:---------|:-------------|:-------------|:--------------------|:----------------|:-----------------|:--------------|:-----------|:----------------------|:----------|:-------------|:------------------|:-------------------|:----------------|:--------------|:--------------|:-----------------|:--------------------|:--------------|:--------------|:----------------|:--------------------|:------------------|:----------------------|:------------------|:------------------|:--------------|:--------|:-----------|:------------------|:---------|:---------------|:--------------|:---------------|:------|:-----------------|:-------------------|:-----------------------|:-------------|:-----------|:-----------------------------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 8 |  |  |  |  |  | X | X | X | | X | X | X | X | X | X | X | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 8 |  |  |  |  |  | X | X | | X | X | X | X | X | X | | | X | | X | | | X | | X | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 15 |  |  |  |  |  | X | X | | X | X | X | X | X | X | X | X | X | | X | X | | | | X | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | | | | | X | | X | | | | | | | | | X | | X | | X | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 7 |  |  |  |  |  | X | | X | | X | X | | X | X | | X | X | X | X | | | | | X | X | | | | | | X | | X | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | | | X | | X | | X | | | X | | | | | | X | | | | | | | | | | | | | | X | X | | X | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 11 |  |  |  |  |  | X | | | X | | X | | X | | | X | X | | X | | | | | | | | | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | |
| 8 | 9 |  |  |  |  |  | X | | | | X | X | | X | | | | | X | | | X | X | | X | X | X | | | | | | | | | | | | | | | | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | |
| 9 | 11 |  |  |  |  |  | X | | | | | X | | X | | | X | X | | X | X | | | | X | | | | | | | X | | X | | | | | | | X | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | X | | | | | | | | | | X | X | X | X | X |
|
CyberHarem/kiyoshimo_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T01:24:26+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T07:27:33+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kiyoshimo/清霜/清霜 (Kantai Collection)
==============================================
This is the dataset of kiyoshimo/清霜/清霜 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, grey\_hair, ahoge, twintails, low\_twintails, hair\_between\_eyes, very\_long\_hair, grey\_eyes, bow', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
c52cb68f14116d7ca776e647ac8baf6beecf71de
|
# Dataset Card for "10026758"
[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/10026758
|
[
"region:us"
] |
2023-08-21T01:29:26+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 176, "num_examples": 10}], "download_size": 1326, "dataset_size": 176}}
|
2023-08-21T01:29:27+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "10026758"
More Information needed
|
[
"# Dataset Card for \"10026758\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"10026758\"\n\nMore Information needed"
] |
[
6,
14
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"10026758\"\n\nMore Information needed"
] |
0cd5d826a399983d4059022d8ec11afecbdaa61b
|
# Dataset Card for "SPP_30K_verified_tasks"
### Dataset Summary
This is an augmented version of the [Synthetic Python Problems(SPP) Dataset](https://huggingface.co/datasets/wuyetao/spp).
This dataset has been generated from the subset of the data has been de-duplicated and verified using a Python interpreter. (SPP_30k_verified.jsonl).
The original dataset contains small Python functions that include a docstring with a small description of what the function does and some calling examples
for the function.
The current dataset includes three different tasks:
- Type 1: give the code as input and ask the model to generate some example calls along the expected return value
- Type 2: give the description and the example calling calls and ask the model to write the function.
- Type 3: give the the function and the example calls without the expected value as input and ask the model to write what the function should return.
For example:
```python
def lowest_prime_factor(n):
""" Find the smallest prime factor of a given number.
Examples:
>>> lowest_prime_factor(12)
2
>>> lowest_prime_factor(14)
2
>>> lowest_prime_factor(8)
2
"""
smallest = 2
while(n % smallest!= 0):
smallest+=1
return smallest
```
First task:
```
INSTRUCTION:
Execute the following function with several example calls, showing the values returned in each case.
INPUT:
def lowest_prime_factor(n):
smallest = 2
while(n % smallest!= 0):
smallest+=1
return smallest
OUTPUT:
Sure, here you have several example calls along the return values they will generate.
"""
>>> lowest_prime_factor(12)
2
>>> lowest_prime_factor(14)
2
>>> lowest_prime_factor(8)
2
"""
```
Second task:
```
INSTRUCTION:
Follow the task given and refer to the provided calling examples as you create the function's body.
INPUT:
Find the smallest prime factor of a given number.
Examples:
>>> lowest_prime_factor(12)
2
>>> lowest_prime_factor(14)
2
>>> lowest_prime_factor(8)
2
OUTPUT:
Of course, here's a function implementation based on the provided calling examples and task.
""" python
def lowest_prime_factor(n):
smallest = 2
while(n % smallest!= 0):
smallest+=1
return smallest
"""
```
Third task:
```
INSTRUCTION:
Examine the given function and the accompanying instance function calls, and outline the specific output generated by each call.
INPUT:
def lowest_prime_factor(n):
smallest = 2
while(n % smallest!= 0):
smallest+=1
return smallest
Function calls:
>>> lowest_prime_factor(12)
>>> lowest_prime_factor(14)
>>> lowest_prime_factor(8)
OUTPUT:
Sure thing, here you have the specific output generated by each function call.
>>> lowest_prime_factor(12)
2
>>> lowest_prime_factor(14)
2
>>> lowest_prime_factor(8)
2
```
### Languages
The dataset is in English.
### Data Splits
There are no splits (Only training).
## Dataset Creation
August of 2023
### Curation Rationale
This dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.
### Source Data
The source dataset can be found at [Synthetic Python Problems(SPP) Dataset](https://huggingface.co/datasets/wuyetao/spp).
### Annotations
The dataset includes an instruction, input, output and type columns.
The type colum indicates the type of task (from 1 to 3).
#### Annotation process
The responses were generated parsing the docstrings of the functions.
|
Nan-Do/SPP_30K_reasoning_tasks
|
[
"task_categories:text-generation",
"task_categories:conversational",
"task_categories:text2text-generation",
"language:en",
"code",
"python",
"reasoning",
"region:us"
] |
2023-08-21T01:34:43+00:00
|
{"language": ["en"], "task_categories": ["text-generation", "conversational", "text2text-generation"], "pretty_name": "SPP python reasoning tasks", "dataset_info": {"features": [{"name": "type", "dtype": "int64"}, {"name": "instruction", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 44253001, "num_examples": 89898}], "download_size": 10073876, "dataset_size": 44253001}, "tags": ["code", "python", "reasoning"]}
|
2023-08-22T06:09:57+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-text-generation #task_categories-conversational #task_categories-text2text-generation #language-English #code #python #reasoning #region-us
|
# Dataset Card for "SPP_30K_verified_tasks"
### Dataset Summary
This is an augmented version of the Synthetic Python Problems(SPP) Dataset.
This dataset has been generated from the subset of the data has been de-duplicated and verified using a Python interpreter. (SPP_30k_verified.jsonl).
The original dataset contains small Python functions that include a docstring with a small description of what the function does and some calling examples
for the function.
The current dataset includes three different tasks:
- Type 1: give the code as input and ask the model to generate some example calls along the expected return value
- Type 2: give the description and the example calling calls and ask the model to write the function.
- Type 3: give the the function and the example calls without the expected value as input and ask the model to write what the function should return.
For example:
First task:
Second task:
Third task:
### Languages
The dataset is in English.
### Data Splits
There are no splits (Only training).
## Dataset Creation
August of 2023
### Curation Rationale
This dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.
### Source Data
The source dataset can be found at Synthetic Python Problems(SPP) Dataset.
### Annotations
The dataset includes an instruction, input, output and type columns.
The type colum indicates the type of task (from 1 to 3).
#### Annotation process
The responses were generated parsing the docstrings of the functions.
|
[
"# Dataset Card for \"SPP_30K_verified_tasks\"",
"### Dataset Summary\n\nThis is an augmented version of the Synthetic Python Problems(SPP) Dataset.\n\nThis dataset has been generated from the subset of the data has been de-duplicated and verified using a Python interpreter. (SPP_30k_verified.jsonl).\nThe original dataset contains small Python functions that include a docstring with a small description of what the function does and some calling examples \nfor the function. \n\nThe current dataset includes three different tasks:\n - Type 1: give the code as input and ask the model to generate some example calls along the expected return value\n - Type 2: give the description and the example calling calls and ask the model to write the function.\n - Type 3: give the the function and the example calls without the expected value as input and ask the model to write what the function should return.\n\n\nFor example:\n\n\n\nFirst task:\n\n\nSecond task:\n\n\nThird task:",
"### Languages\n\nThe dataset is in English.",
"### Data Splits\n\nThere are no splits (Only training).",
"## Dataset Creation\n\nAugust of 2023",
"### Curation Rationale\n\nThis dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.",
"### Source Data\n\nThe source dataset can be found at Synthetic Python Problems(SPP) Dataset.",
"### Annotations\n\nThe dataset includes an instruction, input, output and type columns. \nThe type colum indicates the type of task (from 1 to 3).",
"#### Annotation process\n\nThe responses were generated parsing the docstrings of the functions."
] |
[
"TAGS\n#task_categories-text-generation #task_categories-conversational #task_categories-text2text-generation #language-English #code #python #reasoning #region-us \n",
"# Dataset Card for \"SPP_30K_verified_tasks\"",
"### Dataset Summary\n\nThis is an augmented version of the Synthetic Python Problems(SPP) Dataset.\n\nThis dataset has been generated from the subset of the data has been de-duplicated and verified using a Python interpreter. (SPP_30k_verified.jsonl).\nThe original dataset contains small Python functions that include a docstring with a small description of what the function does and some calling examples \nfor the function. \n\nThe current dataset includes three different tasks:\n - Type 1: give the code as input and ask the model to generate some example calls along the expected return value\n - Type 2: give the description and the example calling calls and ask the model to write the function.\n - Type 3: give the the function and the example calls without the expected value as input and ask the model to write what the function should return.\n\n\nFor example:\n\n\n\nFirst task:\n\n\nSecond task:\n\n\nThird task:",
"### Languages\n\nThe dataset is in English.",
"### Data Splits\n\nThere are no splits (Only training).",
"## Dataset Creation\n\nAugust of 2023",
"### Curation Rationale\n\nThis dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.",
"### Source Data\n\nThe source dataset can be found at Synthetic Python Problems(SPP) Dataset.",
"### Annotations\n\nThe dataset includes an instruction, input, output and type columns. \nThe type colum indicates the type of task (from 1 to 3).",
"#### Annotation process\n\nThe responses were generated parsing the docstrings of the functions."
] |
[
53,
18,
201,
11,
15,
8,
29,
25,
38,
22
] |
[
"passage: TAGS\n#task_categories-text-generation #task_categories-conversational #task_categories-text2text-generation #language-English #code #python #reasoning #region-us \n# Dataset Card for \"SPP_30K_verified_tasks\"### Dataset Summary\n\nThis is an augmented version of the Synthetic Python Problems(SPP) Dataset.\n\nThis dataset has been generated from the subset of the data has been de-duplicated and verified using a Python interpreter. (SPP_30k_verified.jsonl).\nThe original dataset contains small Python functions that include a docstring with a small description of what the function does and some calling examples \nfor the function. \n\nThe current dataset includes three different tasks:\n - Type 1: give the code as input and ask the model to generate some example calls along the expected return value\n - Type 2: give the description and the example calling calls and ask the model to write the function.\n - Type 3: give the the function and the example calls without the expected value as input and ask the model to write what the function should return.\n\n\nFor example:\n\n\n\nFirst task:\n\n\nSecond task:\n\n\nThird task:### Languages\n\nThe dataset is in English.### Data Splits\n\nThere are no splits (Only training).## Dataset Creation\n\nAugust of 2023### Curation Rationale\n\nThis dataset was created to improve the Python 3 reasoning/understanding capabilities of LLMs.### Source Data\n\nThe source dataset can be found at Synthetic Python Problems(SPP) Dataset.### Annotations\n\nThe dataset includes an instruction, input, output and type columns. \nThe type colum indicates the type of task (from 1 to 3).#### Annotation process\n\nThe responses were generated parsing the docstrings of the functions."
] |
46ddfef913bdd557db10b17ebdbf3fac194351f5
|
# ReActor Node 0.1.1b for ComfyUI
### The Fast and Simple "roop-like" Face Swap Extension Node for ComfyUI, based on [ReActor (ex Roop-GE)](https://github.com/Gourieff/sd-webui-reactor) SD-WebUI Face Swap Extension
> This Node goes without NSFW filter (uncensored, use it on your own responsibility)
---
[**Disclaimer**](#disclaimer) | [**Installation**](#installation) | [**Usage**](#usage) | [**Troubleshooting**](#troubleshooting) | [**Updating**](#updating)
---
### Disclaimer
This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.
The developers of this software are aware of its possible unethical applicaitons and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.
Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. **Developers and Contributors of this software are not responsible for actions of end-users.**
## Installation
[SD WebUI](#sdwebui) | [Standalone ComfyUI](#standalone)
<a name="sdwebui">If you use [AUTOMATIC1111](https://github.com/AUTOMATIC1111/stable-diffusion-webui/) or [SD.Next](https://github.com/vladmandic/automatic)
1. Close (stop) your SD-WebUI/Comfy Server if it's running
2. (For Windows Users) Install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) (Community version - you need this step to build Insightface) -OR- only [VS C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile" -OR- if you don't want to install VS or VS C++ BT - follow [this steps (sec. I)](#insightfacebuild)
3. Go to the `extensions\sd-webui-comfyui\ComfyUI\custom_nodes`
4. Open Console or Terminal and run `git clone https://github.com/Gourieff/comfyui-reactor-node`
5. Go to the SD WebUI root folder, open Console or Terminal and run (Windows users)`.\venv\Scripts\activate` or (Linux/MacOS)`venv/bin/activate`
6. `python -m pip install -U pip`
7. `cd extensions\sd-webui-comfyui\ComfyUI\custom_nodes\comfyui-reactor-node`
8. `python install.py`
9. Please, wait until the installation process will be finished
10. Run SD WebUI and check console for the message that ReActor Node is running:
<img src="uploads/console_status_running.jpg" alt="console_status_running" width="759"/>
11. Go to the ComfyUI tab and find there ReActor Node inside the menu `image/postprocessing` or by using a search:
<img src="uploads/webui-demo.png" alt="webui-demo" width="100%"/>
<img src="uploads/search-demo.png" alt="webui-demo" width="1043"/>
12. Enjoy!
<a name="standalone">If you use Standalone [ComfyUI](https://github.com/comfyanonymous/ComfyUI) for Windows
1. Go to the `ComfyUI\custom_nodes` directory
2. Open Console and run `git clone https://github.com/Gourieff/comfyui-reactor-node`
3. Run install.bat
4. Run ComfyUI and find there ReActor Node inside the menu `image/postprocessing` or by using a search
## Usage
Just connect all required nodes and run the query
## Troubleshooting
<a name="insightfacebuild">**I. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:**
1. Download and put [prebuilt Insightface package](https://github.com/Gourieff/sd-webui-reactor/raw/main/example/insightface-0.7.3-cp310-cp310-win_amd64.whl) into the stable-diffusion-webui (A1111 or SD.Next) root folder (where you have "webui-user.bat" file) or into ComfyUI root folder if you use ComfyUI Portable
2. From the root folder run:
- (SD WebUI) CMD and `.\venv\Scripts\activate`
- (ComfyUI Portable) run CMD
3. Then update your PIP:
- (SD WebUI) `python -m pip install -U pip`
- (ComfyUI Portable) `python_embeded\python.exe -m pip install -U pip`
4. Then install Insightface:
- (SD WebUI) `pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
- (ComfyUI Portable) `python_embeded\python.exe -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl`
5. Enjoy!
## Updating
Just put .bat or .sh script from this [Repo](https://github.com/Gourieff/sd-webui-extensions-updater) to the `ComfyUI\custom_nodes` directory and run it when you need to check for updates
|
crystantine/sd-reactor-node
|
[
"region:us"
] |
2023-08-21T01:36:52+00:00
|
{}
|
2023-08-21T01:38:33+00:00
|
[] |
[] |
TAGS
#region-us
|
# ReActor Node 0.1.1b for ComfyUI
### The Fast and Simple "roop-like" Face Swap Extension Node for ComfyUI, based on ReActor (ex Roop-GE) SD-WebUI Face Swap Extension
> This Node goes without NSFW filter (uncensored, use it on your own responsibility)
---
Disclaimer | Installation | Usage | Troubleshooting | Updating
---
### Disclaimer
This software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.
The developers of this software are aware of its possible unethical applicaitons and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.
Users of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers and Contributors of this software are not responsible for actions of end-users.
## Installation
SD WebUI | Standalone ComfyUI
<a name="sdwebui">If you use AUTOMATIC1111 or SD.Next
1. Close (stop) your SD-WebUI/Comfy Server if it's running
2. (For Windows Users) Install Visual Studio 2022 (Community version - you need this step to build Insightface) -OR- only VS C++ Build Tools and select "Desktop Development with C++" under "Workloads -> Desktop & Mobile" -OR- if you don't want to install VS or VS C++ BT - follow this steps (sec. I)
3. Go to the 'extensions\sd-webui-comfyui\ComfyUI\custom_nodes'
4. Open Console or Terminal and run 'git clone URL
5. Go to the SD WebUI root folder, open Console or Terminal and run (Windows users)'.\venv\Scripts\activate' or (Linux/MacOS)'venv/bin/activate'
6. 'python -m pip install -U pip'
7. 'cd extensions\sd-webui-comfyui\ComfyUI\custom_nodes\comfyui-reactor-node'
8. 'python URL'
9. Please, wait until the installation process will be finished
10. Run SD WebUI and check console for the message that ReActor Node is running:
<img src="uploads/console_status_running.jpg" alt="console_status_running" width="759"/>
11. Go to the ComfyUI tab and find there ReActor Node inside the menu 'image/postprocessing' or by using a search:
<img src="uploads/URL" alt="webui-demo" width="100%"/>
<img src="uploads/URL" alt="webui-demo" width="1043"/>
12. Enjoy!
<a name="standalone">If you use Standalone ComfyUI for Windows
1. Go to the 'ComfyUI\custom_nodes' directory
2. Open Console and run 'git clone URL
3. Run URL
4. Run ComfyUI and find there ReActor Node inside the menu 'image/postprocessing' or by using a search
## Usage
Just connect all required nodes and run the query
## Troubleshooting
<a name="insightfacebuild">I. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:
1. Download and put prebuilt Insightface package into the stable-diffusion-webui (A1111 or SD.Next) root folder (where you have "URL" file) or into ComfyUI root folder if you use ComfyUI Portable
2. From the root folder run:
- (SD WebUI) CMD and '.\venv\Scripts\activate'
- (ComfyUI Portable) run CMD
3. Then update your PIP:
- (SD WebUI) 'python -m pip install -U pip'
- (ComfyUI Portable) 'python_embeded\URL -m pip install -U pip'
4. Then install Insightface:
- (SD WebUI) 'pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'
- (ComfyUI Portable) 'python_embeded\URL -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'
5. Enjoy!
## Updating
Just put .bat or .sh script from this Repo to the 'ComfyUI\custom_nodes' directory and run it when you need to check for updates
|
[
"# ReActor Node 0.1.1b for ComfyUI",
"### The Fast and Simple \"roop-like\" Face Swap Extension Node for ComfyUI, based on ReActor (ex Roop-GE) SD-WebUI Face Swap Extension\n\n> This Node goes without NSFW filter (uncensored, use it on your own responsibility) \n\n---\nDisclaimer | Installation | Usage | Troubleshooting | Updating\n\n---",
"### Disclaimer\n\nThis software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.\n\nThe developers of this software are aware of its possible unethical applicaitons and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.\n\nUsers of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers and Contributors of this software are not responsible for actions of end-users.",
"## Installation\n\nSD WebUI | Standalone ComfyUI\n\n<a name=\"sdwebui\">If you use AUTOMATIC1111 or SD.Next\n\n1. Close (stop) your SD-WebUI/Comfy Server if it's running\n2. (For Windows Users) Install Visual Studio 2022 (Community version - you need this step to build Insightface) -OR- only VS C++ Build Tools and select \"Desktop Development with C++\" under \"Workloads -> Desktop & Mobile\" -OR- if you don't want to install VS or VS C++ BT - follow this steps (sec. I)\n3. Go to the 'extensions\\sd-webui-comfyui\\ComfyUI\\custom_nodes'\n4. Open Console or Terminal and run 'git clone URL\n5. Go to the SD WebUI root folder, open Console or Terminal and run (Windows users)'.\\venv\\Scripts\\activate' or (Linux/MacOS)'venv/bin/activate'\n6. 'python -m pip install -U pip'\n7. 'cd extensions\\sd-webui-comfyui\\ComfyUI\\custom_nodes\\comfyui-reactor-node'\n8. 'python URL'\n9. Please, wait until the installation process will be finished\n10. Run SD WebUI and check console for the message that ReActor Node is running:\n<img src=\"uploads/console_status_running.jpg\" alt=\"console_status_running\" width=\"759\"/>\n\n11. Go to the ComfyUI tab and find there ReActor Node inside the menu 'image/postprocessing' or by using a search:\n<img src=\"uploads/URL\" alt=\"webui-demo\" width=\"100%\"/>\n<img src=\"uploads/URL\" alt=\"webui-demo\" width=\"1043\"/>\n\n12. Enjoy!\n\n<a name=\"standalone\">If you use Standalone ComfyUI for Windows\n\n1. Go to the 'ComfyUI\\custom_nodes' directory\n2. Open Console and run 'git clone URL\n3. Run URL\n4. Run ComfyUI and find there ReActor Node inside the menu 'image/postprocessing' or by using a search",
"## Usage\n\nJust connect all required nodes and run the query",
"## Troubleshooting\n\n<a name=\"insightfacebuild\">I. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:\n\n1. Download and put prebuilt Insightface package into the stable-diffusion-webui (A1111 or SD.Next) root folder (where you have \"URL\" file) or into ComfyUI root folder if you use ComfyUI Portable\n2. From the root folder run:\n - (SD WebUI) CMD and '.\\venv\\Scripts\\activate'\n - (ComfyUI Portable) run CMD\n3. Then update your PIP:\n - (SD WebUI) 'python -m pip install -U pip'\n - (ComfyUI Portable) 'python_embeded\\URL -m pip install -U pip'\n4. Then install Insightface:\n - (SD WebUI) 'pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'\n - (ComfyUI Portable) 'python_embeded\\URL -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'\n5. Enjoy!",
"## Updating\n\nJust put .bat or .sh script from this Repo to the 'ComfyUI\\custom_nodes' directory and run it when you need to check for updates"
] |
[
"TAGS\n#region-us \n",
"# ReActor Node 0.1.1b for ComfyUI",
"### The Fast and Simple \"roop-like\" Face Swap Extension Node for ComfyUI, based on ReActor (ex Roop-GE) SD-WebUI Face Swap Extension\n\n> This Node goes without NSFW filter (uncensored, use it on your own responsibility) \n\n---\nDisclaimer | Installation | Usage | Troubleshooting | Updating\n\n---",
"### Disclaimer\n\nThis software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.\n\nThe developers of this software are aware of its possible unethical applicaitons and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.\n\nUsers of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers and Contributors of this software are not responsible for actions of end-users.",
"## Installation\n\nSD WebUI | Standalone ComfyUI\n\n<a name=\"sdwebui\">If you use AUTOMATIC1111 or SD.Next\n\n1. Close (stop) your SD-WebUI/Comfy Server if it's running\n2. (For Windows Users) Install Visual Studio 2022 (Community version - you need this step to build Insightface) -OR- only VS C++ Build Tools and select \"Desktop Development with C++\" under \"Workloads -> Desktop & Mobile\" -OR- if you don't want to install VS or VS C++ BT - follow this steps (sec. I)\n3. Go to the 'extensions\\sd-webui-comfyui\\ComfyUI\\custom_nodes'\n4. Open Console or Terminal and run 'git clone URL\n5. Go to the SD WebUI root folder, open Console or Terminal and run (Windows users)'.\\venv\\Scripts\\activate' or (Linux/MacOS)'venv/bin/activate'\n6. 'python -m pip install -U pip'\n7. 'cd extensions\\sd-webui-comfyui\\ComfyUI\\custom_nodes\\comfyui-reactor-node'\n8. 'python URL'\n9. Please, wait until the installation process will be finished\n10. Run SD WebUI and check console for the message that ReActor Node is running:\n<img src=\"uploads/console_status_running.jpg\" alt=\"console_status_running\" width=\"759\"/>\n\n11. Go to the ComfyUI tab and find there ReActor Node inside the menu 'image/postprocessing' or by using a search:\n<img src=\"uploads/URL\" alt=\"webui-demo\" width=\"100%\"/>\n<img src=\"uploads/URL\" alt=\"webui-demo\" width=\"1043\"/>\n\n12. Enjoy!\n\n<a name=\"standalone\">If you use Standalone ComfyUI for Windows\n\n1. Go to the 'ComfyUI\\custom_nodes' directory\n2. Open Console and run 'git clone URL\n3. Run URL\n4. Run ComfyUI and find there ReActor Node inside the menu 'image/postprocessing' or by using a search",
"## Usage\n\nJust connect all required nodes and run the query",
"## Troubleshooting\n\n<a name=\"insightfacebuild\">I. (For Windows users) If you still cannot build Insightface for some reasons or just don't want to install Visual Studio or VS C++ Build Tools - do the following:\n\n1. Download and put prebuilt Insightface package into the stable-diffusion-webui (A1111 or SD.Next) root folder (where you have \"URL\" file) or into ComfyUI root folder if you use ComfyUI Portable\n2. From the root folder run:\n - (SD WebUI) CMD and '.\\venv\\Scripts\\activate'\n - (ComfyUI Portable) run CMD\n3. Then update your PIP:\n - (SD WebUI) 'python -m pip install -U pip'\n - (ComfyUI Portable) 'python_embeded\\URL -m pip install -U pip'\n4. Then install Insightface:\n - (SD WebUI) 'pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'\n - (ComfyUI Portable) 'python_embeded\\URL -m pip install insightface-0.7.3-cp310-cp310-win_amd64.whl'\n5. Enjoy!",
"## Updating\n\nJust put .bat or .sh script from this Repo to the 'ComfyUI\\custom_nodes' directory and run it when you need to check for updates"
] |
[
6,
13,
84,
179,
513,
14,
280,
42
] |
[
"passage: TAGS\n#region-us \n# ReActor Node 0.1.1b for ComfyUI### The Fast and Simple \"roop-like\" Face Swap Extension Node for ComfyUI, based on ReActor (ex Roop-GE) SD-WebUI Face Swap Extension\n\n> This Node goes without NSFW filter (uncensored, use it on your own responsibility) \n\n---\nDisclaimer | Installation | Usage | Troubleshooting | Updating\n\n---### Disclaimer\n\nThis software is meant to be a productive contribution to the rapidly growing AI-generated media industry. It will help artists with tasks such as animating a custom character or using the character as a model for clothing etc.\n\nThe developers of this software are aware of its possible unethical applicaitons and are committed to take preventative measures against them. We will continue to develop this project in the positive direction while adhering to law and ethics.\n\nUsers of this software are expected to use this software responsibly while abiding the local law. If face of a real person is being used, users are suggested to get consent from the concerned person and clearly mention that it is a deepfake when posting content online. Developers and Contributors of this software are not responsible for actions of end-users."
] |
215a378a6d345812f95868557894c27241a735a2
|
# Dataset Card for "libgen-fiction-metadata"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
emozilla/lg-f
|
[
"region:us"
] |
2023-08-21T01:47:40+00:00
|
{"dataset_info": {"features": [{"name": "ID", "dtype": "int64"}, {"name": "MD5", "dtype": "string"}, {"name": "Title", "dtype": "string"}, {"name": "Author", "dtype": "string"}, {"name": "Series", "dtype": "string"}, {"name": "Edition", "dtype": "string"}, {"name": "Language", "dtype": "string"}, {"name": "Year", "dtype": "string"}, {"name": "Publisher", "dtype": "string"}, {"name": "Pages", "dtype": "string"}, {"name": "Identifier", "dtype": "string"}, {"name": "GooglebookID", "dtype": "string"}, {"name": "ASIN", "dtype": "string"}, {"name": "Coverurl", "dtype": "string"}, {"name": "Extension", "dtype": "string"}, {"name": "Filesize", "dtype": "int64"}, {"name": "Library", "dtype": "string"}, {"name": "Issue", "dtype": "string"}, {"name": "Locator", "dtype": "string"}, {"name": "Commentary", "dtype": "string"}, {"name": "Generic", "dtype": "string"}, {"name": "Visible", "dtype": "string"}, {"name": "TimeAdded", "dtype": "string"}, {"name": "TimeLastModified", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 954063185, "num_examples": 2588707}], "download_size": 402113269, "dataset_size": 954063185}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]}
|
2023-08-21T01:48:07+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "libgen-fiction-metadata"
More Information needed
|
[
"# Dataset Card for \"libgen-fiction-metadata\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"libgen-fiction-metadata\"\n\nMore Information needed"
] |
[
6,
18
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"libgen-fiction-metadata\"\n\nMore Information needed"
] |
23b5838f7a08d875b4a3ffec43697c075433e3e7
|
# Dataset Card for "libgen-nonfiction-metadata"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
emozilla/lg-nf
|
[
"region:us"
] |
2023-08-21T01:48:26+00:00
|
{"dataset_info": {"features": [{"name": "ID", "dtype": "int64"}, {"name": "Title", "dtype": "string"}, {"name": "VolumeInfo", "dtype": "string"}, {"name": "Series", "dtype": "string"}, {"name": "Periodical", "dtype": "string"}, {"name": "Author", "dtype": "string"}, {"name": "Year", "dtype": "string"}, {"name": "Edition", "dtype": "string"}, {"name": "Publisher", "dtype": "string"}, {"name": "City", "dtype": "string"}, {"name": "Pages", "dtype": "string"}, {"name": "PagesInFile", "dtype": "int64"}, {"name": "Language", "dtype": "string"}, {"name": "Topic", "dtype": "string"}, {"name": "Library", "dtype": "string"}, {"name": "Issue", "dtype": "string"}, {"name": "Identifier", "dtype": "string"}, {"name": "ISSN", "dtype": "string"}, {"name": "ASIN", "dtype": "string"}, {"name": "UDC", "dtype": "string"}, {"name": "LBC", "dtype": "string"}, {"name": "DDC", "dtype": "string"}, {"name": "LCC", "dtype": "string"}, {"name": "Doi", "dtype": "string"}, {"name": "Googlebookid", "dtype": "string"}, {"name": "OpenLibraryID", "dtype": "string"}, {"name": "Commentary", "dtype": "string"}, {"name": "DPI", "dtype": "int64"}, {"name": "Color", "dtype": "string"}, {"name": "Cleaned", "dtype": "string"}, {"name": "Orientation", "dtype": "string"}, {"name": "Paginated", "dtype": "string"}, {"name": "Scanned", "dtype": "string"}, {"name": "Bookmarked", "dtype": "string"}, {"name": "Searchable", "dtype": "string"}, {"name": "Filesize", "dtype": "int64"}, {"name": "Extension", "dtype": "string"}, {"name": "MD5", "dtype": "string"}, {"name": "Generic", "dtype": "string"}, {"name": "Visible", "dtype": "string"}, {"name": "Locator", "dtype": "string"}, {"name": "Local", "dtype": "int64"}, {"name": "TimeAdded", "dtype": "string"}, {"name": "TimeLastModified", "dtype": "string"}, {"name": "Coverurl", "dtype": "string"}, {"name": "Tags", "dtype": "string"}, {"name": "IdentifierWODash", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 8003252615, "num_examples": 13122165}], "download_size": 3103416293, "dataset_size": 8003252615}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]}
|
2023-08-21T01:52:32+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "libgen-nonfiction-metadata"
More Information needed
|
[
"# Dataset Card for \"libgen-nonfiction-metadata\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"libgen-nonfiction-metadata\"\n\nMore Information needed"
] |
[
6,
19
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"libgen-nonfiction-metadata\"\n\nMore Information needed"
] |
6fc52d816b3da1075e4898654f36ee76c0e2da30
|
# Dataset Card for "my_custom_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
junehong/my_custom_dataset
|
[
"region:us"
] |
2023-08-21T01:49:32+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "audio", "dtype": "string"}, {"name": "sentence", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 7122729, "num_examples": 60000}, {"name": "test", "num_bytes": 655117, "num_examples": 5503}], "download_size": 3173503, "dataset_size": 7777846}}
|
2023-08-21T04:52:46+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "my_custom_dataset"
More Information needed
|
[
"# Dataset Card for \"my_custom_dataset\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"my_custom_dataset\"\n\nMore Information needed"
] |
[
6,
17
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"my_custom_dataset\"\n\nMore Information needed"
] |
e6f533571cfeb2c0046ba8bfb785c6b45255b7bd
|
# Dataset of libeccio/リベッチオ (Kantai Collection)
This is the dataset of libeccio/リベッチオ (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, long_hair, twintails, dark_skin, dark-skinned_female, brown_eyes, ribbon, hair_ribbon, fang, hat`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 465.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/libeccio_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 305.52 MiB | [Download](https://huggingface.co/datasets/CyberHarem/libeccio_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1156 | 648.79 MiB | [Download](https://huggingface.co/datasets/CyberHarem/libeccio_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 428.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/libeccio_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1156 | 849.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/libeccio_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/libeccio_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 8 |  |  |  |  |  | 1girl, looking_at_viewer, neckerchief, open_mouth, sailor_dress, simple_background, sleeveless_dress, solo, striped, white_background, smile, white_dress, white_sailor_collar, anchor, mini_hat, one-hour_drawing_challenge, dated |
| 1 | 5 |  |  |  |  |  | 1girl, cowboy_shot, neckerchief, one-hour_drawing_challenge, sailor_dress, simple_background, sleeveless_dress, solo, striped, white_background, white_dress, white_sailor_collar, dated, looking_at_viewer, twitter_username, smile, standing |
| 2 | 7 |  |  |  |  |  | 1girl, looking_at_viewer, open_mouth, sailor_dress, sleeveless, solo, striped, :d, blush, twitter_username |
| 3 | 5 |  |  |  |  |  | 1girl, blush, dress_lift, sailor_dress, sleeveless_dress, solo, striped_panties, looking_at_viewer, navel, open_mouth, white_dress, :d, cloud, day, lifted_by_self, sky, thigh_strap |
| 4 | 5 |  |  |  |  |  | 1girl, collarbone, frilled_bikini, looking_at_viewer, navel, official_alternate_costume, simple_background, smile, solo, white_background, white_bikini, blush, open_mouth, polka_dot, cowboy_shot, twitter_username, arms_up |
| 5 | 12 |  |  |  |  |  | 1girl, smile, jack-o'-lantern, open_mouth, solo, halloween_costume, wrist_scrunchie, pumpkin_hat, looking_at_viewer, skirt, blush, camisole, candy, claw_pose, collarbone, orange_scrunchie, white_background, simple_background |
| 6 | 5 |  |  |  |  |  | 1girl, italian_flag, solo, yukata, holding, bag, full_body, looking_at_viewer, shaved_ice, simple_background, smile, white_background, white_kimono, wide_sleeves, blush, open_mouth, paper_lantern, polka_dot, sandals, tongue_out |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | looking_at_viewer | neckerchief | open_mouth | sailor_dress | simple_background | sleeveless_dress | solo | striped | white_background | smile | white_dress | white_sailor_collar | anchor | mini_hat | one-hour_drawing_challenge | dated | cowboy_shot | twitter_username | standing | sleeveless | :d | blush | dress_lift | striped_panties | navel | cloud | day | lifted_by_self | sky | thigh_strap | collarbone | frilled_bikini | official_alternate_costume | white_bikini | polka_dot | arms_up | jack-o'-lantern | halloween_costume | wrist_scrunchie | pumpkin_hat | skirt | camisole | candy | claw_pose | orange_scrunchie | italian_flag | yukata | holding | bag | full_body | shaved_ice | white_kimono | wide_sleeves | paper_lantern | sandals | tongue_out |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:--------------|:-------------|:---------------|:--------------------|:-------------------|:-------|:----------|:-------------------|:--------|:--------------|:----------------------|:---------|:-----------|:-----------------------------|:--------|:--------------|:-------------------|:-----------|:-------------|:-----|:--------|:-------------|:------------------|:--------|:--------|:------|:-----------------|:------|:--------------|:-------------|:-----------------|:-----------------------------|:---------------|:------------|:----------|:------------------|:--------------------|:------------------|:--------------|:--------|:-----------|:--------|:------------|:-------------------|:---------------|:---------|:----------|:------|:------------|:-------------|:---------------|:---------------|:----------------|:----------|:-------------|
| 0 | 8 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | | X | X | X | X | X | X | X | X | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | X | | X | X | | | X | X | | | | | | | | | | X | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | X | | X | X | | X | X | | | | X | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | X | | X | | X | | X | | X | X | | | | | | | X | X | | | | X | | | X | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | |
| 5 | 12 |  |  |  |  |  | X | X | | X | | X | | X | | X | X | | | | | | | | | | | | X | | | | | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | X | | X | | X | | X | | X | X | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/libeccio_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T01:54:28+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T16:36:11+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of libeccio/リベッチオ (Kantai Collection)
=============================================
This is the dataset of libeccio/リベッチオ (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, long\_hair, twintails, dark\_skin, dark-skinned\_female, brown\_eyes, ribbon, hair\_ribbon, fang, hat', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
eeb6b961a5dc28c95ecac53f0aa4b91b3fbb0d6a
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/piqa](https://huggingface.co/datasets/piqa)
Lilac dataset config:
```namespace: lilac
name: piqa
source:
dataset_name: piqa
source_name: huggingface
embeddings:
- path: goal
embedding: gte-small
- path: sol1
embedding: gte-small
- path: sol2
embedding: gte-small
signals:
- path: goal
signal:
signal_name: near_dup
- path: goal
signal:
signal_name: pii
- path: goal
signal:
signal_name: lang_detection
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: goal
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: goal
signal:
signal_name: text_statistics
- path: sol1
signal:
signal_name: near_dup
- path: sol1
signal:
signal_name: pii
- path: sol1
signal:
signal_name: lang_detection
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: sol1
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: sol1
signal:
signal_name: text_statistics
- path: sol2
signal:
signal_name: near_dup
- path: sol2
signal:
signal_name: pii
- path: sol2
signal:
signal_name: lang_detection
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: sol2
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: sol2
signal:
signal_name: text_statistics
settings:
ui:
media_paths:
- sol1
- sol2
- goal
markdown_paths: []
```
|
lilacai/lilac-piqa
|
[
"region:us"
] |
2023-08-21T02:13:22+00:00
|
{}
|
2023-12-07T13:57:22+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
7ac4f1d249fcaca9855da8aa79f8bf922386723d
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/derek-thomas/ScienceQA](https://huggingface.co/datasets/derek-thomas/ScienceQA)
Lilac dataset config:
```namespace: lilac
name: science-qa-derek-thomas
source:
dataset_name: derek-thomas/ScienceQA
source_name: huggingface
embeddings:
- path: lecture
embedding: gte-small
signals:
- path: lecture
signal:
signal_name: near_dup
- path: lecture
signal:
signal_name: pii
- path: lecture
signal:
signal_name: lang_detection
- path: lecture
signal:
signal_name: text_statistics
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: lecture
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: lecture
signal:
signal_name: cluster_dbscan
- path: lecture
signal:
embedding: gte-small
signal_name: cluster_hdbscan
settings:
ui:
media_paths:
- lecture
markdown_paths: []
tags:
- science
```
|
lilacai/lilac-science-qa-derek-thomas
|
[
"region:us"
] |
2023-08-21T02:15:02+00:00
|
{}
|
2023-12-07T13:57:23+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
91e280367a339521ec3283ca7c3c5b9bca097302
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/EleutherAI/pile](https://huggingface.co/datasets/EleutherAI/pile)
Lilac dataset config:
```namespace: lilac
name: enron-emails
source:
dataset_name: EleutherAI/pile
config_name: enron_emails
sample_size: 100000
source_name: huggingface
embeddings:
- path: text
embedding: gte-small
signals:
- path: text
signal:
signal_name: near_dup
- path: text
signal:
signal_name: pii
- path: text
signal:
signal_name: lang_detection
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
signal_name: text_statistics
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
signal_name: cluster_dbscan
- path: text
signal:
embedding: gte-small
signal_name: cluster_hdbscan
settings:
ui:
media_paths:
- text
markdown_paths: []
tags:
- business
```
|
lilacai/lilac-enron-emails
|
[
"region:us"
] |
2023-08-21T02:16:09+00:00
|
{}
|
2023-12-07T13:57:26+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
e14f04abd37cd73ef447fed7ec1a4045b895c9c7
|
# Dataset of warspite (Kantai Collection)
This is the dataset of warspite (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `blonde_hair, long_hair, blue_eyes, braid, french_braid, crown, mini_crown, hairband, breasts, large_breasts, hair_between_eyes, ribbon, red_ribbon`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 647.42 MiB | [Download](https://huggingface.co/datasets/CyberHarem/warspite_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 382.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/warspite_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1157 | 783.31 MiB | [Download](https://huggingface.co/datasets/CyberHarem/warspite_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 579.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/warspite_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1157 | 1.06 GiB | [Download](https://huggingface.co/datasets/CyberHarem/warspite_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/warspite_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 22 |  |  |  |  |  | 1girl, long_sleeves, necklace, off-shoulder_dress, red_rose, solo, white_dress, corset, white_thighhighs, garter_straps, looking_at_viewer, smile, sitting, scepter, cleavage, throne, crossed_legs |
| 1 | 24 |  |  |  |  |  | 1girl, necklace, off-shoulder_dress, red_rose, solo, white_dress, long_sleeves, upper_body, cleavage, looking_at_viewer, smile, white_background, simple_background, corset |
| 2 | 7 |  |  |  |  |  | 1girl, cowboy_shot, long_sleeves, necklace, off-shoulder_dress, red_rose, solo, white_dress, cleavage, corset, dress_lift, looking_at_viewer, simple_background, white_background, garter_belt, garter_straps, white_panties, ring, white_thighhighs |
| 3 | 5 |  |  |  |  |  | 1boy, 1girl, blush, breasts_out, clothed_sex, hetero, long_sleeves, nipples, penis, solo_focus, thighhighs, vaginal, white_dress, open_mouth, sex_from_behind, sweat, trembling, bent_over, doggystyle, necklace, off-shoulder_dress, red_rose, all_fours, bare_shoulders, bouncing_breasts, garter_straps, hanging_breasts, heart, high_heels, mosaic_censoring, panties_aside, pussy_juice, spread_legs |
| 4 | 7 |  |  |  |  |  | 1girl, alternate_costume, looking_at_viewer, short_sleeves, solo, hair_flower, smile, white_hairband, red_rose, white_dress, upper_body, white_shirt, one-hour_drawing_challenge, open_mouth, white_background |
| 5 | 6 |  |  |  |  |  | 1girl, looking_at_viewer, solo, white_bikini, cleavage, smile, cowboy_shot, one-hour_drawing_challenge, dated, red_rose |
| 6 | 5 |  |  |  |  |  | 1girl, blue_sky, day, navel, ocean, outdoors, solo, beach, cleavage, cloud, looking_at_viewer, open_mouth, white_bikini, collarbone, blush, cowboy_shot, hair_flower, standing |
| 7 | 16 |  |  |  |  |  | 1girl, hetero, sex, 1boy, blush, nipples, penis, vaginal, solo_focus, nude, bar_censor, navel, open_mouth, sweat, thighhighs, lying, pussy, straddling |
| 8 | 9 |  |  |  |  |  | 1girl, alternate_costume, floral_print, hair_flower, ponytail, red_kimono, solo, obi, looking_at_viewer, red_rose, wide_sleeves, print_kimono, smile, upper_body, alternate_hairstyle, black_hairband, white_background |
| 9 | 7 |  |  |  |  |  | 1girl, playboy_bunny, rabbit_ears, solo, black_pantyhose, fake_animal_ears, looking_at_viewer, simple_background, strapless_leotard, white_background, alternate_costume, black_leotard, detached_collar, rabbit_tail, cowboy_shot, one-hour_drawing_challenge, wrist_cuffs, dated, red_bowtie, smile |
| 10 | 5 |  |  |  |  |  | 1girl, nude, pussy, solo, anus, blush, navel, nipples, ass, looking_at_viewer, looking_back, mosaic_censoring, sitting, spread_legs, sweat, white_thighhighs |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | long_sleeves | necklace | off-shoulder_dress | red_rose | solo | white_dress | corset | white_thighhighs | garter_straps | looking_at_viewer | smile | sitting | scepter | cleavage | throne | crossed_legs | upper_body | white_background | simple_background | cowboy_shot | dress_lift | garter_belt | white_panties | ring | 1boy | blush | breasts_out | clothed_sex | hetero | nipples | penis | solo_focus | thighhighs | vaginal | open_mouth | sex_from_behind | sweat | trembling | bent_over | doggystyle | all_fours | bare_shoulders | bouncing_breasts | hanging_breasts | heart | high_heels | mosaic_censoring | panties_aside | pussy_juice | spread_legs | alternate_costume | short_sleeves | hair_flower | white_hairband | white_shirt | one-hour_drawing_challenge | white_bikini | dated | blue_sky | day | navel | ocean | outdoors | beach | cloud | collarbone | standing | sex | nude | bar_censor | lying | pussy | straddling | floral_print | ponytail | red_kimono | obi | wide_sleeves | print_kimono | alternate_hairstyle | black_hairband | playboy_bunny | rabbit_ears | black_pantyhose | fake_animal_ears | strapless_leotard | black_leotard | detached_collar | rabbit_tail | wrist_cuffs | red_bowtie | anus | ass | looking_back |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:---------------|:-----------|:---------------------|:-----------|:-------|:--------------|:---------|:-------------------|:----------------|:--------------------|:--------|:----------|:----------|:-----------|:---------|:---------------|:-------------|:-------------------|:--------------------|:--------------|:-------------|:--------------|:----------------|:-------|:-------|:--------|:--------------|:--------------|:---------|:----------|:--------|:-------------|:-------------|:----------|:-------------|:------------------|:--------|:------------|:------------|:-------------|:------------|:-----------------|:-------------------|:------------------|:--------|:-------------|:-------------------|:----------------|:--------------|:--------------|:--------------------|:----------------|:--------------|:-----------------|:--------------|:-----------------------------|:---------------|:--------|:-----------|:------|:--------|:--------|:-----------|:--------|:--------|:-------------|:-----------|:------|:-------|:-------------|:--------|:--------|:-------------|:---------------|:-----------|:-------------|:------|:---------------|:---------------|:----------------------|:-----------------|:----------------|:--------------|:------------------|:-------------------|:--------------------|:----------------|:------------------|:--------------|:--------------|:-------------|:-------|:------|:---------------|
| 0 | 22 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 24 |  |  |  |  |  | X | X | X | X | X | X | X | X | | | X | X | | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | X | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | X | X | X | X | | X | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 7 |  |  |  |  |  | X | | | | X | X | X | | | | X | X | | | | | | X | X | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | | | | X | X | | | | | X | X | | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | | | | | X | | | | | X | | | | X | | | | | | X | | | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | X | | | | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 16 |  |  |  |  |  | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | | | X | X | X | X | X | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 8 | 9 |  |  |  |  |  | X | | | | X | X | | | | | X | X | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | |
| 9 | 7 |  |  |  |  |  | X | | | | | X | | | | | X | X | | | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | X | | X | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | |
| 10 | 5 |  |  |  |  |  | X | | | | | X | | | X | | X | | X | | | | | | | | | | | | | | X | | | | X | | | | | | | X | | | | | | | | | | X | | | X | | | | | | | | | | | X | | | | | | | | X | | | X | | | | | | | | | | | | | | | | | | | | X | X | X |
|
CyberHarem/warspite_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T02:19:32+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-16T01:18:13+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of warspite (Kantai Collection)
=======================================
This is the dataset of warspite (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'blonde\_hair, long\_hair, blue\_eyes, braid, french\_braid, crown, mini\_crown, hairband, breasts, large\_breasts, hair\_between\_eyes, ribbon, red\_ribbon', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
b0d8b70f66c6b1a51ce8d136c5b50df066e1d75e
|
# Dataset Card for "fw_num_bi_train_1000_eval_100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tyzhu/fw_num_bi_train_1000_eval_100
|
[
"region:us"
] |
2023-08-21T02:39:38+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "train_doc2id", "path": "data/train_doc2id-*"}, {"split": "train_id2doc", "path": "data/train_id2doc-*"}, {"split": "train_find_word", "path": "data/train_find_word-*"}, {"split": "eval_find_word", "path": "data/eval_find_word-*"}]}], "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 225375, "num_examples": 3200}, {"name": "train_doc2id", "num_bytes": 87993, "num_examples": 1100}, {"name": "train_id2doc", "num_bytes": 91293, "num_examples": 1100}, {"name": "train_find_word", "num_bytes": 46089, "num_examples": 1000}, {"name": "eval_find_word", "num_bytes": 4723, "num_examples": 100}], "download_size": 104282, "dataset_size": 455473}}
|
2023-08-21T05:36:06+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "fw_num_bi_train_1000_eval_100"
More Information needed
|
[
"# Dataset Card for \"fw_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"fw_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
[
6,
26
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"fw_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
3946870660ac1a52070c4c16f8f31c1c7e63f798
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/cais/mmlu](https://huggingface.co/datasets/cais/mmlu)
Lilac dataset config:
```embeddings:
- embedding: gte-small
path: [choices, '*']
- {embedding: gte-small, path: question}
name: mmlu_professional_law
namespace: lilac
settings:
preferred_embedding: gte-small
ui:
media_paths:
- question
- [choices, '*']
signals:
- path: question
signal: {signal_name: text_statistics}
- path: question
signal: {signal_name: pii}
- path: question
signal: {signal_name: near_dup}
- path: [choices, '*']
signal: {signal_name: text_statistics}
- path: [choices, '*']
signal: {signal_name: spacy_ner}
- path: question
signal: {signal_name: lang_detection}
- path: [choices, '*']
signal: {signal_name: near_dup}
- path: [choices, '*']
signal: {signal_name: pii}
- path: [choices, '*']
signal: {signal_name: lang_detection}
- path: question
signal: {signal_name: spacy_ner}
- path: question
signal: {concept_name: non-english, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: question
signal: {concept_name: profanity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: question
signal: {concept_name: source-code, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: question
signal: {concept_name: question, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: question
signal: {concept_name: toxicity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: question
signal: {concept_name: legal-termination, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: question
signal: {concept_name: negative-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: question
signal: {concept_name: positive-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: legal-termination, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: non-english, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: toxicity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: profanity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: question, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: source-code, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: positive-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: [choices, '*']
signal: {concept_name: negative-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
source: {config_name: professional_law, dataset_name: cais/mmlu, source_name: huggingface}
tags: [legal]
```
|
lilacai/lilac-mmlu_professional_law
|
[
"region:us"
] |
2023-08-21T02:44:27+00:00
|
{}
|
2023-09-25T23:14:46+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
7e99db36695285abc67b1b3527d67ddeed80d9ae
|
```
from datasets import load_dataset
ds=load_dataset("if001/oscar_2023_filtered")
ds['train']
---
Dataset({
features: ['text'],
num_rows: 312396
})
```
oscar 2023をfilterしたもの
https://huggingface.co/datasets/oscar-corpus/OSCAR-2301
詳細はコードを参照
https://github.com/if001/HojiChar_OSCAR_sample/tree/0.0.4
|
if001/oscar_2023_filtered
|
[
"task_categories:text-generation",
"language:ja",
"license:cc0-1.0",
"region:us"
] |
2023-08-21T02:56:56+00:00
|
{"language": ["ja"], "license": "cc0-1.0", "task_categories": ["text-generation"], "dataset_info": {"features": [{"name": "text", "dtype": "string"}]}}
|
2023-08-31T12:35:37+00:00
|
[] |
[
"ja"
] |
TAGS
#task_categories-text-generation #language-Japanese #license-cc0-1.0 #region-us
|
oscar 2023をfilterしたもの
URL
詳細はコードを参照
URL
|
[] |
[
"TAGS\n#task_categories-text-generation #language-Japanese #license-cc0-1.0 #region-us \n"
] |
[
31
] |
[
"passage: TAGS\n#task_categories-text-generation #language-Japanese #license-cc0-1.0 #region-us \n"
] |
372dff04c93e2c7c7ac09cb272201c123d98ba6d
|
# Dataset Card for "merge_new_para_detection_data_v4"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
mHossain/merge_new_para_detection_data_v4
|
[
"region:us"
] |
2023-08-21T02:59:48+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "Unnamed: 0", "dtype": "int64"}, {"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 9374410.8, "num_examples": 54000}, {"name": "test", "num_bytes": 1041601.2, "num_examples": 6000}], "download_size": 4724664, "dataset_size": 10416012.0}}
|
2023-08-21T02:59:55+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "merge_new_para_detection_data_v4"
More Information needed
|
[
"# Dataset Card for \"merge_new_para_detection_data_v4\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"merge_new_para_detection_data_v4\"\n\nMore Information needed"
] |
[
6,
24
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"merge_new_para_detection_data_v4\"\n\nMore Information needed"
] |
80b716e51b0bdd7d3ff6bd1f4449fdb3be6953a1
|
# Dataset Card for "fw_bi_train_10000_eval_100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tyzhu/fw_bi_train_10000_eval_100
|
[
"region:us"
] |
2023-08-21T03:00:30+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "eval_find_word", "path": "data/eval_find_word-*"}]}], "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2135417, "num_examples": 30200}, {"name": "eval_find_word", "num_bytes": 4823, "num_examples": 100}], "download_size": 930254, "dataset_size": 2140240}}
|
2023-08-21T03:00:37+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "fw_bi_train_10000_eval_100"
More Information needed
|
[
"# Dataset Card for \"fw_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"fw_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
[
6,
24
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"fw_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
8ec6ae3ee0911bebec12e14dd01282d0222e084c
|
# Thống kê dữ liệu và số urls (chưa dedup) theo domains
Để tổng hợp dữ liệu và url dedup cho từng domain dùng lệnh
`xzcat */*/*keyword*.jsonl.xz | python3 url_dedup_stdin.py`
```
9948mb 413k 2023 http://quangduc.com
7592mb 312k 2023 http://thuvienhoasen.org
5966mb 135k 2023 http://tangthuphathoc.net
5310mb 1312k 2023 http://rongmotamhon.net
45331mb 3889k 2023 http://tailieu.vn
14118mb 1012k 2023 http://vi.wikipedia.org
11109mb 3494k 2023 http://baomoi.com
10035mb 22k 2018 http://kiemhiepthuvien.forumsmusic.com
9692mb 2230k 2023 http://eva.vn
...
```
Xem bản đầy đủ ở `cc_domain_stats.txt.gz`
|
tiendung/cc-vi_domains
|
[
"region:us"
] |
2023-08-21T03:00:41+00:00
|
{}
|
2023-09-21T01:19:00+00:00
|
[] |
[] |
TAGS
#region-us
|
# Thống kê dữ liệu và số urls (chưa dedup) theo domains
Để tổng hợp dữ liệu và url dedup cho từng domain dùng lệnh
'xzcat */*/*keyword*.URL | python3 url_dedup_stdin.py'
Xem bản đầy đủ ở 'cc_domain_stats.URL'
|
[
"# Thống kê dữ liệu và số urls (chưa dedup) theo domains\n\nĐể tổng hợp dữ liệu và url dedup cho từng domain dùng lệnh\n'xzcat */*/*keyword*.URL | python3 url_dedup_stdin.py'\n\n\n\nXem bản đầy đủ ở 'cc_domain_stats.URL'"
] |
[
"TAGS\n#region-us \n",
"# Thống kê dữ liệu và số urls (chưa dedup) theo domains\n\nĐể tổng hợp dữ liệu và url dedup cho từng domain dùng lệnh\n'xzcat */*/*keyword*.URL | python3 url_dedup_stdin.py'\n\n\n\nXem bản đầy đủ ở 'cc_domain_stats.URL'"
] |
[
6,
83
] |
[
"passage: TAGS\n#region-us \n# Thống kê dữ liệu và số urls (chưa dedup) theo domains\n\nĐể tổng hợp dữ liệu và url dedup cho từng domain dùng lệnh\n'xzcat */*/*keyword*.URL | python3 url_dedup_stdin.py'\n\n\n\nXem bản đầy đủ ở 'cc_domain_stats.URL'"
] |
a62c3a8f5bc12c97a86d1fd3737e6e4e8aed4e58
|
# Dataset of i_58/伊58/伊58 (Kantai Collection)
This is the dataset of i_58/伊58/伊58 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `short_hair, ahoge, pink_hair, hair_ornament, pink_eyes, red_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-----------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 375.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_58_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 265.80 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_58_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1024 | 534.36 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_58_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 351.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_58_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1024 | 671.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_58_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/i_58_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 10 |  |  |  |  |  | 1girl, blue_one-piece_swimsuit, blue_sailor_collar, looking_at_viewer, school_swimsuit, serafuku, solo, swimsuit_under_clothes, cowboy_shot, one-hour_drawing_challenge, pink_neckerchief, pink_necktie, sailor_shirt, simple_background, twitter_username, white_background, dated |
| 1 | 35 |  |  |  |  |  | 1girl, school_swimsuit, serafuku, solo, swimsuit_under_clothes, looking_at_viewer, torpedo, one-piece_swimsuit, smile, blush, open_mouth |
| 2 | 5 |  |  |  |  |  | 1girl, air_bubble, school_swimsuit, serafuku, solo, swimsuit_under_clothes, underwater, one-piece_swimsuit, torpedo, blush, open_mouth, smile, fish, looking_at_viewer |
| 3 | 12 |  |  |  |  |  | school_swimsuit, serafuku, swimsuit_under_clothes, 2girls, long_hair, open_mouth, blush, one-piece_swimsuit |
| 4 | 9 |  |  |  |  |  | 1girl, blush, hetero, one-piece_swimsuit, penis, school_swimsuit, solo_focus, open_mouth, sex, swimsuit_aside, vaginal, 1boy, cum_in_pussy, nipples, small_breasts, spread_legs, bar_censor, serafuku, mosaic_censoring, shirt_lift, swimsuit_under_clothes, tears, torn_clothes |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_one-piece_swimsuit | blue_sailor_collar | looking_at_viewer | school_swimsuit | serafuku | solo | swimsuit_under_clothes | cowboy_shot | one-hour_drawing_challenge | pink_neckerchief | pink_necktie | sailor_shirt | simple_background | twitter_username | white_background | dated | torpedo | one-piece_swimsuit | smile | blush | open_mouth | air_bubble | underwater | fish | 2girls | long_hair | hetero | penis | solo_focus | sex | swimsuit_aside | vaginal | 1boy | cum_in_pussy | nipples | small_breasts | spread_legs | bar_censor | mosaic_censoring | shirt_lift | tears | torn_clothes |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------------|:---------------------|:--------------------|:------------------|:-----------|:-------|:-------------------------|:--------------|:-----------------------------|:-------------------|:---------------|:---------------|:--------------------|:-------------------|:-------------------|:--------|:----------|:---------------------|:--------|:--------|:-------------|:-------------|:-------------|:-------|:---------|:------------|:---------|:--------|:-------------|:------|:-----------------|:----------|:-------|:---------------|:----------|:----------------|:--------------|:-------------|:-------------------|:-------------|:--------|:---------------|
| 0 | 10 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 35 |  |  |  |  |  | X | | | X | X | X | X | X | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | | | X | X | X | X | X | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | |
| 3 | 12 |  |  |  |  |  | | | | | X | X | | X | | | | | | | | | | | X | | X | X | | | | X | X | | | | | | | | | | | | | | | | |
| 4 | 9 |  |  |  |  |  | X | | | | X | X | | X | | | | | | | | | | | X | | X | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/i_58_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T03:01:18+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T05:27:36+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of i\_58/伊58/伊58 (Kantai Collection)
============================================
This is the dataset of i\_58/伊58/伊58 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'short\_hair, ahoge, pink\_hair, hair\_ornament, pink\_eyes, red\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
90d50bf7173bf25e1cc77e7b371d1c71c2210b3f
|
# Dataset Card for "fw_bi_num_train_10000_eval_100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tyzhu/fw_bi_num_train_10000_eval_100
|
[
"region:us"
] |
2023-08-21T03:02:28+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "eval_find_word", "path": "data/eval_find_word-*"}]}], "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2135417, "num_examples": 30200}, {"name": "eval_find_word", "num_bytes": 4823, "num_examples": 100}], "download_size": 930254, "dataset_size": 2140240}}
|
2023-08-21T03:02:35+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "fw_bi_num_train_10000_eval_100"
More Information needed
|
[
"# Dataset Card for \"fw_bi_num_train_10000_eval_100\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"fw_bi_num_train_10000_eval_100\"\n\nMore Information needed"
] |
[
6,
26
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"fw_bi_num_train_10000_eval_100\"\n\nMore Information needed"
] |
c8689c8d90f1f20a1f19037d71339b6712ec6c53
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/pile-of-law/pile-of-law](https://huggingface.co/datasets/pile-of-law/pile-of-law)
Lilac dataset config:
```embeddings:
- {embedding: gte-small, path: text}
name: pile-of-law-r-legaladvice
namespace: lilac
settings:
preferred_embedding: gte-small
ui:
media_paths: [text]
signals:
- path: text
signal: {signal_name: near_dup}
- path: text
signal: {signal_name: text_statistics}
- path: text
signal: {signal_name: pii}
- path: text
signal: {signal_name: lang_detection}
- path: text
signal: {signal_name: spacy_ner}
- path: text
signal: {concept_name: positive-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: text
signal: {concept_name: toxicity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
signal: {concept_name: non-english, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
signal: {concept_name: negative-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: text
signal: {concept_name: profanity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
signal: {concept_name: source-code, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: text
signal: {concept_name: legal-termination, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: text
signal: {concept_name: question, embedding: gte-small, namespace: lilac, signal_name: concept_score}
source: {config_name: r_legaladvice, dataset_name: pile-of-law/pile-of-law, source_name: huggingface}
tags: [legal]
```
|
lilacai/lilac-pile-of-law-r-legaladvice
|
[
"region:us"
] |
2023-08-21T03:04:49+00:00
|
{}
|
2023-09-25T23:14:50+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
e3bedb5c8130405701f5c3c5d5114168414b9156
|
# Dataset of teruzuki/照月/照月 (Kantai Collection)
This is the dataset of teruzuki/照月/照月 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, braid, twin_braids, hair_ornament, headband, light_brown_hair, breasts, propeller_hair_ornament, brown_hair, blue_eyes, grey_eyes, black_headband, hairband`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 560.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/teruzuki_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 327.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/teruzuki_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1197 | 710.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/teruzuki_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 500.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/teruzuki_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1197 | 984.90 MiB | [Download](https://huggingface.co/datasets/CyberHarem/teruzuki_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/teruzuki_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, blush, clothes_writing, gloves, looking_at_viewer, open_mouth, serafuku, solo, neckerchief, smile, miniskirt, pleated_skirt |
| 1 | 8 |  |  |  |  |  | 1girl, black_sailor_collar, black_skirt, clothes_writing, cowboy_shot, hachimaki, pleated_skirt, serafuku, simple_background, solo, white_background, yellow_neckerchief, black_gloves, blush, corset, open_mouth, looking_at_viewer, short_sleeves |
| 2 | 6 |  |  |  |  |  | 1girl, black_sailor_collar, black_skirt, clothes_writing, cowboy_shot, hachimaki, pleated_skirt, serafuku, short_sleeves, simple_background, smile, solo, white_background, yellow_neckerchief, corset, looking_at_viewer, open_mouth, hair_between_eyes, multicolored_gloves, white_gloves, black_gloves, twitter_username |
| 3 | 6 |  |  |  |  |  | 1girl, black_skirt, clothes_writing, corset, hachimaki, pleated_skirt, serafuku, simple_background, solo, white_thighhighs, black_sailor_collar, looking_at_viewer, white_background, white_gloves, yellow_neckerchief, twitter_username, multicolored_gloves |
| 4 | 5 |  |  |  |  |  | 1girl, black_sailor_collar, clothes_writing, hachimaki, looking_at_viewer, serafuku, smile, solo, upper_body, multicolored_gloves, open_mouth, simple_background, white_background, yellow_neckerchief, black_gloves |
| 5 | 8 |  |  |  |  |  | denim_shorts, looking_at_viewer, short_shorts, simple_background, 1girl, collarbone, cowboy_shot, navel, white_background, white_bikini, cleavage, large_breasts, side-tie_bikini_bottom, smile, solo, clothes_writing, open_mouth, blush, front-tie_bikini_top, hachimaki, hair_between_eyes, medium_breasts, groin |
| 6 | 7 |  |  |  |  |  | 1girl, blush, cleavage, collarbone, looking_at_viewer, solo, day, hachimaki, navel, open_mouth, outdoors, smile, white_bikini, clothes_writing, hair_between_eyes, large_breasts, blue_sky, cowboy_shot, short_shorts, beach, cloud, denim_shorts, front-tie_top, ocean |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blush | clothes_writing | gloves | looking_at_viewer | open_mouth | serafuku | solo | neckerchief | smile | miniskirt | pleated_skirt | black_sailor_collar | black_skirt | cowboy_shot | hachimaki | simple_background | white_background | yellow_neckerchief | black_gloves | corset | short_sleeves | hair_between_eyes | multicolored_gloves | white_gloves | twitter_username | white_thighhighs | upper_body | denim_shorts | short_shorts | collarbone | navel | white_bikini | cleavage | large_breasts | side-tie_bikini_bottom | front-tie_bikini_top | medium_breasts | groin | day | outdoors | blue_sky | beach | cloud | front-tie_top | ocean |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:------------------|:---------|:--------------------|:-------------|:-----------|:-------|:--------------|:--------|:------------|:----------------|:----------------------|:--------------|:--------------|:------------|:--------------------|:-------------------|:---------------------|:---------------|:---------|:----------------|:--------------------|:----------------------|:---------------|:-------------------|:-------------------|:-------------|:---------------|:---------------|:-------------|:--------|:---------------|:-----------|:----------------|:-------------------------|:-----------------------|:-----------------|:--------|:------|:-----------|:-----------|:--------|:--------|:----------------|:--------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 8 |  |  |  |  |  | X | X | X | | X | X | X | X | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | | X | | X | X | X | X | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | | X | | X | | X | X | | | | X | X | X | | X | X | X | X | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | | X | | X | X | X | X | | X | | | X | | | X | X | X | X | X | | | | X | | | | X | | | | | | | | | | | | | | | | | | |
| 5 | 8 |  |  |  |  |  | X | X | X | | X | X | | X | | X | | | | | X | X | X | X | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | |
| 6 | 7 |  |  |  |  |  | X | X | X | | X | X | | X | | X | | | | | X | X | | | | | | | X | | | | | | X | X | X | X | X | X | X | | | | | X | X | X | X | X | X | X |
|
CyberHarem/teruzuki_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T03:07:24+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T16:20:03+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of teruzuki/照月/照月 (Kantai Collection)
=============================================
This is the dataset of teruzuki/照月/照月 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, braid, twin\_braids, hair\_ornament, headband, light\_brown\_hair, breasts, propeller\_hair\_ornament, brown\_hair, blue\_eyes, grey\_eyes, black\_headband, hairband', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
d5340c60f9b3d71b14a6b8ab3f798526e695ae36
|
# Dataset Card for "Application_125K"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
EgilKarlsen/Application_125K
|
[
"region:us"
] |
2023-08-21T03:14:48+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}]}], "dataset_info": {"features": [{"name": "log", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 35303437, "num_examples": 112500}, {"name": "validation", "num_bytes": 3955784, "num_examples": 12500}], "download_size": 7689105, "dataset_size": 39259221}}
|
2023-08-21T03:14:51+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "Application_125K"
More Information needed
|
[
"# Dataset Card for \"Application_125K\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"Application_125K\"\n\nMore Information needed"
] |
[
6,
15
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"Application_125K\"\n\nMore Information needed"
] |
472c982470921299b7195cde38f04c6562dbeb37
|
# lilac/open-asssistant-conversations
This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1)
To download the dataset to a local directory:
```bash
lilac download lilacai/lilac-open-asssistant-conversations
```
or from python with:
```py
ll.download("lilacai/lilac-open-asssistant-conversations")
```
|
lilacai/lilac-open-asssistant-conversations
|
[
"Lilac",
"region:us"
] |
2023-08-21T03:32:52+00:00
|
{"tags": ["Lilac"]}
|
2024-01-17T22:31:49+00:00
|
[] |
[] |
TAGS
#Lilac #region-us
|
# lilac/open-asssistant-conversations
This dataset is a Lilac processed dataset. Original dataset: URL
To download the dataset to a local directory:
or from python with:
|
[
"# lilac/open-asssistant-conversations\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
"TAGS\n#Lilac #region-us \n",
"# lilac/open-asssistant-conversations\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
9,
47
] |
[
"passage: TAGS\n#Lilac #region-us \n# lilac/open-asssistant-conversations\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
25a7a2925a3ba84313a2c6d126a790f5d1eb6081
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/squad_v2](https://huggingface.co/datasets/squad_v2)
Lilac dataset config:
```embeddings:
- {embedding: gte-small, path: context}
name: squad_v2
namespace: local
settings:
preferred_embedding: gte-small
ui:
media_paths:
- context
- question
- [answers, text, '*']
signals:
- path: context
signal: {signal_name: text_statistics}
- path: context
signal: {signal_name: pii}
- path: context
signal: {signal_name: near_dup}
- path: question
signal: {signal_name: spacy_ner}
- path: question
signal: {signal_name: pii}
- path: [answers, text, '*']
signal: {signal_name: pii}
- path: [answers, text, '*']
signal: {signal_name: spacy_ner}
- path: [answers, text, '*']
signal: {signal_name: near_dup}
- path: context
signal: {signal_name: lang_detection}
- path: [answers, text, '*']
signal: {signal_name: lang_detection}
- path: question
signal: {signal_name: near_dup}
- path: question
signal: {signal_name: lang_detection}
- path: [answers, text, '*']
signal: {signal_name: text_statistics}
- path: question
signal: {signal_name: text_statistics}
- path: context
signal: {signal_name: spacy_ner}
- path: context
signal: {concept_name: question, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: context
signal: {concept_name: non-english, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: context
signal: {concept_name: positive-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: context
signal: {concept_name: negative-sentiment, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: context
signal: {concept_name: legal-termination, embedding: gte-small, namespace: lilac,
signal_name: concept_score}
- path: context
signal: {concept_name: source-code, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: context
signal: {concept_name: toxicity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
- path: context
signal: {concept_name: profanity, embedding: gte-small, namespace: lilac, signal_name: concept_score}
source: {dataset_name: squad_v2, source_name: huggingface}
tags: [machine-learning]
```
|
lilacai/lilac-squad_v2
|
[
"region:us"
] |
2023-08-21T03:37:59+00:00
|
{}
|
2023-09-25T23:14:56+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
25755cd80eedc0a8cc1aa147d820faf4a1b5a04b
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/imdb](https://huggingface.co/datasets/imdb)
Lilac dataset config:
```namespace: lilac
name: imdb
source:
dataset_name: imdb
source_name: huggingface
embeddings:
- path: text
embedding: gte-small
signals:
- path: text
signal:
signal_name: near_dup
- path: text
signal:
signal_name: pii
- path: text
signal:
signal_name: lang_detection
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
signal_name: text_statistics
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
signal_name: cluster_dbscan
- path: text
signal:
embedding: gte-small
signal_name: cluster_hdbscan
settings:
ui:
media_paths:
- text
markdown_paths: []
tags:
- machine-learning
```
|
lilacai/lilac-imdb
|
[
"region:us"
] |
2023-08-21T03:47:16+00:00
|
{}
|
2023-12-07T13:57:29+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
dc983e91ca2fd7504f5360d05f29ef9845895c62
|
# Dataset of seaport_hime/港湾棲姫 (Kantai Collection)
This is the dataset of seaport_hime/港湾棲姫 (Kantai Collection), containing 426 images and their tags.
The core tags of this character are `long_hair, horns, white_hair, single_horn, breasts, red_eyes, pale_skin, large_breasts, very_long_hair, colored_skin, white_skin`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 426 | 428.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/seaport_hime_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 426 | 291.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/seaport_hime_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 899 | 544.40 MiB | [Download](https://huggingface.co/datasets/CyberHarem/seaport_hime_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 426 | 399.54 MiB | [Download](https://huggingface.co/datasets/CyberHarem/seaport_hime_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 899 | 696.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/seaport_hime_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/seaport_hime_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 7 |  |  |  |  |  | 1girl, abyssal_ship, claws, detached_sleeves, looking_at_viewer, ribbed_dress, solo, bare_shoulders, short_dress, sweater_dress, sideboob |
| 1 | 11 |  |  |  |  |  | 1girl, abyssal_ship, bare_shoulders, claws, detached_sleeves, looking_at_viewer, ribbed_dress, short_dress, sideboob, solo, sweater_dress, covered_nipples, ribbed_sweater |
| 2 | 9 |  |  |  |  |  | 1girl, abyssal_ship, claws, detached_sleeves, ribbed_dress, short_dress, solo, bare_shoulders, looking_at_viewer, sideboob, white_footwear, knee_boots, sweater, sitting |
| 3 | 8 |  |  |  |  |  | 1girl, abyssal_ship, claws, detached_sleeves, glowing_eyes, ribbed_dress, sideboob, solo, bare_shoulders, looking_at_viewer, short_dress, covered_nipples |
| 4 | 6 |  |  |  |  |  | 2girls, abyssal_ship, claws, detached_sleeves, mittens, ribbed_dress, short_dress, white_dress, ahoge, orange_eyes |
| 5 | 6 |  |  |  |  |  | 1boy, abyssal_ship, blush, detached_sleeves, hetero, ribbed_dress, 1girl, breast_grab, covered_nipples, grabbing, solo_focus, bare_shoulders, claws |
| 6 | 8 |  |  |  |  |  | abyssal_ship, cleavage_cutout, open-chest_sweater, ribbed_sweater, 1girl, solo, blush, turtleneck, alternate_costume, looking_at_viewer |
| 7 | 8 |  |  |  |  |  | 1girl, abyssal_ship, blush, navel, solo, cleavage, huge_breasts, collarbone, looking_at_viewer, blue_bra, blue_panties, pink_eyes, simple_background, blue_thighhighs, detached_sleeves, plump, underwear_only, white_background |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | abyssal_ship | claws | detached_sleeves | looking_at_viewer | ribbed_dress | solo | bare_shoulders | short_dress | sweater_dress | sideboob | covered_nipples | ribbed_sweater | white_footwear | knee_boots | sweater | sitting | glowing_eyes | 2girls | mittens | white_dress | ahoge | orange_eyes | 1boy | blush | hetero | breast_grab | grabbing | solo_focus | cleavage_cutout | open-chest_sweater | turtleneck | alternate_costume | navel | cleavage | huge_breasts | collarbone | blue_bra | blue_panties | pink_eyes | simple_background | blue_thighhighs | plump | underwear_only | white_background |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:--------|:-------------------|:--------------------|:---------------|:-------|:-----------------|:--------------|:----------------|:-----------|:------------------|:-----------------|:-----------------|:-------------|:----------|:----------|:---------------|:---------|:----------|:--------------|:--------|:--------------|:-------|:--------|:---------|:--------------|:-----------|:-------------|:------------------|:---------------------|:-------------|:--------------------|:--------|:-----------|:---------------|:-------------|:-----------|:---------------|:------------|:--------------------|:------------------|:--------|:-----------------|:-------------------|
| 0 | 7 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 11 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 8 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | | X | X | X | | X | | | X | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | X | X | X | | X | | X | | | | X | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | |
| 6 | 8 |  |  |  |  |  | X | X | | | X | | X | | | | | | X | | | | | | | | | | | | X | | | | | X | X | X | X | | | | | | | | | | | | |
| 7 | 8 |  |  |  |  |  | X | X | | X | X | | X | | | | | | | | | | | | | | | | | | X | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/seaport_hime_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T03:56:11+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T12:48:43+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of seaport\_hime/港湾棲姫 (Kantai Collection)
=================================================
This is the dataset of seaport\_hime/港湾棲姫 (Kantai Collection), containing 426 images and their tags.
The core tags of this character are 'long\_hair, horns, white\_hair, single\_horn, breasts, red\_eyes, pale\_skin, large\_breasts, very\_long\_hair, colored\_skin, white\_skin', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
13a1867e7161e538e871bffd4ea147e02d233be0
|
# lilac/databricks-dolly-15k-curated-en
This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-en](https://huggingface.co/datasets/argilla/databricks-dolly-15k-curated-en)
To download the dataset to a local directory:
```bash
lilac download lilacai/lilac-databricks-dolly-15k-curated-en
```
or from python with:
```py
ll.download("lilacai/lilac-databricks-dolly-15k-curated-en")
```
|
lilacai/lilac-databricks-dolly-15k-curated-en
|
[
"Lilac",
"region:us"
] |
2023-08-21T03:57:51+00:00
|
{"tags": ["Lilac"]}
|
2024-01-24T14:40:18+00:00
|
[] |
[] |
TAGS
#Lilac #region-us
|
# lilac/databricks-dolly-15k-curated-en
This dataset is a Lilac processed dataset. Original dataset: URL
To download the dataset to a local directory:
or from python with:
|
[
"# lilac/databricks-dolly-15k-curated-en\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
"TAGS\n#Lilac #region-us \n",
"# lilac/databricks-dolly-15k-curated-en\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
9,
51
] |
[
"passage: TAGS\n#Lilac #region-us \n# lilac/databricks-dolly-15k-curated-en\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
e7c6ee336c563f647d129c7cfa3ae23984d4729d
|
# lilac/OpenOrca-100k
This dataset is a [Lilac](http://lilacml.com) processed dataset. Original dataset: [https://huggingface.co/datasets/Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)
To download the dataset to a local directory:
```bash
lilac download lilacai/lilac-OpenOrca-100k
```
or from python with:
```py
ll.download("lilacai/lilac-OpenOrca-100k")
```
|
lilacai/lilac-OpenOrca-100k
|
[
"Lilac",
"region:us"
] |
2023-08-21T03:59:09+00:00
|
{"tags": ["Lilac"]}
|
2024-01-17T22:31:57+00:00
|
[] |
[] |
TAGS
#Lilac #region-us
|
# lilac/OpenOrca-100k
This dataset is a Lilac processed dataset. Original dataset: URL
To download the dataset to a local directory:
or from python with:
|
[
"# lilac/OpenOrca-100k\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
"TAGS\n#Lilac #region-us \n",
"# lilac/OpenOrca-100k\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
[
9,
43
] |
[
"passage: TAGS\n#Lilac #region-us \n# lilac/OpenOrca-100k\nThis dataset is a Lilac processed dataset. Original dataset: URL\n\nTo download the dataset to a local directory:\n\n\n\nor from python with:"
] |
b593e06b7907c8d611fb41ffa9194e1fd618211d
|
# Dataset of i_168/伊168/伊168 (Kantai Collection)
This is the dataset of i_168/伊168/伊168 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `ponytail, long_hair, red_hair, red_eyes, hair_ribbon, ribbon, ahoge`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 357.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_168_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 264.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_168_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1021 | 521.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_168_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 339.13 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_168_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1021 | 638.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/i_168_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/i_168_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 10 |  |  |  |  |  | 1girl, one-piece_swimsuit, school_swimsuit, solo, open_mouth, blush, looking_at_viewer, innertube, medium_breasts, torn_swimsuit, name_tag |
| 1 | 6 |  |  |  |  |  | 1girl, looking_at_viewer, one-piece_swimsuit, school_swimsuit, serafuku, solo, swimsuit_under_clothes, blush, innertube, open_mouth, ass |
| 2 | 6 |  |  |  |  |  | 1girl, one-piece_swimsuit, school_swimsuit, serafuku, solo, swimsuit_under_clothes |
| 3 | 6 |  |  |  |  |  | 1girl, one-piece_swimsuit, school_swimsuit, serafuku, smartphone, solo, swimsuit_under_clothes, smile |
| 4 | 8 |  |  |  |  |  | 1girl, fake_animal_ears, playboy_bunny, rabbit_ears, solo, wrist_cuffs, detached_collar, simple_background, strapless_leotard, white_background, black_leotard, looking_at_viewer, alternate_costume, pantyhose, rabbit_tail, blue_leotard, blush, bowtie, cleavage, dated |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | one-piece_swimsuit | school_swimsuit | solo | open_mouth | blush | looking_at_viewer | innertube | medium_breasts | torn_swimsuit | name_tag | serafuku | swimsuit_under_clothes | ass | smartphone | smile | fake_animal_ears | playboy_bunny | rabbit_ears | wrist_cuffs | detached_collar | simple_background | strapless_leotard | white_background | black_leotard | alternate_costume | pantyhose | rabbit_tail | blue_leotard | bowtie | cleavage | dated |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------------|:------------------|:-------|:-------------|:--------|:--------------------|:------------|:-----------------|:----------------|:-----------|:-----------|:-------------------------|:------|:-------------|:--------|:-------------------|:----------------|:--------------|:--------------|:------------------|:--------------------|:--------------------|:-------------------|:----------------|:--------------------|:------------|:--------------|:---------------|:---------|:-----------|:--------|
| 0 | 10 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | | | | X | X | X | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | X | X | X | | | | | | | | X | X | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | X | X | X | | | | | | | | X | X | | X | X | | | | | | | | | | | | | | | | |
| 4 | 8 |  |  |  |  |  | X | | | X | | X | X | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/i_168_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T04:00:09+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T12:21:55+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of i\_168/伊168/伊168 (Kantai Collection)
===============================================
This is the dataset of i\_168/伊168/伊168 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'ponytail, long\_hair, red\_hair, red\_eyes, hair\_ribbon, ribbon, ahoge', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
85e5f78663be0e0deea80d01f8d241f8f228d06e
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/wikitext](https://huggingface.co/datasets/wikitext)
Lilac dataset config:
```namespace: lilac
name: wikitext-2-raw-v1
source:
dataset_name: wikitext
config_name: wikitext-2-raw-v1
source_name: huggingface
embeddings:
- path: text
embedding: gte-small
signals:
- path: text
signal:
signal_name: near_dup
- path: text
signal:
signal_name: pii
- path: text
signal:
signal_name: lang_detection
- path: text
signal:
signal_name: text_statistics
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: legal-termination
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: negative-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: non-english
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: positive-sentiment
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: profanity
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: question
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: source-code
signal_name: concept_score
- path: text
signal:
embedding: gte-small
namespace: lilac
concept_name: toxicity
signal_name: concept_score
- path: text
signal:
signal_name: cluster_dbscan
- path: text
signal:
embedding: gte-small
signal_name: cluster_hdbscan
settings:
ui:
media_paths:
- text
markdown_paths: []
tags:
- machine-learning
```
|
lilacai/lilac-wikitext-2-raw-v1
|
[
"region:us"
] |
2023-08-21T04:15:15+00:00
|
{}
|
2023-12-07T13:57:38+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
1892bc5433424a0f00ffc6556b3162b4edf2de27
|
This dataset is generated by [Lilac](http://lilacml.com) for a HuggingFace Space: [huggingface.co/spaces/lilacai/lilac](https://huggingface.co/spaces/lilacai/lilac).
Original dataset: [https://huggingface.co/datasets/opus100](https://huggingface.co/datasets/opus100)
Lilac dataset config:
```embeddings:
- embedding: gte-small
path: [translation, en]
- embedding: gte-small
path: [translation, es]
name: opus100-en-us-validation
namespace: lilac
settings:
preferred_embedding: gte-small
ui:
media_paths:
- [translation, es]
- [translation, en]
signals:
- path: [translation, es]
signal: {signal_name: near_dup}
- path: [translation, es]
signal: {signal_name: pii}
- path: [translation, es]
signal: {signal_name: lang_detection}
- path: [translation, es]
signal: {signal_name: text_statistics}
- path: [translation, en]
signal: {signal_name: near_dup}
- path: [translation, en]
signal: {signal_name: text_statistics}
- path: [translation, en]
signal: {signal_name: pii}
- path: [translation, en]
signal: {signal_name: lang_detection}
source: {config_name: en-es, dataset_name: opus100, source_name: huggingface, split: validation}
tags: [machine-learning]
```
|
lilacai/lilac-opus100-en-us-validation
|
[
"region:us"
] |
2023-08-21T04:16:43+00:00
|
{}
|
2023-08-21T19:26:10+00:00
|
[] |
[] |
TAGS
#region-us
|
This dataset is generated by Lilac for a HuggingFace Space: URL
Original dataset: URL
Lilac dataset config:
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
980151b8ab752a5700af32dcf1fcdf61a3611374
|
# Dataset Card for "AA_DistilRoBERTa_Final"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
EgilKarlsen/AA_DistilRoBERTa_Final
|
[
"region:us"
] |
2023-08-21T04:18:56+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "0", "dtype": "float32"}, {"name": "1", "dtype": "float32"}, {"name": "2", "dtype": "float32"}, {"name": "3", "dtype": "float32"}, {"name": "4", "dtype": "float32"}, {"name": "5", "dtype": "float32"}, {"name": "6", "dtype": "float32"}, {"name": "7", "dtype": "float32"}, {"name": "8", "dtype": "float32"}, {"name": "9", "dtype": "float32"}, {"name": "10", "dtype": "float32"}, {"name": "11", "dtype": "float32"}, {"name": "12", "dtype": "float32"}, {"name": "13", "dtype": "float32"}, {"name": "14", "dtype": "float32"}, {"name": "15", "dtype": "float32"}, {"name": "16", "dtype": "float32"}, {"name": "17", "dtype": "float32"}, {"name": "18", "dtype": "float32"}, {"name": "19", "dtype": "float32"}, {"name": "20", "dtype": "float32"}, {"name": "21", "dtype": "float32"}, {"name": "22", "dtype": "float32"}, {"name": 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"754", "dtype": "float32"}, {"name": "755", "dtype": "float32"}, {"name": "756", "dtype": "float32"}, {"name": "757", "dtype": "float32"}, {"name": "758", "dtype": "float32"}, {"name": "759", "dtype": "float32"}, {"name": "760", "dtype": "float32"}, {"name": "761", "dtype": "float32"}, {"name": "762", "dtype": "float32"}, {"name": "763", "dtype": "float32"}, {"name": "764", "dtype": "float32"}, {"name": "765", "dtype": "float32"}, {"name": "766", "dtype": "float32"}, {"name": "767", "dtype": "float32"}, {"name": "label", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 80318780.21618997, "num_examples": 26057}, {"name": "test", "num_bytes": 26774087.073587257, "num_examples": 8686}], "download_size": 147167865, "dataset_size": 107092867.28977722}}
|
2023-08-21T04:23:03+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "AA_DistilRoBERTa_Final"
More Information needed
|
[
"# Dataset Card for \"AA_DistilRoBERTa_Final\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"AA_DistilRoBERTa_Final\"\n\nMore Information needed"
] |
[
6,
20
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"AA_DistilRoBERTa_Final\"\n\nMore Information needed"
] |
faaf2a36ad771e18a9c88ef763f993f9dd845fc9
|
# Dataset Card for "tokenized_gpt2_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
yardeny/tokenized_gpt2_dataset
|
[
"region:us"
] |
2023-08-21T04:49:15+00:00
|
{"dataset_info": {"features": [{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}], "splits": [{"name": "train", "num_bytes": 16291456129, "num_examples": 80462898}], "download_size": 7056135272, "dataset_size": 16291456129}}
|
2023-08-21T07:23:11+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "tokenized_gpt2_dataset"
More Information needed
|
[
"# Dataset Card for \"tokenized_gpt2_dataset\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"tokenized_gpt2_dataset\"\n\nMore Information needed"
] |
[
6,
20
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"tokenized_gpt2_dataset\"\n\nMore Information needed"
] |
f9ea8f3a47ce274b5d8a0478e01ef4c1c2a28d49
|
# Dataset Card for "processed_gpt2_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
yardeny/processed_gpt2_context_len_512
|
[
"region:us"
] |
2023-08-21T04:49:19+00:00
|
{"dataset_info": {"features": [{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}], "splits": [{"name": "train", "num_bytes": 15593335128.0, "num_examples": 6072171}], "download_size": 6562663671, "dataset_size": 15593335128.0}}
|
2023-08-21T07:53:12+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "processed_gpt2_dataset"
More Information needed
|
[
"# Dataset Card for \"processed_gpt2_dataset\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"processed_gpt2_dataset\"\n\nMore Information needed"
] |
[
6,
19
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"processed_gpt2_dataset\"\n\nMore Information needed"
] |
e5e6a1785fdb2da0dd07332a0a15bdb3f6ac785f
|
# Dataset of akitsushima/秋津洲/秋津洲 (Kantai Collection)
This is the dataset of akitsushima/秋津洲/秋津洲 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, side_ponytail, purple_eyes, ahoge, hat, grey_hair, breasts, sidelocks, hair_ornament, purple_hair, ribbon, earrings, hair_ribbon, mini_hat`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 485.04 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsushima_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 317.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsushima_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1152 | 660.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsushima_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 444.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsushima_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1152 | 855.69 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsushima_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/akitsushima_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 9 |  |  |  |  |  | 1girl, skirt, solo, looking_at_viewer, simple_background, alternate_costume, green_headwear, open_mouth, smile, white_background, jewelry, beret, black_shirt, belt, blush, jacket |
| 1 | 7 |  |  |  |  |  | 1girl, looking_at_viewer, military_uniform, miniskirt, solo, white_gloves, jewelry, pleated_skirt, simple_background, white_background, anchor, blush, thighhighs, medium_breasts, open_mouth, sideboob, torn_clothes |
| 2 | 6 |  |  |  |  |  | 1girl, military_uniform, miniskirt, open_mouth, solo, thighhighs, white_background, green_skirt, jewelry, pleated_skirt, simple_background, white_gloves, smile, airplane, armpit_cutout, jacket, looking_at_viewer |
| 3 | 7 |  |  |  |  |  | 1girl, gloves, miniskirt, open_mouth, solo, blush, jewelry, looking_at_viewer, smile, thighhighs, anchor, zettai_ryouiki, airplane, military_uniform |
| 4 | 7 |  |  |  |  |  | 1girl, airplane, military_uniform, open_mouth, solo, jewelry, miniskirt, pleated_skirt, thighhighs, anchor, smile, zettai_ryouiki, armpit_cutout, looking_at_viewer, white_gloves |
| 5 | 10 |  |  |  |  |  | 1girl, jacket, looking_at_viewer, solo, upper_body, jewelry, military_uniform, armpit_cutout, simple_background, long_sleeves, smile, white_background, open_mouth, white_gloves, bangs |
| 6 | 31 |  |  |  |  |  | 1girl, solo, white_bikini, polka_dot, smile, open_mouth, looking_at_viewer, navel, blush, collarbone, simple_background, eyewear_on_head, single_hair_bun, white_background |
| 7 | 5 |  |  |  |  |  | 1girl, fake_animal_ears, playboy_bunny, rabbit_ears, rabbit_tail, solo, adapted_costume, cleavage, detached_collar, looking_at_viewer, simple_background, white_gloves, blush, bowtie, dated, large_breasts, open_mouth, smile, thighhighs, twitter_username, white_background, wrist_cuffs, black_pantyhose, full_body, medium_breasts, strapless_leotard |
| 8 | 6 |  |  |  |  |  | 1girl, long_sleeves, obi, solo, wide_sleeves, blush, green_kimono, open_mouth, single_hair_bun, smile, full_body, holding, jewelry, jingle_bell, looking_at_viewer, looking_back |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | skirt | solo | looking_at_viewer | simple_background | alternate_costume | green_headwear | open_mouth | smile | white_background | jewelry | beret | black_shirt | belt | blush | jacket | military_uniform | miniskirt | white_gloves | pleated_skirt | anchor | thighhighs | medium_breasts | sideboob | torn_clothes | green_skirt | airplane | armpit_cutout | gloves | zettai_ryouiki | upper_body | long_sleeves | bangs | white_bikini | polka_dot | navel | collarbone | eyewear_on_head | single_hair_bun | fake_animal_ears | playboy_bunny | rabbit_ears | rabbit_tail | adapted_costume | cleavage | detached_collar | bowtie | dated | large_breasts | twitter_username | wrist_cuffs | black_pantyhose | full_body | strapless_leotard | obi | wide_sleeves | green_kimono | holding | jingle_bell | looking_back |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------|:-------|:--------------------|:--------------------|:--------------------|:-----------------|:-------------|:--------|:-------------------|:----------|:--------|:--------------|:-------|:--------|:---------|:-------------------|:------------|:---------------|:----------------|:---------|:-------------|:-----------------|:-----------|:---------------|:--------------|:-----------|:----------------|:---------|:-----------------|:-------------|:---------------|:--------|:---------------|:------------|:--------|:-------------|:------------------|:------------------|:-------------------|:----------------|:--------------|:--------------|:------------------|:-----------|:------------------|:---------|:--------|:----------------|:-------------------|:--------------|:------------------|:------------|:--------------------|:------|:---------------|:---------------|:----------|:--------------|:---------------|
| 0 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 7 |  |  |  |  |  | X | | X | X | X | | | X | | X | X | | | | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | | X | X | X | | | X | X | X | X | | | | | X | X | X | X | X | | X | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 7 |  |  |  |  |  | X | | X | X | | | | X | X | | X | | | | X | | X | X | | | X | X | | | | | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 7 |  |  |  |  |  | X | | X | X | | | | X | X | | X | | | | | | X | X | X | X | X | X | | | | | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 10 |  |  |  |  |  | X | | X | X | X | | | X | X | X | X | | | | | X | X | | X | | | | | | | | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 31 |  |  |  |  |  | X | | X | X | X | | | X | X | X | | | | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 7 | 5 |  |  |  |  |  | X | | X | X | X | | | X | X | X | | | | | X | | | | X | | | X | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | |
| 8 | 6 |  |  |  |  |  | X | | X | X | | | | X | X | | X | | | | X | | | | | | | | | | | | | | | | | X | | | | | | | X | | | | | | | | | | | | | | X | | X | X | X | X | X | X |
|
CyberHarem/akitsushima_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T04:54:30+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T20:04:06+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of akitsushima/秋津洲/秋津洲 (Kantai Collection)
==================================================
This is the dataset of akitsushima/秋津洲/秋津洲 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, side\_ponytail, purple\_eyes, ahoge, hat, grey\_hair, breasts, sidelocks, hair\_ornament, purple\_hair, ribbon, earrings, hair\_ribbon, mini\_hat', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
e26deee34f6c9823cdb432bb92cd103dddca221a
|
# Dataset of kawakaze/江風 (Kantai Collection)
This is the dataset of kawakaze/江風 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, red_hair, hairband, ahoge, ribbon, hair_ribbon, twintails, bangs, very_long_hair, low_twintails, sidelocks, asymmetrical_bangs, blue_eyes, braid, twin_braids, yellow_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:---------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 465.81 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kawakaze_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 315.37 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kawakaze_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1144 | 651.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kawakaze_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 432.84 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kawakaze_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1144 | 829.83 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kawakaze_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kawakaze_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 17 |  |  |  |  |  | 1girl, black_gloves, black_skirt, elbow_gloves, fingerless_gloves, looking_at_viewer, neckerchief, pleated_skirt, serafuku, sleeveless_shirt, solo, belt, smile, navel, blush, collared_shirt, simple_background, white_background, bare_shoulders, black_thighhighs, open_mouth |
| 1 | 6 |  |  |  |  |  | 1girl, black_gloves, black_serafuku, black_skirt, collared_shirt, elbow_gloves, navel, one-hour_drawing_challenge, pleated_skirt, simple_background, sleeveless_shirt, solo, white_background, blue_neckerchief, fingerless_gloves, twitter_username, black_thighhighs, cowboy_shot, looking_at_viewer, white_belt, dated, smile |
| 2 | 14 |  |  |  |  |  | 1girl, looking_at_viewer, serafuku, sleeveless_shirt, solo, collared_shirt, elbow_gloves, upper_body, black_gloves, blue_neckerchief, bare_shoulders, fingerless_gloves, blush, navel, simple_background, grin |
| 3 | 15 |  |  |  |  |  | 1girl, black_gloves, fingerless_gloves, hair_flaps, scarf, serafuku, solo, looking_at_viewer, smile, cape, elbow_gloves, neckerchief, open_mouth, torpedo, black_skirt, machinery, pleated_skirt, turret |
| 4 | 6 |  |  |  |  |  | 1girl, cape, hair_flaps, serafuku, solo, chibi, fang, open_mouth, white_scarf, :d, ^_^, neckerchief, pleated_skirt, thighhighs, elbow_gloves, fingerless_gloves |
| 5 | 12 |  |  |  |  |  | 1girl, hair_flaps, solo, alternate_costume, employee_uniform, looking_at_viewer, pleated_skirt, black_skirt, smile, vertical-striped_shirt, cowboy_shot, open_mouth, name_tag, red_ribbon, simple_background |
| 6 | 5 |  |  |  |  |  | 1girl, alternate_costume, looking_at_viewer, simple_background, solo, blush, cowboy_shot, long_sleeves, twitter_username, white_background, hand_on_hip, one-hour_drawing_challenge, pleated_skirt, red_ribbon, school_uniform, smile, white_shirt, bowtie, closed_mouth, collared_shirt, cropped_legs, lips, pointy_ears |
| 7 | 18 |  |  |  |  |  | 1girl, solo, looking_at_viewer, adapted_costume, sailor_bikini, smile, black_bikini, simple_background, blush, white_background, navel, small_breasts, hair_flaps, medium_breasts |
| 8 | 10 |  |  |  |  |  | 1girl, looking_at_viewer, solo, white_background, alternate_costume, simple_background, artist_logo, blush, cowboy_shot, dated, dress, collarbone, grin, pointy_ears |
| 9 | 12 |  |  |  |  |  | 1girl, yukata, solo, alternate_costume, looking_at_viewer, floral_print, obi, smile, blush, candy_apple, fox_mask, mask_on_head, open_mouth |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_gloves | black_skirt | elbow_gloves | fingerless_gloves | looking_at_viewer | neckerchief | pleated_skirt | serafuku | sleeveless_shirt | solo | belt | smile | navel | blush | collared_shirt | simple_background | white_background | bare_shoulders | black_thighhighs | open_mouth | black_serafuku | one-hour_drawing_challenge | blue_neckerchief | twitter_username | cowboy_shot | white_belt | dated | upper_body | grin | hair_flaps | scarf | cape | torpedo | machinery | turret | chibi | fang | white_scarf | :d | ^_^ | thighhighs | alternate_costume | employee_uniform | vertical-striped_shirt | name_tag | red_ribbon | long_sleeves | hand_on_hip | school_uniform | white_shirt | bowtie | closed_mouth | cropped_legs | lips | pointy_ears | adapted_costume | sailor_bikini | black_bikini | small_breasts | medium_breasts | artist_logo | dress | collarbone | yukata | floral_print | obi | candy_apple | fox_mask | mask_on_head |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:--------------|:---------------|:--------------------|:--------------------|:--------------|:----------------|:-----------|:-------------------|:-------|:-------|:--------|:--------|:--------|:-----------------|:--------------------|:-------------------|:-----------------|:-------------------|:-------------|:-----------------|:-----------------------------|:-------------------|:-------------------|:--------------|:-------------|:--------|:-------------|:-------|:-------------|:--------|:-------|:----------|:------------|:---------|:--------|:-------|:--------------|:-----|:------|:-------------|:--------------------|:-------------------|:-------------------------|:-----------|:-------------|:---------------|:--------------|:-----------------|:--------------|:---------|:---------------|:---------------|:-------|:--------------|:------------------|:----------------|:---------------|:----------------|:-----------------|:--------------|:--------|:-------------|:---------|:---------------|:------|:--------------|:-----------|:---------------|
| 0 | 17 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | X | X | X | X | | X | | X | X | | X | X | | X | X | X | | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 14 |  |  |  |  |  | X | X | | X | X | X | | | X | X | X | | | X | X | X | X | | X | | | | | X | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 15 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | | X | | X | | | | | | | | X | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | | | X | X | | X | X | X | | X | | | | | | | | | | X | | | | | | | | | | X | | X | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 12 |  |  |  |  |  | X | | X | | | X | | X | | | X | | X | | | | X | | | | X | | | | | X | | | | | X | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | | | | | X | | X | | | X | | X | | X | X | X | X | | | | | X | | X | X | | | | | | | | | | | | | | | | | X | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | |
| 7 | 18 |  |  |  |  |  | X | | | | | X | | | | | X | | X | X | X | | X | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | |
| 8 | 10 |  |  |  |  |  | X | | | | | X | | | | | X | | | | X | | X | X | | | | | | | | X | | X | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | X | X | X | | | | | | |
| 9 | 12 |  |  |  |  |  | X | | | | | X | | | | | X | | X | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X |
|
CyberHarem/kawakaze_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T05:09:20+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T10:23:55+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kawakaze/江風 (Kantai Collection)
==========================================
This is the dataset of kawakaze/江風 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, red\_hair, hairband, ahoge, ribbon, hair\_ribbon, twintails, bangs, very\_long\_hair, low\_twintails, sidelocks, asymmetrical\_bangs, blue\_eyes, braid, twin\_braids, yellow\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
63c1916b4db3380185cf476432b6c465cc123058
|
# Dataset Card for "merge_new_para_detection_data_v5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
mHossain/merge_new_para_detection_data_v5
|
[
"region:us"
] |
2023-08-21T05:33:01+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "Unnamed: 0", "dtype": "int64"}, {"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 8837101.8, "num_examples": 50400}, {"name": "test", "num_bytes": 981900.2, "num_examples": 5600}], "download_size": 4451360, "dataset_size": 9819002.0}}
|
2023-08-21T05:33:05+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "merge_new_para_detection_data_v5"
More Information needed
|
[
"# Dataset Card for \"merge_new_para_detection_data_v5\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"merge_new_para_detection_data_v5\"\n\nMore Information needed"
] |
[
6,
24
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"merge_new_para_detection_data_v5\"\n\nMore Information needed"
] |
6d57d5c37af47b0d5c5d6acfbb0258138a461725
|
# Dataset of isuzu/五十鈴 (Kantai Collection)
This is the dataset of isuzu/五十鈴 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `long_hair, twintails, breasts, ribbon, large_breasts, hair_ribbon, blue_hair, blue_eyes, green_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 491.75 MiB | [Download](https://huggingface.co/datasets/CyberHarem/isuzu_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 328.85 MiB | [Download](https://huggingface.co/datasets/CyberHarem/isuzu_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1199 | 703.02 MiB | [Download](https://huggingface.co/datasets/CyberHarem/isuzu_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 455.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/isuzu_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1199 | 910.21 MiB | [Download](https://huggingface.co/datasets/CyberHarem/isuzu_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/isuzu_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 31 |  |  |  |  |  | 1girl, serafuku, solo, detached_sleeves, pleated_skirt, red_skirt, white_sailor_collar, looking_at_viewer, simple_background, white_thighhighs, brown_neckerchief, white_background, sleeveless, smile, cowboy_shot |
| 1 | 6 |  |  |  |  |  | 1girl, cleavage, looking_at_viewer, solo, underwear_only, black_bra, black_panties, navel, smile, blush |
| 2 | 10 |  |  |  |  |  | 1girl, looking_at_viewer, simple_background, solo, white_background, blue_bikini, floral_print, blush, cleavage, navel, collarbone, hair_between_eyes, sarong, smile, aqua_eyes, open_mouth |
| 3 | 6 |  |  |  |  |  | 1girl, blue_bikini, floral_print, navel, sarong, smile, solo, black_hair, looking_at_viewer, cowboy_shot |
| 4 | 14 |  |  |  |  |  | 1girl, day, solo, blue_bikini, looking_at_viewer, smile, ocean, beach, collarbone, outdoors, cloud, floral_print, sarong, cleavage, blue_sky, blush, navel, black_hair, green_hair, cowboy_shot, open_mouth, water |
| 5 | 6 |  |  |  |  |  | 1girl, blush, looking_at_viewer, solo, covered_navel, cowboy_shot, school_swimsuit, simple_background, white_background, blue_one-piece_swimsuit, collarbone, dated, name_tag, twitter_username |
| 6 | 8 |  |  |  |  |  | 1girl, enmaided, looking_at_viewer, solo, white_apron, cleavage, frilled_apron, simple_background, waist_apron, white_background, black_dress, maid_headdress, blush, white_thighhighs, hair_between_eyes, open_mouth, short_sleeves, wrist_cuffs, bangs, dated, sweat |
| 7 | 5 |  |  |  |  |  | 1boy, 1girl, blush, cum_on_breasts, facial, hetero, nipples, open_mouth, penis, solo_focus, looking_at_viewer, mosaic_censoring, paizuri, black_hair, one_eye_closed, cum_on_tongue, detached_sleeves, huge_breasts, pov |
| 8 | 5 |  |  |  |  |  | 1boy, 1girl, blush, hetero, nipples, nude, open_mouth, solo_focus, sweat, girl_on_top, hairband, navel, penis, sex_from_behind, tears, vaginal, bar_censor, green_hair, reverse_cowgirl_position, bangs, collarbone, cum_in_pussy, motion_lines, trembling |
| 9 | 14 |  |  |  |  |  | 1girl, playboy_bunny, rabbit_ears, solo, detached_collar, fake_animal_ears, looking_at_viewer, cleavage, wrist_cuffs, simple_background, strapless_leotard, cowboy_shot, white_background, bowtie, pantyhose, alternate_costume, blush, rabbit_tail, highleg, blue_leotard, covered_navel, white_gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | serafuku | solo | detached_sleeves | pleated_skirt | red_skirt | white_sailor_collar | looking_at_viewer | simple_background | white_thighhighs | brown_neckerchief | white_background | sleeveless | smile | cowboy_shot | cleavage | underwear_only | black_bra | black_panties | navel | blush | blue_bikini | floral_print | collarbone | hair_between_eyes | sarong | aqua_eyes | open_mouth | black_hair | day | ocean | beach | outdoors | cloud | blue_sky | green_hair | water | covered_navel | school_swimsuit | blue_one-piece_swimsuit | dated | name_tag | twitter_username | enmaided | white_apron | frilled_apron | waist_apron | black_dress | maid_headdress | short_sleeves | wrist_cuffs | bangs | sweat | 1boy | cum_on_breasts | facial | hetero | nipples | penis | solo_focus | mosaic_censoring | paizuri | one_eye_closed | cum_on_tongue | huge_breasts | pov | nude | girl_on_top | hairband | sex_from_behind | tears | vaginal | bar_censor | reverse_cowgirl_position | cum_in_pussy | motion_lines | trembling | playboy_bunny | rabbit_ears | detached_collar | fake_animal_ears | strapless_leotard | bowtie | pantyhose | alternate_costume | rabbit_tail | highleg | blue_leotard | white_gloves |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------|:-------|:-------------------|:----------------|:------------|:----------------------|:--------------------|:--------------------|:-------------------|:--------------------|:-------------------|:-------------|:--------|:--------------|:-----------|:-----------------|:------------|:----------------|:--------|:--------|:--------------|:---------------|:-------------|:--------------------|:---------|:------------|:-------------|:-------------|:------|:--------|:--------|:-----------|:--------|:-----------|:-------------|:--------|:----------------|:------------------|:--------------------------|:--------|:-----------|:-------------------|:-----------|:--------------|:----------------|:--------------|:--------------|:-----------------|:----------------|:--------------|:--------|:--------|:-------|:-----------------|:---------|:---------|:----------|:--------|:-------------|:-------------------|:----------|:-----------------|:----------------|:---------------|:------|:-------|:--------------|:-----------|:------------------|:--------|:----------|:-------------|:---------------------------|:---------------|:---------------|:------------|:----------------|:--------------|:------------------|:-------------------|:--------------------|:---------|:------------|:--------------------|:--------------|:----------|:---------------|:---------------|
| 0 | 31 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | | X | | | | | X | | | | | | X | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 10 |  |  |  |  |  | X | | X | | | | | X | X | | | X | | X | | X | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | | X | | | | | X | | | | | | X | X | | | | | X | | X | X | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 14 |  |  |  |  |  | X | | X | | | | | X | | | | | | X | X | X | | | | X | X | X | X | X | | X | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | | X | | | | | X | X | | | X | | | X | | | | | | X | | | X | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 8 |  |  |  |  |  | X | | X | | | | | X | X | X | | X | | | | X | | | | | X | | | | X | | | X | | | | | | | | | | | | | X | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 5 |  |  |  |  |  | X | | | X | | | | X | | | | | | | | | | | | | X | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 5 |  |  |  |  |  | X | | | | | | | | | | | | | | | | | | | X | X | | | X | | | | X | | | | | | | | X | | | | | | | | | | | | | | | | X | X | X | | | X | X | X | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 9 | 14 |  |  |  |  |  | X | | X | | | | | X | X | | | X | | | X | X | | | | | X | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/isuzu_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T05:51:30+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T12:17:58+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of isuzu/五十鈴 (Kantai Collection)
========================================
This is the dataset of isuzu/五十鈴 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'long\_hair, twintails, breasts, ribbon, large\_breasts, hair\_ribbon, blue\_hair, blue\_eyes, green\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
06fd293c94c93d4489cc8730487460f66c4de9ed
|
# Dataset of aoba/青葉 (Kantai Collection)
This is the dataset of aoba/青葉 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `ponytail, scrunchie, blue_eyes, purple_hair, blue_scrunchie, pink_hair, messy_hair, short_hair, breasts, hair_scrunchie`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:-----------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 457.85 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aoba_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 295.14 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aoba_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1175 | 634.55 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aoba_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 417.90 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aoba_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1175 | 834.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/aoba_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/aoba_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, black_thighhighs, sailor_collar, serafuku, short_sleeves, solo, yellow_neckerchief, looking_at_viewer, shorts, simple_background, smile, white_background, ahoge, shirt, large_breasts |
| 1 | 36 |  |  |  |  |  | 1girl, serafuku, solo, simple_background, yellow_neckerchief, looking_at_viewer, upper_body, white_background, smile, purple_sailor_collar, short_sleeves, hair_ornament |
| 2 | 7 |  |  |  |  |  | 1girl, alternate_costume, full_body, looking_at_viewer, simple_background, sneakers, solo, standing, white_background, medium_breasts, black_shorts, grey_background, open_mouth, smile, t-shirt, white_shirt |
| 3 | 5 |  |  |  |  |  | 1girl, looking_at_viewer, simple_background, solo, white_background, blush, collarbone, blue_bikini, cleavage, hair_between_eyes, hair_ornament, large_breasts, medium_breasts, open_mouth, twitter_username, ahoge, front-tie_bikini_top, one-hour_drawing_challenge, side-tie_bikini_bottom, upper_body |
| 4 | 9 |  |  |  |  |  | 1girl, looking_at_viewer, blue_sky, day, outdoors, solo, medium_breasts, ocean, cleavage, cloud, beach, blue_bikini, large_breasts, navel, smile |
| 5 | 9 |  |  |  |  |  | fake_animal_ears, playboy_bunny, rabbit_ears, 1girl, black_leotard, rabbit_tail, solo, strapless_leotard, alternate_costume, detached_collar, fake_tail, looking_at_viewer, black_pantyhose, medium_breasts, black_bowtie, cleavage, cowboy_shot, large_breasts, simple_background, wrist_cuffs |
| 6 | 6 |  |  |  |  |  | 1girl, smile, solo, alternate_costume, floral_print, looking_at_viewer, hair_ornament, obi, upper_body, blue_kimono, new_year |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | black_thighhighs | sailor_collar | serafuku | short_sleeves | solo | yellow_neckerchief | looking_at_viewer | shorts | simple_background | smile | white_background | ahoge | shirt | large_breasts | upper_body | purple_sailor_collar | hair_ornament | alternate_costume | full_body | sneakers | standing | medium_breasts | black_shorts | grey_background | open_mouth | t-shirt | white_shirt | blush | collarbone | blue_bikini | cleavage | hair_between_eyes | twitter_username | front-tie_bikini_top | one-hour_drawing_challenge | side-tie_bikini_bottom | blue_sky | day | outdoors | ocean | cloud | beach | navel | fake_animal_ears | playboy_bunny | rabbit_ears | black_leotard | rabbit_tail | strapless_leotard | detached_collar | fake_tail | black_pantyhose | black_bowtie | cowboy_shot | wrist_cuffs | floral_print | obi | blue_kimono | new_year |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------------|:----------------|:-----------|:----------------|:-------|:---------------------|:--------------------|:---------|:--------------------|:--------|:-------------------|:--------|:--------|:----------------|:-------------|:-----------------------|:----------------|:--------------------|:------------|:-----------|:-----------|:-----------------|:---------------|:------------------|:-------------|:----------|:--------------|:--------|:-------------|:--------------|:-----------|:--------------------|:-------------------|:-----------------------|:-----------------------------|:-------------------------|:-----------|:------|:-----------|:--------|:--------|:--------|:--------|:-------------------|:----------------|:--------------|:----------------|:--------------|:--------------------|:------------------|:------------|:------------------|:---------------|:--------------|:--------------|:---------------|:------|:--------------|:-----------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 36 |  |  |  |  |  | X | | | X | X | X | X | X | | X | X | X | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | | | | | X | | X | | X | X | X | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | | | | | X | | X | | X | | X | X | | X | X | | X | | | | | X | | | X | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 9 |  |  |  |  |  | X | | | | | X | | X | | | X | | | | X | | | | | | | | X | | | | | | | | X | X | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | |
| 5 | 9 |  |  |  |  |  | X | | | | | X | | X | | X | | | | | X | | | | X | | | | X | | | | | | | | | X | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | |
| 6 | 6 |  |  |  |  |  | X | | | | | X | | X | | | X | | | | | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X |
|
CyberHarem/aoba_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T06:01:10+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T01:37:47+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of aoba/青葉 (Kantai Collection)
======================================
This is the dataset of aoba/青葉 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'ponytail, scrunchie, blue\_eyes, purple\_hair, blue\_scrunchie, pink\_hair, messy\_hair, short\_hair, breasts, hair\_scrunchie', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
d637eaccc6992ccd4ec76daec3e73bf529c9144a
|
# Dataset Card for "cleaned_elderly_CV"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
StofEzz/cleaned_elderly_CV
|
[
"region:us"
] |
2023-08-21T06:02:30+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "path", "dtype": "string"}, {"name": "audio", "dtype": {"audio": {"sampling_rate": 48000}}}, {"name": "sentence", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 882678219.0, "num_examples": 21000}, {"name": "test", "num_bytes": 8944629.0, "num_examples": 211}], "download_size": 877792381, "dataset_size": 891622848.0}}
|
2023-08-21T06:03:23+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "cleaned_elderly_CV"
More Information needed
|
[
"# Dataset Card for \"cleaned_elderly_CV\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"cleaned_elderly_CV\"\n\nMore Information needed"
] |
[
6,
19
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"cleaned_elderly_CV\"\n\nMore Information needed"
] |
0d992c6c64647ac83be326b621f298cd1ab9d955
|
This is a Single label emotion classification dataset based on go emotion parameters.
This dataset was labeled by a team of 12 engineers (custom marked label).
This dataset also shows the evaluation result for 3 models viz. Roberta, Bert Cased, and Bert Uncased on this dataset.
|
Ajitava/go_emotions_single_label
|
[
"license:mit",
"region:us"
] |
2023-08-21T06:04:57+00:00
|
{"license": "mit"}
|
2023-08-21T06:23:45+00:00
|
[] |
[] |
TAGS
#license-mit #region-us
|
This is a Single label emotion classification dataset based on go emotion parameters.
This dataset was labeled by a team of 12 engineers (custom marked label).
This dataset also shows the evaluation result for 3 models viz. Roberta, Bert Cased, and Bert Uncased on this dataset.
|
[] |
[
"TAGS\n#license-mit #region-us \n"
] |
[
11
] |
[
"passage: TAGS\n#license-mit #region-us \n"
] |
e30d994e928597e4d48500ddf6e674a7997fa670
|
This is a dataset for multilabel emotion classification based on go emotion parameters.
This dataset was labeled by a team of 12 engineers (custom marked label).
This dataset also shows the evaluation result for 3 models viz. Roberta, Bert Cased, and Bert Uncased on this dataset.
|
Ajitava/go_emotions_multi_label
|
[
"license:mit",
"region:us"
] |
2023-08-21T06:07:26+00:00
|
{"license": "mit"}
|
2023-08-21T06:22:49+00:00
|
[] |
[] |
TAGS
#license-mit #region-us
|
This is a dataset for multilabel emotion classification based on go emotion parameters.
This dataset was labeled by a team of 12 engineers (custom marked label).
This dataset also shows the evaluation result for 3 models viz. Roberta, Bert Cased, and Bert Uncased on this dataset.
|
[] |
[
"TAGS\n#license-mit #region-us \n"
] |
[
11
] |
[
"passage: TAGS\n#license-mit #region-us \n"
] |
46d5d146eec8dc8b951035c4093d69288c97a9bc
|
<head><link rel="stylesheet" href="https://huggingface.co/front/build/kube-91c9610/style.css"></head>
<div class="container mt-4"><div class="prose"><p>Edit this <code>README.md</code> markdown file to author your organization card 🔥</p>
</div></div>
|
e-mohammadii/fanap-test
|
[
"region:us"
] |
2023-08-21T06:36:32+00:00
|
{}
|
2023-08-21T07:46:12+00:00
|
[] |
[] |
TAGS
#region-us
|
<head><link rel="stylesheet" href="URL
<div class="container mt-4"><div class="prose"><p>Edit this <code>URL</code> markdown file to author your organization card </p>
</div></div>
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
3ec02957c794867a7295d6a0ed62aee7c8111d77
|
# Dataset Card for "pretrain_zh"
[Tigerbot](https://github.com/TigerResearch/TigerBot) pretrain数据的中文部分。
包含(未压缩前) 中文书籍zh-books 12G, 中文互联网zh-webtext 25G, 中文百科zh-wiki 19G
更多语料请关注开源模型及持续更新 [https://github.com/TigerResearch/TigerBot](https://github.com/TigerResearch/TigerBot)
<p align="center" width="40%">
</p>
## Usage
```python
import datasets
ds_sft = datasets.load_dataset('TigerResearch/pretrain_zh')
```
|
botp/TigerResearch-pretrain_zh
|
[
"region:us"
] |
2023-08-21T06:39:09+00:00
|
{"dataset_info": {"features": [{"name": "dataType", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "uniqueKey", "dtype": "string"}, {"name": "titleUkey", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 58043923125, "num_examples": 16905023}], "download_size": 25662051889, "dataset_size": 58043923125}, "duplicated_from": "TigerResearch/pretrain_zh"}
|
2023-08-21T06:39:09+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "pretrain_zh"
Tigerbot pretrain数据的中文部分。
包含(未压缩前) 中文书籍zh-books 12G, 中文互联网zh-webtext 25G, 中文百科zh-wiki 19G
更多语料请关注开源模型及持续更新 URL
<p align="center" width="40%">
</p>
## Usage
|
[
"# Dataset Card for \"pretrain_zh\"\n\nTigerbot pretrain数据的中文部分。\n\n包含(未压缩前) 中文书籍zh-books 12G, 中文互联网zh-webtext 25G, 中文百科zh-wiki 19G\n\n更多语料请关注开源模型及持续更新 URL \n\n<p align=\"center\" width=\"40%\">\n</p>",
"## Usage"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"pretrain_zh\"\n\nTigerbot pretrain数据的中文部分。\n\n包含(未压缩前) 中文书籍zh-books 12G, 中文互联网zh-webtext 25G, 中文百科zh-wiki 19G\n\n更多语料请关注开源模型及持续更新 URL \n\n<p align=\"center\" width=\"40%\">\n</p>",
"## Usage"
] |
[
6,
83,
3
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"pretrain_zh\"\n\nTigerbot pretrain数据的中文部分。\n\n包含(未压缩前) 中文书籍zh-books 12G, 中文互联网zh-webtext 25G, 中文百科zh-wiki 19G\n\n更多语料请关注开源模型及持续更新 URL \n\n<p align=\"center\" width=\"40%\">\n</p>## Usage"
] |
17be7f178bcac605d52fb2668fa21d4dff7f6b26
|
# 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]
|
chanelcolgate/tumorsbrain
|
[
"region:us"
] |
2023-08-21T06:41:46+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "image_id", "dtype": "int64"}, {"name": "objects", "sequence": [{"name": "id", "dtype": "int64"}, {"name": "area", "dtype": "float64"}, {"name": "bbox", "sequence": "float32", "length": 4}, {"name": "label", "dtype": {"class_label": {"names": {"0": "negative", "1": "positive"}}}}, {"name": "iscrowd", "dtype": "bool"}]}], "splits": [{"name": "train", "num_bytes": 11482275, "num_examples": 893}, {"name": "test", "num_bytes": 2794404, "num_examples": 223}], "download_size": 12628405, "dataset_size": 14276679}}
|
2023-08-21T06:48:23+00:00
|
[] |
[] |
TAGS
#region-us
|
# 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.
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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 Card for Dataset Name",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
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"### Discussion of Biases",
"### Other Known Limitations",
"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] |
[
"TAGS\n#region-us \n",
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"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
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"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
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"### Data Splits",
"## Dataset Creation",
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"### Social Impact of Dataset",
"### Discussion of Biases",
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8,
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10,
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] |
[
"passage: TAGS\n#region-us \n# Dataset Card for Dataset Name## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
b622f7ae39bec0f406e05bb9b58f2983014139c1
|
# Dataset of agano/阿賀野 (Kantai Collection)
This is the dataset of agano/阿賀野 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `black_hair, long_hair, breasts, large_breasts, green_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 480.21 MiB | [Download](https://huggingface.co/datasets/CyberHarem/agano_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 309.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/agano_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1138 | 631.64 MiB | [Download](https://huggingface.co/datasets/CyberHarem/agano_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 437.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/agano_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1138 | 836.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/agano_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/agano_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 21 |  |  |  |  |  | 1girl, red_skirt, serafuku, solo, black_sailor_collar, looking_at_viewer, pleated_skirt, white_gloves, anchor_symbol, sleeveless_shirt, black_necktie, simple_background, smile, midriff, white_background, cowboy_shot, navel, cleavage, one-hour_drawing_challenge, garter_straps, one_eye_closed |
| 1 | 9 |  |  |  |  |  | 1girl, black_sailor_collar, garter_straps, pleated_skirt, red_skirt, serafuku, single_thighhigh, sleeveless_shirt, solo, uneven_legwear, white_background, anchor_symbol, looking_at_viewer, simple_background, white_gloves, black_necktie, full_body, midriff, sitting |
| 2 | 5 |  |  |  |  |  | 1girl, looking_at_viewer, skirt, solo, white_gloves, open_mouth, serafuku, smile, blush, navel, midriff, necktie, star_(symbol) |
| 3 | 27 |  |  |  |  |  | 1girl, blush, 1boy, hetero, nipples, open_mouth, solo_focus, censored, sex, white_gloves, vaginal, penis, serafuku, clothes_lift, miniskirt, necktie, single_thighhigh, cum_in_pussy |
| 4 | 5 |  |  |  |  |  | 1girl, black_hairband, black_panties, crop_top, elbow_gloves, highleg_panties, shimakaze_(kancolle)_(cosplay), solo, striped_thighhighs, thong, white_gloves, black_neckerchief, cowboy_shot, looking_at_viewer, microskirt, miniskirt, navel, pleated_skirt, serafuku, blue_sailor_collar, blue_skirt, blush, open_mouth, simple_background, white_background, aqua_eyes, plump, sleeveless, smile, twitter_username |
| 5 | 14 |  |  |  |  |  | 1girl, pleated_skirt, red_skirt, solo, two-tone_jacket, simple_background, smile, looking_at_viewer, open_mouth, white_background, official_alternate_costume, cowboy_shot, hoodie, long_sleeves, white_thighhighs, twitter_username |
| 6 | 8 |  |  |  |  |  | 1girl, looking_at_viewer, smile, solo, alternate_costume, open_mouth, pleated_skirt, long_sleeves, white_background, black_skirt, simple_background, sweater, white_shirt, black_jacket, brown_jacket, cowboy_shot, school_uniform, twitter_username, black_thighhighs, blazer, bowtie, collared_shirt, heart |
| 7 | 6 |  |  |  |  |  | 1girl, solo, yukata, alternate_costume, obi, open_mouth, smile, blush, looking_at_viewer, floral_print, uchiwa |
| 8 | 7 |  |  |  |  |  | 1girl, looking_at_viewer, navel, simple_background, solo, collarbone, nipples, white_background, bangs, blush, smile, completely_nude, closed_mouth, open_mouth, stomach, upper_body, very_long_hair |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | red_skirt | serafuku | solo | black_sailor_collar | looking_at_viewer | pleated_skirt | white_gloves | anchor_symbol | sleeveless_shirt | black_necktie | simple_background | smile | midriff | white_background | cowboy_shot | navel | cleavage | one-hour_drawing_challenge | garter_straps | one_eye_closed | single_thighhigh | uneven_legwear | full_body | sitting | skirt | open_mouth | blush | necktie | star_(symbol) | 1boy | hetero | nipples | solo_focus | censored | sex | vaginal | penis | clothes_lift | miniskirt | cum_in_pussy | black_hairband | black_panties | crop_top | elbow_gloves | highleg_panties | shimakaze_(kancolle)_(cosplay) | striped_thighhighs | thong | black_neckerchief | microskirt | blue_sailor_collar | blue_skirt | aqua_eyes | plump | sleeveless | twitter_username | two-tone_jacket | official_alternate_costume | hoodie | long_sleeves | white_thighhighs | alternate_costume | black_skirt | sweater | white_shirt | black_jacket | brown_jacket | school_uniform | black_thighhighs | blazer | bowtie | collared_shirt | heart | yukata | obi | floral_print | uchiwa | collarbone | bangs | completely_nude | closed_mouth | stomach | upper_body | very_long_hair |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:------------|:-----------|:-------|:----------------------|:--------------------|:----------------|:---------------|:----------------|:-------------------|:----------------|:--------------------|:--------|:----------|:-------------------|:--------------|:--------|:-----------|:-----------------------------|:----------------|:-----------------|:-------------------|:-----------------|:------------|:----------|:--------|:-------------|:--------|:----------|:----------------|:-------|:---------|:----------|:-------------|:-----------|:------|:----------|:--------|:---------------|:------------|:---------------|:-----------------|:----------------|:-----------|:---------------|:------------------|:---------------------------------|:---------------------|:--------|:--------------------|:-------------|:---------------------|:-------------|:------------|:--------|:-------------|:-------------------|:------------------|:-----------------------------|:---------|:---------------|:-------------------|:--------------------|:--------------|:----------|:--------------|:---------------|:---------------|:-----------------|:-------------------|:---------|:---------|:-----------------|:--------|:---------|:------|:---------------|:---------|:-------------|:--------|:------------------|:---------------|:----------|:-------------|:-----------------|
| 0 | 21 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 9 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | X | X | | | | | X | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 5 |  |  |  |  |  | X | | X | X | | X | | X | | | | | X | X | | | X | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 27 |  |  |  |  |  | X | | X | | | | | X | | | | | | | | | | | | | | X | | | | | X | X | X | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | | X | X | | X | X | X | | | | X | X | | X | X | X | | | | | | | | | | X | X | | | | | | | | | | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 14 |  |  |  |  |  | X | X | | X | | X | X | | | | | X | X | | X | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 8 |  |  |  |  |  | X | | | X | | X | X | | | | | X | X | | X | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | |
| 7 | 6 |  |  |  |  |  | X | | | X | | X | | | | | | | X | | | | | | | | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | X | X | X | X | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | | X | | X | | | | | | X | X | | X | | X | | | | | | | | | | X | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X |
|
CyberHarem/agano_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T06:41:57+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T18:15:51+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of agano/阿賀野 (Kantai Collection)
========================================
This is the dataset of agano/阿賀野 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'black\_hair, long\_hair, breasts, large\_breasts, green\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
2464b20b629b1c58f9ddf139624441896445f25d
|
A dataset of contradictory sentence pairs.
This is the dataset from a Master's thesis: https://repositorio-aberto.up.pt/bitstream/10216/129029/2/415679.pdf. The name of the dataset comes from the title of the thesis. You can find some documentation for the dataset in the following repository: https://github.com/BeatrizBaldaia/sentence-pair-contradictions/tree/master
Originally collated by Beatriz Souto de Sá Baldaia, I take no credit for that aspect, I just processed and uploaded it here because I needed to train a sentence contradiction model.
This dataset is a merge of several others, so I'm not sure what the license should be.
I think there is quite a lot of political content in the data, but models trained from it do seem to generalise
|
afg1/sentence-pair-contradictions
|
[
"task_categories:text-classification",
"size_categories:10K<n<100K",
"language:en",
"license:unknown",
"region:us"
] |
2023-08-21T06:55:24+00:00
|
{"language": ["en"], "license": "unknown", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification"]}
|
2023-08-21T06:59:23+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-unknown #region-us
|
A dataset of contradictory sentence pairs.
This is the dataset from a Master's thesis: URL The name of the dataset comes from the title of the thesis. You can find some documentation for the dataset in the following repository: URL
Originally collated by Beatriz Souto de Sá Baldaia, I take no credit for that aspect, I just processed and uploaded it here because I needed to train a sentence contradiction model.
This dataset is a merge of several others, so I'm not sure what the license should be.
I think there is quite a lot of political content in the data, but models trained from it do seem to generalise
|
[] |
[
"TAGS\n#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-unknown #region-us \n"
] |
[
40
] |
[
"passage: TAGS\n#task_categories-text-classification #size_categories-10K<n<100K #language-English #license-unknown #region-us \n"
] |
94f843ebc4b39dd2582c68447eca0007f259dfd3
|
# Dataset Card for "ocr-masks"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
xinke-wang/ocr-masks
|
[
"region:us"
] |
2023-08-21T07:02:38+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "caption", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1087540216.0, "num_examples": 1138}], "download_size": 1087038711, "dataset_size": 1087540216.0}}
|
2023-08-21T07:09:11+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "ocr-masks"
More Information needed
|
[
"# Dataset Card for \"ocr-masks\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"ocr-masks\"\n\nMore Information needed"
] |
[
6,
15
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"ocr-masks\"\n\nMore Information needed"
] |
d325094db92b5c5ce9654e7999688fc4afa6636c
|
# AutoTrain Dataset for project: full2
## Dataset Description
This dataset has been automatically processed by AutoTrain for project full2.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"text": "# TPQN\t4\n# Key\t0\tC\tmajor\t0\n# Meter\t0\t4\t4\t16\n# Meter\t292\t0\t0\t0\n# SPQN 0 0.5\n0 1 15 G#6\n1 1 19 C#4\n2 5 21 G#4\n3 7 19 C#5\n4 9 17 E5\n5 11 59 G#5\n6 13 50 A6\n7 13 43 C#6\n8 15 17 G#6\n9 17 39 E5\n10 17 44 G#6\n11 19 31 F#6\n12 19 21 C#5\n13 19 25 C#4\n14 21 60 G#4\n15 21 37 C#5\n16 23 27 E4\n17 25 58 C#4\n18 27 60 E4\n19 29 60 E6\n20 31 33 F#6\n21 33 60 F#6\n22 33 58 A3\n23 35 60 A4\n24 37 58 C#5\n25 39 52 E5\n26 41 48 A5\n27 43 46 C#6\n28 45 58 G#6\n29 47 56 C#6\n30 49 54 A5\n31 50 74 A6\n32 52 58 E5\n33 54 66 A5\n34 56 95 C#6\n35 58 75 G#6\n36 60 64 F#6\n37 62 65 E6\n38 64 66 F#6\n39 64 100 B3\n40 65 68 E6\n41 66 100 F#4\n42 66 70 F#6\n43 68 100 B4\n44 68 100 E6\n45 70 100 Eb5\n46 70 93 F#6\n47 71 73 F#5\n48 73 100 F#5\n49 74 79 B5\n50 75 77 G#6\n51 77 79 G#6\n52 77 79 Eb6\n53 79 80 Eb6\n54 79 91 G#6\n55 79 85 B5\n56 80 83 Eb6\n57 81 83 A6\n58 83 85 A6\n60 83 107 Eb6\n61 85 89 A6\n62 85 100 B5\n63 87 100 B6\n64 89 103 A6\n65 91 95 G#6\n66 93 97 F#6\n68 95 98 G#6\n69 97 102 F#6\n70 97 140 Eb4\n71 98 99 G#6\n72 99 100 G#6\n73 99 140 G#4\n74 100 102 G#6\n75 101 140 C5\n76 102 140 F#6\n77 102 104 G#6\n78 103 104 A6\n79 104 140 G#6\n80 105 106 A6\n81 105 113 G#5\n82 106 107 A6\n83 107 108 A6\n84 107 115 C6\n85 108 140 A6\n86 109 118 Eb6\n87 111 112 C7\n88 112 113 C7\n89 113 140 G#5\n90 113 142 C7\n91 115 131 C6\n92 118 123 Eb6\n93 120 160 C#7\n94 123 127 Eb6\n95 127 153 Eb6\n96 131 179 C6\n97 146 180 C#5\n98 146 147 E7\n99 147 172 E7\n100 150 190 G#6\n101 150 180 G#5\n102 153 155 Eb7\n103 153 180 Eb6\n104 155 157 Eb7\n105 157 176 Eb7\n106 160 179 C#7\n107 160 183 C#6\n108 164 212 G#7\n109 168 216 F#7\n110 172 174 E7\n111 174 178 E7\n112 176 178 Eb7\n114 178 181 E7\n115 179 220 Eb7\n116 180 181 C#7\n117 180 187 E5\n118 181 182 C#7\n119 181 220 E7\n120 182 183 C#7\n121 183 220 C#7\n122 183 184 A6\n123 183 220 C#6\n124 184 187 A6\n125 187 194 E5\n126 187 204 A6\n127 190 194 F#6\n128 190 194 A5\n129 194 201 E5\n130 194 206 F#6\n131 194 220 A5\n132 198 220 A4\n133 201 249 E5\n134 202 242 G#6\n135 204 205 A6\n136 205 207 A6\n137 206 229 B4\n138 206 208 F#6\n139 207 241 A6\n140 208 210 F#6\n141 210 212 F#5\n142 210 237 F#6\n143 212 217 F#5\n144 214 215 Eb6\n145 214 243 B5\n146 215 216 Eb6\n147 216 254 Eb6\n148 217 222 F#5\n149 221 260 Eb5\n150 222 224 F#5\n151 224 226 F#5\n152 226 260 F#5\n153 229 246 B4\n154 234 250 E6\n155 237 246 F#6\n156 240 288 C5\n157 241 289 G#5\n158 241 260 C6\n159 242 287 G#6\n160 246 247 F#6\n161 248 292 F#6\n162 250 286 E6\n163 255 260 Eb6\n164 260 280 C6\n165 260 280 Eb6\n The above is a music score for piano. TQDN 4 refers to \u201cTick per quarter note (QN) is 4\u201d; \u201c# Key\t0\tC\tmajor\t 0\u201d refers to \u201cKey defined at tick 0 is C major with key_fifth = 0. (key_fifth = 1 (one sharp), -1 (one flat), \u2026)\u201d; \u201c# Meter\t0\t4\t4\t16\u201d refers to \u201cMeter defined at tick 0 is 4/4, for which the bar length is 16 ticks.\u201d; \u201c# SPQN\t0\t0.5\u201d refers to \u201cTempo defined at tick 0 is 0.5 (sec per QN)\u201d. The note event is defined as [No.] [onset score time] [offset score time] [spelled pitch] According to the score, please predict its corresponding emotion label. The output shall be either one of these labels:happy, angry, sad, relaxed.",
"target": 3
},
{
"text": "# TPQN\t4\n# Key\t0\tC\tmajor\t0\n# Meter\t0\t4\t4\t16\n# Meter\t240\t0\t0\t0\n# SPQN 0 0.5\n0 4 22 C#5\n1 5 22 C5\n2 6 14 Bb4\n3 6 22 Bb2\n4 8 21 F3\n5 10 22 Bb3\n6 12 15 F4\n7 12 17 C4\n8 14 17 Bb4\n9 14 22 C#4\n10 15 22 F4\n11 17 22 C4\n12 17 22 Bb4\n13 19 22 F5\n14 21 36 Eb5\n15 21 23 F3\n16 21 36 F2\n17 21 36 G#4\n18 23 36 C3\n19 25 36 F3\n20 27 36 G3\n21 29 36 G#3\n22 32 36 C#5\n23 34 36 C5\n24 36 43 Bb4\n25 36 51 F#2\n26 36 42 C#4\n27 36 43 F#4\n28 38 51 C#3\n29 40 51 F#3\n30 42 47 G#3\n31 42 45 C#4\n32 43 47 Bb4\n33 43 47 F#4\n34 43 51 Bb3\n35 45 51 C#4\n36 47 51 G#3\n37 47 51 Bb4\n38 47 51 F#4\n39 49 51 F5\n40 51 66 Eb5\n41 51 66 Bb4\n42 51 66 F#4\n43 51 66 Eb2\n44 53 66 Bb2\n45 55 66 Eb3\n46 57 62 F3\n47 58 64 F#3\n48 62 66 F3\n49 62 66 C#5\n50 64 66 F#3\n51 64 66 C5\n52 66 71 C#4\n53 66 81 Bb4\n54 66 81 F#2\n55 66 77 F#4\n56 68 77 C#3\n57 69 81 F#3\n58 71 77 G#3\n59 71 73 C#4\n60 71 77 C5\n61 73 79 C#4\n62 73 79 Bb3\n63 73 81 C#5\n64 77 81 C5\n65 77 81 G#3\n66 77 81 F#4\n67 77 81 C#3\n68 79 81 Bb3\n69 79 81 C#4\n70 81 93 G#4\n71 81 96 G#2\n72 81 88 C#5\n73 83 96 Eb3\n74 84 96 G#3\n75 84 91 C5\n76 84 96 Eb4\n77 86 92 Bb3\n78 88 96 C#5\n79 88 93 C4\n80 90 96 Eb5\n81 92 96 C5\n82 92 96 Bb3\n83 93 96 G#4\n84 93 96 C4\n85 96 111 Bb2\n86 96 126 Bb4\n87 97 113 F3\n88 99 107 Bb3\n89 101 109 C4\n90 103 118 C#4\n91 103 119 F4\n92 107 115 Bb3\n93 109 117 C4\n94 111 126 Bb2\n95 113 126 F3\n96 115 122 Bb3\n97 117 120 C4\n98 119 126 C#4\n99 119 124 F4\n100 120 126 C4\n101 122 126 Bb3\n102 124 127 C#5\n103 124 126 F4\n104 126 127 C5\n105 126 141 Bb2\n106 126 133 Bb4\n107 128 141 F3\n108 130 141 Bb3\n109 132 135 F4\n110 132 137 C4\n111 133 137 Bb4\n112 133 141 C#4\n113 135 141 F4\n114 137 141 C4\n115 137 141 Bb4\n116 138 141 F5\n117 141 156 F2\n118 141 156 Eb5\n119 141 156 G#4\n120 142 156 C3\n121 144 156 F3\n122 146 156 G3\n123 148 152 G#3\n124 150 156 F4\n125 151 156 C#5\n126 152 156 G#3\n127 153 156 C5\n128 155 170 F#2\n129 155 162 F#4\n130 155 162 Bb4\n131 157 170 C#3\n132 159 162 F#3\n133 160 164 C#4\n134 160 166 G#3\n135 162 166 Bb4\n136 162 170 Bb3\n137 162 170 F#4\n138 164 170 C#4\n139 166 170 Bb4\n140 166 170 G#3\n141 168 170 F5\n142 170 185 Eb2\n143 170 185 Bb4\n144 170 185 Eb5\n145 170 185 F#4\n146 170 185 Eb4\n147 172 185 Bb2\n148 173 185 Eb3\n149 175 181 F3\n150 177 183 F#3\n151 181 185 C#5\n152 181 185 F3\n153 183 185 F#3\n154 183 185 C5\n155 185 200 Bb4\n156 185 191 C#4\n157 185 191 F#2\n158 185 191 F#4\n159 187 200 C#3\n160 189 191 F#3\n161 191 196 G#3\n162 191 196 C5\n163 191 192 C#4\n164 191 200 F#4\n165 193 198 Bb3\n166 193 200 C#5\n167 193 198 C#4\n168 196 200 G#3\n169 196 200 C5\n170 198 200 Bb3\n171 198 200 C#4\n172 200 212 G#4\n173 200 215 G#2\n174 200 207 C#5\n175 202 215 Eb3\n176 203 215 G#3\n177 204 211 C5\n178 204 215 Eb4\n179 205 211 Bb3\n180 207 215 C#5\n181 207 212 C4\n182 209 215 Eb5\n183 211 215 C5\n184 211 215 Bb3\n185 212 215 G#4\n186 212 215 C4\n187 215 240 Bb4\n188 215 230 Bb2\n189 217 230 F3\n190 219 226 Bb3\n191 220 223 C4\n192 222 230 C#4\n193 223 238 F4\n194 223 228 C4\n195 226 234 Bb3\n196 228 230 C4\n197 230 240 Bb2\n198 232 240 F3\n199 234 240 Bb3\n200 236 239 C4\n201 238 240 C#4\n202 238 240 F4\n The above is a music score for piano. TQDN 4 refers to \u201cTick per quarter note (QN) is 4\u201d; \u201c# Key\t0\tC\tmajor\t 0\u201d refers to \u201cKey defined at tick 0 is C major with key_fifth = 0. (key_fifth = 1 (one sharp), -1 (one flat), \u2026)\u201d; \u201c# Meter\t0\t4\t4\t16\u201d refers to \u201cMeter defined at tick 0 is 4/4, for which the bar length is 16 ticks.\u201d; \u201c# SPQN\t0\t0.5\u201d refers to \u201cTempo defined at tick 0 is 0.5 (sec per QN)\u201d. The note event is defined as [No.] [onset score time] [offset score time] [spelled pitch] According to the score, please predict its corresponding emotion label. The output shall be either one of these labels:happy, angry, sad, relaxed.",
"target": 0
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(names=['angry', 'happy', 'relaxed', 'sad'], id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 855 |
| valid | 216 |
|
Kagou/autotrain-data-full2
|
[
"task_categories:text-classification",
"region:us"
] |
2023-08-21T07:05:10+00:00
|
{"task_categories": ["text-classification"]}
|
2023-08-21T07:05:42+00:00
|
[] |
[] |
TAGS
#task_categories-text-classification #region-us
|
AutoTrain Dataset for project: full2
====================================
Dataset Description
-------------------
This dataset has been automatically processed by AutoTrain for project full2.
### Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
-----------------
### Data Instances
A sample from this dataset looks as follows:
### Dataset Fields
The dataset has the following fields (also called "features"):
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
|
[
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
[
"TAGS\n#task_categories-text-classification #region-us \n",
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
[
17,
27,
17,
23,
27
] |
[
"passage: TAGS\n#task_categories-text-classification #region-us \n### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------### Data Instances\n\n\nA sample from this dataset looks as follows:### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):### Dataset Splits\n\n\nThis dataset is split into a train and validation split. The split sizes are as follow:"
] |
79e07a057adb26313c182d9421264b451510f1d9
|
# Dataset Card for "face-partuv2beautifulluv-ffhq10-samples"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
kasvii/face-partuv2beautifulluv-ffhq10-samples
|
[
"region:us"
] |
2023-08-21T07:06:24+00:00
|
{"dataset_info": {"features": [{"name": "original_image", "dtype": "image"}, {"name": "edit_prompt", "dtype": "string"}, {"name": "edited_image", "dtype": "image"}, {"name": "control_image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 9517189.0, "num_examples": 10}], "download_size": 0, "dataset_size": 9517189.0}}
|
2023-08-21T07:21:15+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "face-partuv2beautifulluv-ffhq10-samples"
More Information needed
|
[
"# Dataset Card for \"face-partuv2beautifulluv-ffhq10-samples\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"face-partuv2beautifulluv-ffhq10-samples\"\n\nMore Information needed"
] |
[
6,
27
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"face-partuv2beautifulluv-ffhq10-samples\"\n\nMore Information needed"
] |
899af5208e84de44ff03d7f7c1419765540a8c59
|
# Dataset of gambier_bay (Kantai Collection)
This is the dataset of gambier_bay (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `blonde_hair, long_hair, twintails, hairband, blue_eyes, breasts, large_breasts, hair_between_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:------------|:------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 534.26 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gambier_bay_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 324.20 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gambier_bay_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1192 | 717.35 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gambier_bay_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 484.42 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gambier_bay_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1192 | 1008.17 MiB | [Download](https://huggingface.co/datasets/CyberHarem/gambier_bay_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/gambier_bay_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 22 |  |  |  |  |  | 1girl, blue_shirt, breast_pocket, solo, collared_shirt, simple_background, short_sleeves, upper_body, looking_at_viewer, open_mouth, white_background, twitter_username, multicolored_gloves, one-hour_drawing_challenge, blush |
| 1 | 14 |  |  |  |  |  | 1girl, blue_shirt, breast_pocket, collared_shirt, short_sleeves, shorts, solo, simple_background, open_mouth, belt, cowboy_shot, white_background, white_gloves, white_thighhighs, multicolored_gloves |
| 2 | 8 |  |  |  |  |  | 1boy, 1girl, blush, hetero, open_mouth, paizuri, short_sleeves, solo_focus, blue_shirt, collared_shirt, white_gloves, on_back, bangs, nipples, penis, crying_with_eyes_open, cum_on_breasts, open_clothes |
| 3 | 5 |  |  |  |  |  | 1girl, blush, nipples, nude, simple_background, solo, looking_at_viewer, open_mouth, collarbone, navel, white_background, upper_body |
| 4 | 11 |  |  |  |  |  | 1girl, bikini_top_only, red_bikini, red_gloves, christmas, looking_at_viewer, santa_hat, solo, open_mouth, blush, navel, santa_bikini, santa_costume, simple_background, white_background, alternate_costume, red_shorts, belt, cleavage, upper_body, choker, cowboy_shot, fur-trimmed_gloves, star_print, thighhighs |
| 5 | 6 |  |  |  |  |  | 1girl, open_mouth, simple_background, solo, blush, looking_at_viewer, navel, white_background, black_bikini, cleavage, collarbone |
| 6 | 10 |  |  |  |  |  | collared_shirt, employee_uniform, 1girl, blue_shirt, solo, alternate_costume, blush, ponytail, alternate_hairstyle, open_mouth, looking_at_viewer, name_tag, simple_background, vertical-striped_shirt, bangs, blue_hairband, upper_body, white_background, breast_pocket, holding, pleated_skirt, short_sleeves, smile |
| 7 | 24 |  |  |  |  |  | 1girl, sailor_dress, solo, long_sleeves, blue_hairband, white_dress, open_mouth, looking_at_viewer, simple_background, white_background, white_thighhighs, blue_sailor_collar |
| 8 | 14 |  |  |  |  |  | detached_collar, playboy_bunny, rabbit_ears, strapless_leotard, fake_animal_ears, wrist_cuffs, 1girl, cleavage, looking_at_viewer, solo, simple_background, white_background, open_mouth, blush, cowboy_shot, alternate_costume, rabbit_tail, black_bowtie, black_leotard, brown_pantyhose, gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blue_shirt | breast_pocket | solo | collared_shirt | simple_background | short_sleeves | upper_body | looking_at_viewer | open_mouth | white_background | twitter_username | multicolored_gloves | one-hour_drawing_challenge | blush | shorts | belt | cowboy_shot | white_gloves | white_thighhighs | 1boy | hetero | paizuri | solo_focus | on_back | bangs | nipples | penis | crying_with_eyes_open | cum_on_breasts | open_clothes | nude | collarbone | navel | bikini_top_only | red_bikini | red_gloves | christmas | santa_hat | santa_bikini | santa_costume | alternate_costume | red_shorts | cleavage | choker | fur-trimmed_gloves | star_print | thighhighs | black_bikini | employee_uniform | ponytail | alternate_hairstyle | name_tag | vertical-striped_shirt | blue_hairband | holding | pleated_skirt | smile | sailor_dress | long_sleeves | white_dress | blue_sailor_collar | detached_collar | playboy_bunny | rabbit_ears | strapless_leotard | fake_animal_ears | wrist_cuffs | rabbit_tail | black_bowtie | black_leotard | brown_pantyhose | gloves |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------|:----------------|:-------|:-----------------|:--------------------|:----------------|:-------------|:--------------------|:-------------|:-------------------|:-------------------|:----------------------|:-----------------------------|:--------|:---------|:-------|:--------------|:---------------|:-------------------|:-------|:---------|:----------|:-------------|:----------|:--------|:----------|:--------|:------------------------|:-----------------|:---------------|:-------|:-------------|:--------|:------------------|:-------------|:-------------|:------------|:------------|:---------------|:----------------|:--------------------|:-------------|:-----------|:---------|:---------------------|:-------------|:-------------|:---------------|:-------------------|:-----------|:----------------------|:-----------|:-------------------------|:----------------|:----------|:----------------|:--------|:---------------|:---------------|:--------------|:---------------------|:------------------|:----------------|:--------------|:--------------------|:-------------------|:--------------|:--------------|:---------------|:----------------|:------------------|:---------|
| 0 | 22 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 14 |  |  |  |  |  | X | X | X | X | X | X | X | | | X | X | | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 8 |  |  |  |  |  | X | X | | | X | | X | | | X | | | | | X | | | | X | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | | | X | | X | | X | X | X | X | | | | X | | | | | | | | | | | | X | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 11 |  |  |  |  |  | X | | | X | | X | | X | X | X | X | | | | X | | X | X | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | | | X | | X | | | X | X | X | | | | X | | | | | | | | | | | | | | | | | | X | X | | | | | | | | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 10 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | X | | | | | | | | | | | X | | | | | | | | | | | | | | | | X | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | |
| 7 | 24 |  |  |  |  |  | X | | | X | | X | | | X | X | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | X | X | X | X | | | | | | | | | | | |
| 8 | 14 |  |  |  |  |  | X | | | X | | X | | | X | X | X | | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/gambier_bay_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T07:15:52+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-16T05:49:06+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of gambier\_bay (Kantai Collection)
===========================================
This is the dataset of gambier\_bay (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'blonde\_hair, long\_hair, twintails, hairband, blue\_eyes, breasts, large\_breasts, hair\_between\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
0f9e4857863161b7a5f173914885d9ff938c3821
|
# Dataset Card for "face-partuv2beautifulluv-ffhq5-samples"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
kasvii/face-partuv2beautifulluv-ffhq5-samples
|
[
"region:us"
] |
2023-08-21T07:25:51+00:00
|
{"dataset_info": {"features": [{"name": "original_image", "dtype": "image"}, {"name": "edit_prompt", "dtype": "string"}, {"name": "edited_image", "dtype": "image"}, {"name": "control_image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 4873402.0, "num_examples": 5}], "download_size": 0, "dataset_size": 4873402.0}}
|
2023-08-21T07:29:45+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "face-partuv2beautifulluv-ffhq5-samples"
More Information needed
|
[
"# Dataset Card for \"face-partuv2beautifulluv-ffhq5-samples\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"face-partuv2beautifulluv-ffhq5-samples\"\n\nMore Information needed"
] |
[
6,
26
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"face-partuv2beautifulluv-ffhq5-samples\"\n\nMore Information needed"
] |
b3c22a8908b7e3d81b73b8630cfd426864bd8ec0
|
init
|
ChrisGao/32k
|
[
"region:us"
] |
2023-08-21T07:34:15+00:00
|
{}
|
2023-08-21T07:37:35+00:00
|
[] |
[] |
TAGS
#region-us
|
init
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
3dbe481fe33416c0eaf6ab092b55f5a525271065
|
# Dataset of yuugumo/夕雲 (Kantai Collection)
This is the dataset of yuugumo/夕雲 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `green_hair, long_hair, mole, mole_under_mouth, braid, single_braid, ahoge, blue_eyes, very_long_hair, breasts, bow`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 528.11 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yuugumo_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 318.78 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yuugumo_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1123 | 660.98 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yuugumo_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 470.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yuugumo_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1123 | 901.96 MiB | [Download](https://huggingface.co/datasets/CyberHarem/yuugumo_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/yuugumo_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 12 |  |  |  |  |  | 1girl, bowtie, school_uniform, solo, white_shirt, long_sleeves, looking_at_viewer, simple_background, upper_body, halterneck, smile, white_background, purple_dress, sleeveless |
| 1 | 5 |  |  |  |  |  | 1girl, bowtie, full_body, grey_pantyhose, halterneck, lace-up_boots, pleated_dress, purple_dress, school_uniform, solo, standing, white_background, white_shirt, simple_background, long_sleeves, blush_stickers, character_name, chibi, looking_at_viewer, one-hour_drawing_challenge |
| 2 | 10 |  |  |  |  |  | 1girl, blazer, school_uniform, solo, aqua_bowtie, halterneck, upper_body, long_sleeves, looking_at_viewer, purple_dress, smile, twitter_username, simple_background, one-hour_drawing_challenge, white_background |
| 3 | 9 |  |  |  |  |  | 1girl, aqua_bowtie, blazer, long_sleeves, school_uniform, solo, cowboy_shot, grey_thighhighs, purple_dress, purple_skirt, smile, halterneck, looking_at_viewer, pleated_skirt, purple_vest, shirt, blush |
| 4 | 31 |  |  |  |  |  | bowtie, school_uniform, white_shirt, 1girl, short_sleeves, solo, pleated_skirt, fingerless_gloves, purple_skirt, white_background, brown_gloves, simple_background, grey_thighhighs, looking_at_viewer, blouse, purple_vest, smile, cowboy_shot |
| 5 | 10 |  |  |  |  |  | 1girl, medium_breasts, solo, purple_panties, simple_background, navel, purple_bra, underwear_only, white_background, looking_at_viewer, blush, collarbone, cowboy_shot, twitter_username, smile |
| 6 | 8 |  |  |  |  |  | 1boy, 1girl, blush, hetero, penis, solo_focus, school_uniform, smile, mosaic_censoring, open_mouth, feet, handjob, medium_breasts, cum_in_clothes, footjob, looking_at_viewer, panties_under_pantyhose |
| 7 | 20 |  |  |  |  |  | fake_animal_ears, rabbit_ears, playboy_bunny, 1girl, detached_collar, strapless_leotard, wrist_cuffs, solo, purple_leotard, looking_at_viewer, simple_background, rabbit_tail, medium_breasts, adapted_costume, large_breasts, white_background, fishnet_pantyhose, aqua_bowtie, cleavage |
| 8 | 8 |  |  |  |  |  | blue_sky, day, looking_at_viewer, medium_breasts, smile, 1girl, blush, cowboy_shot, ocean, outdoors, water, bangs, bikini, collarbone, navel, cleavage, alternate_costume, bare_shoulders, cloudy_sky, competition_swimsuit, open_mouth, solo_focus, standing |
| 9 | 13 |  |  |  |  |  | 1girl, blush, 1boy, hetero, sex, bangs, nipples, solo_focus, sweat, open_mouth, completely_nude, vaginal, girl_on_top, medium_breasts, navel, tears, white_background, collarbone, cowgirl_position, cum_in_pussy, large_breasts, simple_background, smile, spoken_heart, trembling |
| 10 | 5 |  |  |  |  |  | 1girl, solo, white_apron, black_dress, enmaided, frilled_apron, looking_at_viewer, large_breasts, maid_apron, maid_headdress, one-hour_drawing_challenge, open_mouth, simple_background, bowtie, cowboy_shot, dated, long_sleeves, short_sleeves, smile, white_background, white_gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bowtie | school_uniform | solo | white_shirt | long_sleeves | looking_at_viewer | simple_background | upper_body | halterneck | smile | white_background | purple_dress | sleeveless | full_body | grey_pantyhose | lace-up_boots | pleated_dress | standing | blush_stickers | character_name | chibi | one-hour_drawing_challenge | blazer | aqua_bowtie | twitter_username | cowboy_shot | grey_thighhighs | purple_skirt | pleated_skirt | purple_vest | shirt | blush | short_sleeves | fingerless_gloves | brown_gloves | blouse | medium_breasts | purple_panties | navel | purple_bra | underwear_only | collarbone | 1boy | hetero | penis | solo_focus | mosaic_censoring | open_mouth | feet | handjob | cum_in_clothes | footjob | panties_under_pantyhose | fake_animal_ears | rabbit_ears | playboy_bunny | detached_collar | strapless_leotard | wrist_cuffs | purple_leotard | rabbit_tail | adapted_costume | large_breasts | fishnet_pantyhose | cleavage | blue_sky | day | ocean | outdoors | water | bangs | bikini | alternate_costume | bare_shoulders | cloudy_sky | competition_swimsuit | sex | nipples | sweat | completely_nude | vaginal | girl_on_top | tears | cowgirl_position | cum_in_pussy | spoken_heart | trembling | white_apron | black_dress | enmaided | frilled_apron | maid_apron | maid_headdress | dated | white_gloves |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:---------|:-----------------|:-------|:--------------|:---------------|:--------------------|:--------------------|:-------------|:-------------|:--------|:-------------------|:---------------|:-------------|:------------|:-----------------|:----------------|:----------------|:-----------|:-----------------|:-----------------|:--------|:-----------------------------|:---------|:--------------|:-------------------|:--------------|:------------------|:---------------|:----------------|:--------------|:--------|:--------|:----------------|:--------------------|:---------------|:---------|:-----------------|:-----------------|:--------|:-------------|:-----------------|:-------------|:-------|:---------|:--------|:-------------|:-------------------|:-------------|:-------|:----------|:-----------------|:----------|:--------------------------|:-------------------|:--------------|:----------------|:------------------|:--------------------|:--------------|:-----------------|:--------------|:------------------|:----------------|:--------------------|:-----------|:-----------|:------|:--------|:-----------|:--------|:--------|:---------|:--------------------|:-----------------|:-------------|:-----------------------|:------|:----------|:--------|:------------------|:----------|:--------------|:--------|:-------------------|:---------------|:---------------|:------------|:--------------|:--------------|:-----------|:----------------|:-------------|:-----------------|:--------|:---------------|
| 0 | 12 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | | X | | X | X | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 10 |  |  |  |  |  | X | | X | X | | X | X | X | X | X | X | X | X | | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 9 |  |  |  |  |  | X | | X | X | | X | X | | | X | X | | X | | | | | | | | | | | X | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 31 |  |  |  |  |  | X | X | X | X | X | | X | X | | | X | X | | | | | | | | | | | | | | | X | X | X | X | X | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 10 |  |  |  |  |  | X | | | X | | | X | X | | | X | X | | | | | | | | | | | | | | X | X | | | | | | X | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 8 |  |  |  |  |  | X | | X | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 20 |  |  |  |  |  | X | | | X | | | X | X | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 8 |  |  |  |  |  | X | | | | | | X | | | | X | | | | | | | | X | | | | | | | | X | | | | | | X | | | | | X | | X | | | X | | | | X | | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | |
| 9 | 13 |  |  |  |  |  | X | | | | | | | X | | | X | X | | | | | | | | | | | | | | | | | | | | | X | | | | | X | | X | | | X | X | X | | X | | X | | | | | | | | | | | | | | | X | | | | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | |
| 10 | 5 |  |  |  |  |  | X | X | | X | | X | X | X | | | X | X | | | | | | | | | | | X | | | | X | | | | | | | X | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X |
|
CyberHarem/yuugumo_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T07:36:55+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T12:33:43+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of yuugumo/夕雲 (Kantai Collection)
=========================================
This is the dataset of yuugumo/夕雲 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'green\_hair, long\_hair, mole, mole\_under\_mouth, braid, single\_braid, ahoge, blue\_eyes, very\_long\_hair, breasts, bow', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
335b347426b61f219fa4ae6a2411b3977467afa3
|
# Dataset Card for "donutdata2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
Amani123/donutdata2
|
[
"region:us"
] |
2023-08-21T07:50:38+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "ground_truth", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 77291761.0, "num_examples": 96}, {"name": "test", "num_bytes": 4621446.0, "num_examples": 6}, {"name": "validation", "num_bytes": 9222827.0, "num_examples": 11}], "download_size": 90088586, "dataset_size": 91136034.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}, {"split": "validation", "path": "data/validation-*"}]}]}
|
2023-08-29T12:08:47+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "donutdata2"
More Information needed
|
[
"# Dataset Card for \"donutdata2\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"donutdata2\"\n\nMore Information needed"
] |
[
6,
14
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"donutdata2\"\n\nMore Information needed"
] |
03c85ef0b72b05aa647a3eefdc63e10af083b38e
|
# 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]
|
chanelcolgate/brain-tumors-object-detection-datasets
|
[
"region:us"
] |
2023-08-21T07:51:35+00:00
|
{"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "image_id", "dtype": "int64"}, {"name": "objects", "sequence": [{"name": "id", "dtype": "int64"}, {"name": "area", "dtype": "float64"}, {"name": "bbox", "sequence": "float32", "length": 4}, {"name": "label", "dtype": {"class_label": {"names": {"0": "negative", "1": "positive"}}}}, {"name": "iscrowd", "dtype": "bool"}]}], "splits": [{"name": "train", "num_bytes": 222568, "num_examples": 893}, {"name": "test", "num_bytes": 55697, "num_examples": 223}], "download_size": 12896319, "dataset_size": 278265}}
|
2023-08-21T08:47:12+00:00
|
[] |
[] |
TAGS
#region-us
|
# 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.
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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 Card for Dataset Name",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
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"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations",
"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for Dataset Name",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
] |
[
6,
8,
24,
32,
10,
4,
6,
6,
5,
5,
5,
7,
4,
10,
10,
5,
5,
9,
8,
8,
7,
8,
7,
5,
6,
6,
5
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for Dataset Name## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
dee75c1fb96b4b9d4d25629fce66b2e12b50daf9
|
# Dataset Card for "5e9951c3"
[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/5e9951c3
|
[
"region:us"
] |
2023-08-21T08:20:48+00:00
|
{"dataset_info": {"features": [{"name": "result", "dtype": "string"}, {"name": "id", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 178, "num_examples": 10}], "download_size": 1339, "dataset_size": 178}}
|
2023-08-21T08:20:49+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "5e9951c3"
More Information needed
|
[
"# Dataset Card for \"5e9951c3\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"5e9951c3\"\n\nMore Information needed"
] |
[
6,
16
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"5e9951c3\"\n\nMore Information needed"
] |
2cc9985699a1a8593eab6ddef4f59bc1ecf6d774
|
# amazon_reviews_multi_fr_prompt_classes_classification
## Summary
**amazon_reviews_multi_fr_prompt_classes_classification** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
It contains **4,480,000** rows that can be used for a text classification task.
The original data (without prompts) comes from the dataset [amazon_reviews_multi](https://huggingface.co/datasets/amazon_reviews_multi) by Keung et al. where only the French split has been kept.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
## Prompts used
### List
21 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
```
'Le texte suivant parle-t-il de "'+classes+'" ?\n Texte : '+text,
'Le texte suivant concerne-t-il "'+classes+'" ?\n Texte : '+text,
'Le texte suivant évoque-t-il "'+classes+'" ?\n Texte : '+text,
text+'\n Étant donné la liste de catégories suivante : "'+classes+'" à quelle catégorie appartient le texte ?',
text+'\n Étant donné la liste de classes suivante : "'+classes+'" à quelle classe appartient le texte ?',
'Étant donné une liste de catégories : "'+classes+'" à quelle catégorie appartient le texte suivant ?\n Texte : '+text,
'Étant donné une liste de classes : "'+classes+'" à quelle classe appartient le texte suivant ?\n Texte : '+text,
'Étant donné un choix de catégories : "'+classes+'", le texte fait référence à laquelle ?\n Texte : '+text,
'Étant donné un choix de classe : "'+classes+'", le texte fait référence à laquelle ?\n Texte : '+text,
'Choisir une catégorie pour le texte suivant. Les options sont les suivantes : "'+classes+'"\n Texte : '+text,
'Choisir une catégorie pour le texte suivant. Les possibilités sont les suivantes : "'+classes+'"\n Texte : '+text,
'Choisir une catégorie pour le texte suivant. Les choix sont les suivants : "'+classes+'"\n Texte : '+text,
'Choisir une classe pour le texte suivant. Les options sont les suivantes : "'+classes+'"\n Texte : '+text,
'Choisir une classe pour le texte suivant. Les possibilités sont les suivantes : "'+classes+'"\n Texte : '+text,
'Choisir une classe pour le texte suivant. Les choix sont les suivants : "'+classes+'"\n Texte : '+text,
'Sélectionner une catégorie pour le texte suivant. Les options sont les suivantes : "'+classes+'"\n Texte : '+text,
'Sélectionner une catégorie pour le texte suivant. Les possibilités sont les suivantes : "'+classes+'"\n Texte : '+text,
'Sélectionner une catégorie pour le texte suivant. Les choix sont les suivants : "'+classes+'"\n Texte : '+text,
'Sélectionner une classe pour le texte suivant. Les options sont les suivantes : "'+classes+'"\n Texte : '+text,
'Sélectionner une classe pour le texte suivant. Les possibilités sont les suivantes : "'+classes+'"\n Texte : '+text,
'Sélectionner une classe pour le texte suivant. Les choix sont les suivants : "'+classes+'"\n Texte : '+text
```
### Features used in the prompts
In the prompt list above, `text` and `targets` have been constructed from:
```
arm = load_dataset('amazon_reviews_multi', 'fr')
text = arm['train']['review_body'][i]
targets = arm['train']['product_category'][i].replace('personal_care_appliances','appareils_de_soins_personnels').replace('beauty','beauté').replace('lawn_and_garden','pelouse_et_jardin').replace('digital_ebook_purchase','livres_numériques').replace('musical_instruments','instruments').replace('watch','montre').replace('other','autre').replace('jewelry','bijou').replace('automotive','automobile').replace('apparel','vêtement').replace('video_games','jeux_vidéos').replace('toy','jeux').replace('luggage', 'bagages').replace('pet_products', 'produits_animaux').replace('electronics','électroniques').replace('office_product','produit_bureau').replace('drugstore','pharmacie').replace('camera','appareil_photo').replace('home','maison').replace('furniture','meubles').replace('book','livre').replace('wireless','sans_fil').replace('grocery','épicerie').replace('industrial_supplies','fournitures_industrielles').replace('kitchen','cuisine').replace('baby_product','produit_bébé').replace('shoes','chaussures').replace('home_improvement','amélioration_de_la_maison')
```
# Splits
- `train` with 4,200,000 samples
- `valid` with 140,000 samples
- `test` with 140,000 samples
-
# How to use?
```
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/amazon_reviews_multi_fr_prompt_text_generation")
```
# Citation
## Original data
> @inproceedings{marc_reviews,
title={The Multilingual Amazon Reviews Corpus},
author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { https://huggingface.co/datasets/CATIE-AQ/DFP },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
Amazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: https://docs.opendata.aws/amazon-reviews-ml/license.txt
By accessing the Multilingual Amazon Reviews Corpus ("Reviews Corpus"), you agree that the Reviews Corpus is an Amazon Service subject to the Amazon.com Conditions of Use and you agree to be bound by them, with the following additional conditions:
In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.
|
CATIE-AQ/amazon_reviews_multi_fr_prompt_classes_classification
|
[
"task_categories:text-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:amazon_reviews_multi",
"language:fr",
"license:other",
"DFP",
"french prompts",
"region:us"
] |
2023-08-21T08:27:42+00:00
|
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": "other", "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["amazon_reviews_multi"], "task_categories": ["text-classification"], "tags": ["DFP", "french prompts"]}
|
2023-10-11T11:22:57+00:00
|
[] |
[
"fr"
] |
TAGS
#task_categories-text-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #DFP #french prompts #region-us
|
# amazon_reviews_multi_fr_prompt_classes_classification
## Summary
amazon_reviews_multi_fr_prompt_classes_classification is a subset of the Dataset of French Prompts (DFP).
It contains 4,480,000 rows that can be used for a text classification task.
The original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.
## Prompts used
### List
21 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
### Features used in the prompts
In the prompt list above, 'text' and 'targets' have been constructed from:
# Splits
- 'train' with 4,200,000 samples
- 'valid' with 140,000 samples
- 'test' with 140,000 samples
-
# How to use?
## Original data
> @inproceedings{marc_reviews,
title={The Multilingual Amazon Reviews Corpus},
author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { URL },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
Amazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL
By accessing the Multilingual Amazon Reviews Corpus ("Reviews Corpus"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:
In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.
|
[
"# amazon_reviews_multi_fr_prompt_classes_classification",
"## Summary\n\namazon_reviews_multi_fr_prompt_classes_classification is a subset of the Dataset of French Prompts (DFP). \nIt contains 4,480,000 rows that can be used for a text classification task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept.\nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n21 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"### Features used in the prompts\nIn the prompt list above, 'text' and 'targets' have been constructed from:",
"# Splits\n- 'train' with 4,200,000 samples\n- 'valid' with 140,000 samples\n- 'test' with 140,000 samples\n-",
"# How to use?",
"## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nAmazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL\n\nBy accessing the Multilingual Amazon Reviews Corpus (\"Reviews Corpus\"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:\n\nIn addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have."
] |
[
"TAGS\n#task_categories-text-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #DFP #french prompts #region-us \n",
"# amazon_reviews_multi_fr_prompt_classes_classification",
"## Summary\n\namazon_reviews_multi_fr_prompt_classes_classification is a subset of the Dataset of French Prompts (DFP). \nIt contains 4,480,000 rows that can be used for a text classification task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept.\nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n21 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"### Features used in the prompts\nIn the prompt list above, 'text' and 'targets' have been constructed from:",
"# Splits\n- 'train' with 4,200,000 samples\n- 'valid' with 140,000 samples\n- 'test' with 140,000 samples\n-",
"# How to use?",
"## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nAmazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL\n\nBy accessing the Multilingual Amazon Reviews Corpus (\"Reviews Corpus\"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:\n\nIn addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have."
] |
[
89,
20,
140,
5,
46,
30,
36,
5,
89,
106,
339
] |
[
"passage: TAGS\n#task_categories-text-classification #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #DFP #french prompts #region-us \n# amazon_reviews_multi_fr_prompt_classes_classification## Summary\n\namazon_reviews_multi_fr_prompt_classes_classification is a subset of the Dataset of French Prompts (DFP). \nIt contains 4,480,000 rows that can be used for a text classification task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept.\nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.## Prompts used### List\n21 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.### Features used in the prompts\nIn the prompt list above, 'text' and 'targets' have been constructed from:# Splits\n- 'train' with 4,200,000 samples\n- 'valid' with 140,000 samples\n- 'test' with 140,000 samples\n-# How to use?## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}"
] |
a935f28426c4dc32b8d39a7d20f9453732bb23e2
|
# Dataset Card for "Neurology_Adams"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
zxvix/Neurology_Adams
|
[
"region:us"
] |
2023-08-21T08:30:44+00:00
|
{"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 7403512, "num_examples": 12454}, {"name": "test", "num_bytes": 825843, "num_examples": 1383}], "download_size": 5165097, "dataset_size": 8229355}}
|
2023-08-21T08:30:52+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "Neurology_Adams"
More Information needed
|
[
"# Dataset Card for \"Neurology_Adams\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"Neurology_Adams\"\n\nMore Information needed"
] |
[
6,
16
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"Neurology_Adams\"\n\nMore Information needed"
] |
34e85d6d7f8f7e296143e3ea3b13523cbd724692
|
# Dataset of hayashimo/早霜/早霜 (Kantai Collection)
This is the dataset of hayashimo/早霜/早霜 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `black_hair, long_hair, hair_over_one_eye, ribbon, very_long_hair, hair_ribbon, bow, brown_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 428.63 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayashimo_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 281.71 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayashimo_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1071 | 558.06 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayashimo_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 390.21 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayashimo_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1071 | 723.97 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayashimo_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/hayashimo_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 11 |  |  |  |  |  | 1girl, solo, blush, looking_at_viewer, simple_background, sitting, white_background, barefoot, medium_breasts, navel, nude, purple_eyes, smile, bikini, yellow_eyes |
| 1 | 6 |  |  |  |  |  | 1girl, black_bra, black_panties, solo, looking_at_viewer, navel, simple_background, small_breasts, underwear_only, blush, white_background, cleavage |
| 2 | 6 |  |  |  |  |  | 1girl, blush, looking_at_viewer, open_shirt, solo, black_panties, large_breasts, open_mouth, purple_eyes, grey_pantyhose, navel, nipples, no_bra, smile, white_shirt, dakimakura_(medium), full_body, on_back, skirt |
| 3 | 19 |  |  |  |  |  | 1girl, bowtie, school_uniform, solo, white_shirt, long_sleeves, looking_at_viewer, purple_dress, halterneck, simple_background, white_background, white_ribbon, cowboy_shot |
| 4 | 9 |  |  |  |  |  | 1girl, bowtie, grey_pantyhose, looking_at_viewer, school_uniform, solo, white_shirt, lace-up_boots, simple_background, long_sleeves, white_background, full_body, skirt, smile |
| 5 | 5 |  |  |  |  |  | 1girl, bowtie, holding_umbrella, long_sleeves, looking_at_viewer, school_uniform, solo, white_shirt, rain, smile, sleeveless_dress, hydrangea, upper_body |
| 6 | 14 |  |  |  |  |  | 1girl, enmaided, solo, black_dress, maid_headdress, looking_at_viewer, simple_background, maid_apron, smile, white_apron, long_sleeves, white_background, frilled_apron, puffy_sleeves, twitter_username, blush, one-hour_drawing_challenge, breasts, dated, pantyhose, purple_eyes |
| 7 | 21 |  |  |  |  |  | playboy_bunny, 1girl, bowtie, detached_collar, fake_animal_ears, rabbit_ears, wrist_cuffs, solo, strapless_leotard, purple_leotard, looking_at_viewer, rabbit_tail, grey_pantyhose, simple_background, fishnet_pantyhose, adapted_costume, small_breasts, blush, cleavage, white_background |
| 8 | 7 |  |  |  |  |  | 1boy, 1girl, blush, hetero, penis, solo_focus, fellatio, medium_breasts, open_mouth, closed_eyes, mosaic_censoring, nipples, shirt, bowtie, breasts_out, cum_on_tongue, facial, male_pubic_hair |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | blush | looking_at_viewer | simple_background | sitting | white_background | barefoot | medium_breasts | navel | nude | purple_eyes | smile | bikini | yellow_eyes | black_bra | black_panties | small_breasts | underwear_only | cleavage | open_shirt | large_breasts | open_mouth | grey_pantyhose | nipples | no_bra | white_shirt | dakimakura_(medium) | full_body | on_back | skirt | bowtie | school_uniform | long_sleeves | purple_dress | halterneck | white_ribbon | cowboy_shot | lace-up_boots | holding_umbrella | rain | sleeveless_dress | hydrangea | upper_body | enmaided | black_dress | maid_headdress | maid_apron | white_apron | frilled_apron | puffy_sleeves | twitter_username | one-hour_drawing_challenge | breasts | dated | pantyhose | playboy_bunny | detached_collar | fake_animal_ears | rabbit_ears | wrist_cuffs | strapless_leotard | purple_leotard | rabbit_tail | fishnet_pantyhose | adapted_costume | 1boy | hetero | penis | solo_focus | fellatio | closed_eyes | mosaic_censoring | shirt | breasts_out | cum_on_tongue | facial | male_pubic_hair |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------|:--------------------|:--------------------|:----------|:-------------------|:-----------|:-----------------|:--------|:-------|:--------------|:--------|:---------|:--------------|:------------|:----------------|:----------------|:-----------------|:-----------|:-------------|:----------------|:-------------|:-----------------|:----------|:---------|:--------------|:----------------------|:------------|:----------|:--------|:---------|:-----------------|:---------------|:---------------|:-------------|:---------------|:--------------|:----------------|:-------------------|:-------|:-------------------|:------------|:-------------|:-----------|:--------------|:-----------------|:-------------|:--------------|:----------------|:----------------|:-------------------|:-----------------------------|:----------|:--------|:------------|:----------------|:------------------|:-------------------|:--------------|:--------------|:--------------------|:-----------------|:--------------|:--------------------|:------------------|:-------|:---------|:--------|:-------------|:-----------|:--------------|:-------------------|:--------|:--------------|:----------------|:---------|:------------------|
| 0 | 11 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | X | X | X | | X | | | X | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | X | X | X | | | | | | X | | X | X | | | | X | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 19 |  |  |  |  |  | X | X | | X | X | | X | | | | | | | | | | | | | | | | | | | | X | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 9 |  |  |  |  |  | X | X | | X | X | | X | | | | | | X | | | | | | | | | | | X | | | X | | X | | X | X | X | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 5 |  |  |  |  |  | X | X | | X | | | | | | | | | X | | | | | | | | | | | | | | X | | | | | X | X | X | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 14 |  |  |  |  |  | X | X | X | X | X | | X | | | | | X | X | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 21 |  |  |  |  |  | X | X | X | X | X | | X | | | | | | | | | | | X | | X | | | | X | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 8 | 7 |  |  |  |  |  | X | | X | | | | | | X | | | | | | | | | | | | | | X | | X | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/hayashimo_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T08:32:27+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T14:22:52+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of hayashimo/早霜/早霜 (Kantai Collection)
==============================================
This is the dataset of hayashimo/早霜/早霜 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'black\_hair, long\_hair, hair\_over\_one\_eye, ribbon, very\_long\_hair, hair\_ribbon, bow, brown\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
e49d4ed10e65ef6fe8f46e1bb9f6726d72020786
|
# Chinese Speech Corpus
This dataset has been sourced from [SayIt](https://sayit.pdis.nat.gov.tw/), a specialized website focused on preserving transcripts and meeting notes. Presently, it encompasses a compilation of 1739 dialogues, encompassing approximately 340,000 sentences along with their respective speakers.
## License
[CC0 License](https://creativecommons.org/share-your-work/public-domain/cc0/)
|
zake7749/chinese-speech-corpus
|
[
"task_categories:conversational",
"size_categories:1K<n<10K",
"language:zh",
"license:cc",
"region:us"
] |
2023-08-21T08:33:09+00:00
|
{"language": ["zh"], "license": "cc", "size_categories": ["1K<n<10K"], "task_categories": ["conversational"], "pretty_name": "s", "dataset_info": {"features": [{"name": "sentences", "list": [{"name": "speaker", "dtype": "string"}, {"name": "speech", "dtype": "string"}]}, {"name": "source_url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 77964319, "num_examples": 1739}], "download_size": 43895652, "dataset_size": 77964319}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]}
|
2023-08-30T15:19:14+00:00
|
[] |
[
"zh"
] |
TAGS
#task_categories-conversational #size_categories-1K<n<10K #language-Chinese #license-cc #region-us
|
# Chinese Speech Corpus
This dataset has been sourced from SayIt, a specialized website focused on preserving transcripts and meeting notes. Presently, it encompasses a compilation of 1739 dialogues, encompassing approximately 340,000 sentences along with their respective speakers.
## License
CC0 License
|
[
"# Chinese Speech Corpus\n\nThis dataset has been sourced from SayIt, a specialized website focused on preserving transcripts and meeting notes. Presently, it encompasses a compilation of 1739 dialogues, encompassing approximately 340,000 sentences along with their respective speakers.",
"## License\n\nCC0 License"
] |
[
"TAGS\n#task_categories-conversational #size_categories-1K<n<10K #language-Chinese #license-cc #region-us \n",
"# Chinese Speech Corpus\n\nThis dataset has been sourced from SayIt, a specialized website focused on preserving transcripts and meeting notes. Presently, it encompasses a compilation of 1739 dialogues, encompassing approximately 340,000 sentences along with their respective speakers.",
"## License\n\nCC0 License"
] |
[
38,
64,
5
] |
[
"passage: TAGS\n#task_categories-conversational #size_categories-1K<n<10K #language-Chinese #license-cc #region-us \n# Chinese Speech Corpus\n\nThis dataset has been sourced from SayIt, a specialized website focused on preserving transcripts and meeting notes. Presently, it encompasses a compilation of 1739 dialogues, encompassing approximately 340,000 sentences along with their respective speakers.## License\n\nCC0 License"
] |
df3f902b43d8306cc9da450d873e7fe0f03a0a31
|
Move AI helps creators to animate artificial characters more easily and at a fraction of the cost of alternative solutions. This is achieved through cutting edge research in foundational models for encoding human motion and high fidelity markerless motion capture, enabling the creation of a platform for multimodal generation of 3D animation. Move AI is also adding to this platform a state-of-the-art labelled human animation dataset of over ten million assets. The dataset is composed of diverse human motion captured using their single camera and multi-camera products, which are powered by their AI and physics markerless motion capture technology. No motion capture suits are used, in order to capture the most authentic and unencumbered movement data. This collection includes raw video data, camera calibration parameters, full body 3D animation data, 2D and 3D human keypoints, forward and inverse kinematics and dynamics, foot contact information and natural language descriptions of each motion. This extensive and meticulously curated collection has a wide range of applications across many domains. It serves as a critical tool for researchers and professionals engaged in the study of human motion, the development of AI models for motion recognition and generation, digital character simulation, avatar synthesis and robotic systems inspired by human movement. The dataset is sourced from Move AI's vast network of partners who are familiar with capturing and creating 3D animation data using Move AI's products. A commercial license to the dataset, motion capture tools and foundational models will be made available.
|
move-ai/olympus
|
[
"region:us"
] |
2023-08-21T08:37:43+00:00
|
{}
|
2023-08-21T11:19:41+00:00
|
[] |
[] |
TAGS
#region-us
|
Move AI helps creators to animate artificial characters more easily and at a fraction of the cost of alternative solutions. This is achieved through cutting edge research in foundational models for encoding human motion and high fidelity markerless motion capture, enabling the creation of a platform for multimodal generation of 3D animation. Move AI is also adding to this platform a state-of-the-art labelled human animation dataset of over ten million assets. The dataset is composed of diverse human motion captured using their single camera and multi-camera products, which are powered by their AI and physics markerless motion capture technology. No motion capture suits are used, in order to capture the most authentic and unencumbered movement data. This collection includes raw video data, camera calibration parameters, full body 3D animation data, 2D and 3D human keypoints, forward and inverse kinematics and dynamics, foot contact information and natural language descriptions of each motion. This extensive and meticulously curated collection has a wide range of applications across many domains. It serves as a critical tool for researchers and professionals engaged in the study of human motion, the development of AI models for motion recognition and generation, digital character simulation, avatar synthesis and robotic systems inspired by human movement. The dataset is sourced from Move AI's vast network of partners who are familiar with capturing and creating 3D animation data using Move AI's products. A commercial license to the dataset, motion capture tools and foundational models will be made available.
|
[] |
[
"TAGS\n#region-us \n"
] |
[
6
] |
[
"passage: TAGS\n#region-us \n"
] |
236cf3d1cbcd0bcddd3003e1bbce7caf55c02f22
|
# amazon_reviews_multi_fr_prompt_title_generation_from_a_review
## Summary
**amazon_reviews_multi_fr_prompt_title_generation_from_a_review** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
It contains **3,989,924** rows that can be used for a text generation task.
The original data (without prompts) comes from the dataset [amazon_reviews_multi](https://huggingface.co/datasets/amazon_reviews_multi) by Keung et al. where only the French split has been kept.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
## Prompts used
### List
18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
```
review+'\n Générer un titre pour cet avis : ',
review+'\n Génère un titre pour cet avis : ',
review+'\n Générez un titre pour cet avis : ',
review+'\n Rédiger un titre pour cet avis : ',
review+'\n Rédige un titre pour cet avis : ',
review+'\n Rédigez un titre pour cet avis : ',
review+'\n Ecrire un titre pour cet avis : ',
review+'\n Ecris un titre pour cet avis : ',
review+'\n Ecrivez un titre pour cet avis : ',
"""Générer un titre pour l'avis suivant : """+review,
"""Génère un titre pour l'avis suivant : """+review,
"""Générez un titre pour l'avis suivant : """+review,
"""Rédiger un titre pour l'avis suivant : """+review,
"""Rédige un titre pour l'avis suivant : """+review,
"""Rédigez un titre pour l'avis suivant : """+review,
"""Ecrire un titre pour l'avis suivant : """+review,
"""Ecris un titre pour l'avis suivant : """+review,
"""Ecrivez un titre pour l'avis suivant : """+review,
review+'\n Titre :\n '
```
### Features used in the prompts
In the prompt list above, `review` and `targets` have been constructed from:
```
arm = load_dataset('amazon_reviews_multi', 'fr')
review = arm['train']['review_body'][i]
targets = arm['train']['review_title'][i]
```
# Splits
- `train` with 3,799,924 samples
- `valid` with 95,000 samples
- `test` with 95,000 samples
# How to use?
```
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/amazon_reviews_multi_fr_prompt_title_generation_from_a_review")
```
# Citation
## Original data
> @inproceedings{marc_reviews,
title={The Multilingual Amazon Reviews Corpus},
author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { https://huggingface.co/datasets/CATIE-AQ/DFP },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
Amazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: https://docs.opendata.aws/amazon-reviews-ml/license.txt
By accessing the Multilingual Amazon Reviews Corpus ("Reviews Corpus"), you agree that the Reviews Corpus is an Amazon Service subject to the Amazon.com Conditions of Use and you agree to be bound by them, with the following additional conditions:
In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.
|
CATIE-AQ/amazon_reviews_multi_fr_prompt_title_generation_from_a_review
|
[
"task_categories:text-generation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:amazon_reviews_multi",
"language:fr",
"license:other",
"title-generation",
"DFP",
"french prompts",
"region:us"
] |
2023-08-21T08:38:06+00:00
|
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": "other", "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "source_datasets": ["amazon_reviews_multi"], "task_categories": ["text-generation"], "tags": ["title-generation", "DFP", "french prompts"]}
|
2023-10-11T11:23:29+00:00
|
[] |
[
"fr"
] |
TAGS
#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #title-generation #DFP #french prompts #region-us
|
# amazon_reviews_multi_fr_prompt_title_generation_from_a_review
## Summary
amazon_reviews_multi_fr_prompt_title_generation_from_a_review is a subset of the Dataset of French Prompts (DFP).
It contains 3,989,924 rows that can be used for a text generation task.
The original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.
## Prompts used
### List
18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
### Features used in the prompts
In the prompt list above, 'review' and 'targets' have been constructed from:
# Splits
- 'train' with 3,799,924 samples
- 'valid' with 95,000 samples
- 'test' with 95,000 samples
# How to use?
## Original data
> @inproceedings{marc_reviews,
title={The Multilingual Amazon Reviews Corpus},
author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},
booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { URL },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
Amazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL
By accessing the Multilingual Amazon Reviews Corpus ("Reviews Corpus"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:
In addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have.
|
[
"# amazon_reviews_multi_fr_prompt_title_generation_from_a_review",
"## Summary\n\namazon_reviews_multi_fr_prompt_title_generation_from_a_review is a subset of the Dataset of French Prompts (DFP). \nIt contains 3,989,924 rows that can be used for a text generation task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"### Features used in the prompts\nIn the prompt list above, 'review' and 'targets' have been constructed from:",
"# Splits\n- 'train' with 3,799,924 samples\n- 'valid' with 95,000 samples\n- 'test' with 95,000 samples",
"# How to use?",
"## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nAmazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL\n\nBy accessing the Multilingual Amazon Reviews Corpus (\"Reviews Corpus\"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:\n\nIn addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have."
] |
[
"TAGS\n#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #title-generation #DFP #french prompts #region-us \n",
"# amazon_reviews_multi_fr_prompt_title_generation_from_a_review",
"## Summary\n\namazon_reviews_multi_fr_prompt_title_generation_from_a_review is a subset of the Dataset of French Prompts (DFP). \nIt contains 3,989,924 rows that can be used for a text generation task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"### Features used in the prompts\nIn the prompt list above, 'review' and 'targets' have been constructed from:",
"# Splits\n- 'train' with 3,799,924 samples\n- 'valid' with 95,000 samples\n- 'test' with 95,000 samples",
"# How to use?",
"## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nAmazon has licensed his dataset under its own agreement for non-commercial research usage only. This licence is quite restrictive preventing use anywhere a fee is received including paid for internships etc. A copy of the agreement can be found at the dataset webpage here: URL\n\nBy accessing the Multilingual Amazon Reviews Corpus (\"Reviews Corpus\"), you agree that the Reviews Corpus is an Amazon Service subject to the URL Conditions of Use and you agree to be bound by them, with the following additional conditions:\n\nIn addition to the license rights granted under the Conditions of Use, Amazon or its content providers grant you a limited, non-exclusive, non-transferable, non-sublicensable, revocable license to access and use the Reviews Corpus for purposes of academic research. You may not resell, republish, or make any commercial use of the Reviews Corpus or its contents, including use of the Reviews Corpus for commercial research, such as research related to a funding or consultancy contract, internship, or other relationship in which the results are provided for a fee or delivered to a for-profit organization. You may not (a) link or associate content in the Reviews Corpus with any personal information (including Amazon customer accounts), or (b) attempt to determine the identity of the author of any content in the Reviews Corpus. If you violate any of the foregoing conditions, your license to access and use the Reviews Corpus will automatically terminate without prejudice to any of the other rights or remedies Amazon may have."
] |
[
94,
25,
146,
5,
46,
30,
35,
5,
89,
106,
339
] |
[
"passage: TAGS\n#task_categories-text-generation #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #source_datasets-amazon_reviews_multi #language-French #license-other #title-generation #DFP #french prompts #region-us \n# amazon_reviews_multi_fr_prompt_title_generation_from_a_review## Summary\n\namazon_reviews_multi_fr_prompt_title_generation_from_a_review is a subset of the Dataset of French Prompts (DFP). \nIt contains 3,989,924 rows that can be used for a text generation task. \nThe original data (without prompts) comes from the dataset amazon_reviews_multi by Keung et al. where only the French split has been kept. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.## Prompts used### List\n18 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.### Features used in the prompts\nIn the prompt list above, 'review' and 'targets' have been constructed from:# Splits\n- 'train' with 3,799,924 samples\n- 'valid' with 95,000 samples\n- 'test' with 95,000 samples# How to use?## Original data\n> @inproceedings{marc_reviews,\n title={The Multilingual Amazon Reviews Corpus},\n author={Keung, Phillip and Lu, Yichao and Szarvas, György and Smith, Noah A.},\n booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing},\n year={2020}\n}"
] |
26253e08009e1f03dc4bcb81511f4e528b5ba215
|
# Dataset Card for "fw_squad_num_bi_train_1000_eval_100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tyzhu/fw_squad_num_bi_train_1000_eval_100
|
[
"region:us"
] |
2023-08-21T08:41:50+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "train_doc2id", "path": "data/train_doc2id-*"}, {"split": "train_id2doc", "path": "data/train_id2doc-*"}, {"split": "train_find_word", "path": "data/train_find_word-*"}, {"split": "eval_find_word", "path": "data/eval_find_word-*"}]}], "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1776667, "num_examples": 3200}, {"name": "train_doc2id", "num_bytes": 861440, "num_examples": 1100}, {"name": "train_id2doc", "num_bytes": 864740, "num_examples": 1100}, {"name": "train_find_word", "num_bytes": 50487, "num_examples": 1000}, {"name": "eval_find_word", "num_bytes": 5168, "num_examples": 100}], "download_size": 0, "dataset_size": 3558502}}
|
2023-08-22T14:53:58+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "fw_squad_num_bi_train_1000_eval_100"
More Information needed
|
[
"# Dataset Card for \"fw_squad_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"fw_squad_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
[
6,
29
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"fw_squad_num_bi_train_1000_eval_100\"\n\nMore Information needed"
] |
3cbf0f53115cfb59a163c03e9e7baae880abb354
|
# Dataset of akitsu_maru/あきつ丸 (Kantai Collection)
This is the dataset of akitsu_maru/あきつ丸 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `black_hair, short_hair, hat, breasts, peaked_cap, black_eyes, large_breasts, black_headwear, pale_skin`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 409.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsu_maru_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 279.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsu_maru_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1141 | 562.61 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsu_maru_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 383.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsu_maru_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1141 | 712.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/akitsu_maru_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/akitsu_maru_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 32 |  |  |  |  |  | 1girl, military_uniform, solo, white_gloves, pleated_skirt, black_thighhighs, looking_at_viewer, randoseru, zettai_ryouiki, lantern, black_skirt |
| 1 | 6 |  |  |  |  |  | 1girl, military_uniform, solo, white_gloves, looking_at_viewer, pleated_skirt |
| 2 | 6 |  |  |  |  |  | 1girl, black_thighhighs, looking_at_viewer, military_uniform, pantyshot, solo, white_gloves, white_panties, blush, pleated_skirt, sitting |
| 3 | 7 |  |  |  |  |  | 1girl, looking_at_viewer, military_uniform, solo, upper_body, white_gloves, blush, smile, twitter_username |
| 4 | 10 |  |  |  |  |  | 1girl, military_uniform, solo, twitter_username, upper_body, one-hour_drawing_challenge, simple_background, white_background, white_gloves, long_sleeves, looking_at_viewer, military_hat, blush, brown_eyes |
| 5 | 9 |  |  |  |  |  | 1boy, 1girl, hetero, solo_focus, white_gloves, blush, paizuri, cum_on_breasts, military_uniform, penis, heart, looking_at_viewer, nipples, pov, censored, facial, open_clothes, open_mouth |
| 6 | 9 |  |  |  |  |  | 1girl, looking_at_viewer, navel, solo, blush, cleavage, simple_background, black_bikini, collarbone, black_thighhighs, cowboy_shot, white_background, covered_nipples, white_gloves |
| 7 | 5 |  |  |  |  |  | 1girl, cleavage, cowboy_shot, playboy_bunny, solo, strapless_leotard, black_leotard, blush, fake_animal_ears, looking_at_viewer, rabbit_ears, simple_background, alternate_costume, covered_navel, white_background, wrist_cuffs, adapted_costume, apron, bare_legs, black_pantyhose, detached_collar, gradient_background, highleg_leotard, military_hat |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | military_uniform | solo | white_gloves | pleated_skirt | black_thighhighs | looking_at_viewer | randoseru | zettai_ryouiki | lantern | black_skirt | pantyshot | white_panties | blush | sitting | upper_body | smile | twitter_username | one-hour_drawing_challenge | simple_background | white_background | long_sleeves | military_hat | brown_eyes | 1boy | hetero | solo_focus | paizuri | cum_on_breasts | penis | heart | nipples | pov | censored | facial | open_clothes | open_mouth | navel | cleavage | black_bikini | collarbone | cowboy_shot | covered_nipples | playboy_bunny | strapless_leotard | black_leotard | fake_animal_ears | rabbit_ears | alternate_costume | covered_navel | wrist_cuffs | adapted_costume | apron | bare_legs | black_pantyhose | detached_collar | gradient_background | highleg_leotard |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------------------|:-------|:---------------|:----------------|:-------------------|:--------------------|:------------|:-----------------|:----------|:--------------|:------------|:----------------|:--------|:----------|:-------------|:--------|:-------------------|:-----------------------------|:--------------------|:-------------------|:---------------|:---------------|:-------------|:-------|:---------|:-------------|:----------|:-----------------|:--------|:--------|:----------|:------|:-----------|:---------|:---------------|:-------------|:--------|:-----------|:---------------|:-------------|:--------------|:------------------|:----------------|:--------------------|:----------------|:-------------------|:--------------|:--------------------|:----------------|:--------------|:------------------|:--------|:------------|:------------------|:------------------|:----------------------|:------------------|
| 0 | 32 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | X | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 7 |  |  |  |  |  | X | X | X | X | | | X | | | | | | | X | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 10 |  |  |  |  |  | X | X | X | X | | | X | | | | | | | X | | X | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 9 |  |  |  |  |  | X | X | | X | | | X | | | | | | | X | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 6 | 9 |  |  |  |  |  | X | | X | X | | X | X | | | | | | | X | | | | | | X | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | |
| 7 | 5 |  |  |  |  |  | X | | X | | | | X | | | | | | | X | | | | | | X | X | | X | | | | | | | | | | | | | | | | X | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
|
CyberHarem/akitsu_maru_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T08:53:52+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T06:25:40+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of akitsu\_maru/あきつ丸 (Kantai Collection)
================================================
This is the dataset of akitsu\_maru/あきつ丸 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'black\_hair, short\_hair, hat, breasts, peaked\_cap, black\_eyes, large\_breasts, black\_headwear, pale\_skin', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
b5f017c144f3d937ac0357e19de8bbad0415f320
|
# orange_sum_fr_prompt_fill_mask
## Summary
**orange_sum_fr_prompt_fill_mask** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
It contains **585,624** rows that can be used for a fill mask task.
The original data (without prompts) comes from the dataset [orange_sum](https://huggingface.co/datasets/orange_sum) by Eddine et al.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
## Prompts used
### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
```
'Remplacer le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Remplace le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Remplacez le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Remplacer le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Remplace le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Remplacez le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Substituer le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Substitue le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Substituez le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Substituer le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Substitue le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Substituez le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Changer le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Change le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Changez le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Changer le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Change le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Changez le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Transformer le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Transforme le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Transformez le <mask> dans le texte suivant par le mot le plus vraisemblable : '+text,
'Transformer le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Transforme le <mask> dans le texte suivant par le mot le plus probable : '+text,
'Transformez le <mask> dans le texte suivant par le mot le plus probable : '+text,
```
# Splits
- `train` with 513,624 samples
- `valid` with 36,000 samples
- `test` with 36,000 samples
# How to use?
```
from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/orange_sum_fr_prompt_fill_mask")
```
# Citation
## Original data
> @article{eddine2020barthez,
title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},
author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},
journal={arXiv preprint arXiv:2010.12321},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { https://huggingface.co/datasets/CATIE-AQ/DFP },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
CC-BY-SA-4.0
|
CATIE-AQ/orange_sum_fr_prompt_fill_mask
|
[
"task_categories:fill-mask",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:orange_sum",
"language:fr",
"license:cc-by-sa-4.0",
"DFP",
"french prompts",
"region:us"
] |
2023-08-21T08:54:21+00:00
|
{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["fr"], "license": "cc-by-sa-4.0", "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["orange_sum"], "task_categories": ["fill-mask"], "tags": ["DFP", "french prompts"]}
|
2023-10-11T11:26:36+00:00
|
[] |
[
"fr"
] |
TAGS
#task_categories-fill-mask #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-orange_sum #language-French #license-cc-by-sa-4.0 #DFP #french prompts #region-us
|
# orange_sum_fr_prompt_fill_mask
## Summary
orange_sum_fr_prompt_fill_mask is a subset of the Dataset of French Prompts (DFP).
It contains 585,624 rows that can be used for a fill mask task.
The original data (without prompts) comes from the dataset orange_sum by Eddine et al.
A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.
## Prompts used
### List
24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.
# Splits
- 'train' with 513,624 samples
- 'valid' with 36,000 samples
- 'test' with 36,000 samples
# How to use?
## Original data
> @article{eddine2020barthez,
title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},
author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},
journal={arXiv preprint arXiv:2010.12321},
year={2020}
}
## This Dataset
> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023,
author = { {Centre Aquitain des Technologies de l'Information et Electroniques} },
title = { DFP (Revision 1d24c09) },
year = 2023,
url = { URL },
doi = { 10.57967/hf/1200 },
publisher = { Hugging Face }
}
## License
CC-BY-SA-4.0
|
[
"# orange_sum_fr_prompt_fill_mask",
"## Summary\n\norange_sum_fr_prompt_fill_mask is a subset of the Dataset of French Prompts (DFP). \nIt contains 585,624 rows that can be used for a fill mask task. \nThe original data (without prompts) comes from the dataset orange_sum by Eddine et al. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"# Splits\n- 'train' with 513,624 samples\n- 'valid' with 36,000 samples\n- 'test' with 36,000 samples",
"# How to use?",
"## Original data\n> @article{eddine2020barthez,\n title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},\n author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n journal={arXiv preprint arXiv:2010.12321},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nCC-BY-SA-4.0"
] |
[
"TAGS\n#task_categories-fill-mask #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-orange_sum #language-French #license-cc-by-sa-4.0 #DFP #french prompts #region-us \n",
"# orange_sum_fr_prompt_fill_mask",
"## Summary\n\norange_sum_fr_prompt_fill_mask is a subset of the Dataset of French Prompts (DFP). \nIt contains 585,624 rows that can be used for a fill mask task. \nThe original data (without prompts) comes from the dataset orange_sum by Eddine et al. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.",
"## Prompts used",
"### List\n24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.",
"# Splits\n- 'train' with 513,624 samples\n- 'valid' with 36,000 samples\n- 'test' with 36,000 samples",
"# How to use?",
"## Original data\n> @article{eddine2020barthez,\n title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},\n author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n journal={arXiv preprint arXiv:2010.12321},\n year={2020}\n}",
"## This Dataset\n> @misc {centre_aquitain_des_technologies_de_l'information_et_electroniques_2023, \n\tauthor = { {Centre Aquitain des Technologies de l'Information et Electroniques} }, \n\ttitle = { DFP (Revision 1d24c09) }, \n\tyear = 2023, \n\turl = { URL }, \n\tdoi = { 10.57967/hf/1200 }, \n\tpublisher = { Hugging Face } \n}",
"## License\nCC-BY-SA-4.0"
] |
[
92,
16,
123,
5,
46,
35,
5,
91,
106,
9
] |
[
"passage: TAGS\n#task_categories-fill-mask #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-100K<n<1M #source_datasets-orange_sum #language-French #license-cc-by-sa-4.0 #DFP #french prompts #region-us \n# orange_sum_fr_prompt_fill_mask## Summary\n\norange_sum_fr_prompt_fill_mask is a subset of the Dataset of French Prompts (DFP). \nIt contains 585,624 rows that can be used for a fill mask task. \nThe original data (without prompts) comes from the dataset orange_sum by Eddine et al. \nA list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the xP3 dataset by Muennighoff et al.## Prompts used### List\n24 prompts were created for this dataset. The logic applied consists in proposing prompts in the indicative tense, in the form of tutoiement and in the form of vouvoiement.# Splits\n- 'train' with 513,624 samples\n- 'valid' with 36,000 samples\n- 'test' with 36,000 samples# How to use?## Original data\n> @article{eddine2020barthez,\n title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},\n author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n journal={arXiv preprint arXiv:2010.12321},\n year={2020}\n}"
] |
757c59c3766a8621bc4b83b0e2c7c577f8de8aa1
|
# Dataset Card for "sharegpt"
Combined and filtered from [shibing624/sharegpt_gpt4](https://huggingface.co/datasets/shibing624/sharegpt_gpt4) and [zetavg/ShareGPT-Processed](https://huggingface.co/datasets/zetavg/ShareGPT-Processed).
|
larryvrh/ShareGPT-Zh_Only
|
[
"task_categories:text-generation",
"task_categories:conversational",
"size_categories:1K<n<10K",
"language:zh",
"region:us"
] |
2023-08-21T08:57:50+00:00
|
{"language": ["zh"], "size_categories": ["1K<n<10K"], "task_categories": ["text-generation", "conversational"], "dataset_info": {"features": [{"name": "conversations", "list": [{"name": "from", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "src", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 69835231, "num_examples": 8631}], "download_size": 32862465, "dataset_size": 69835231}}
|
2023-08-22T07:25:50+00:00
|
[] |
[
"zh"
] |
TAGS
#task_categories-text-generation #task_categories-conversational #size_categories-1K<n<10K #language-Chinese #region-us
|
# Dataset Card for "sharegpt"
Combined and filtered from shibing624/sharegpt_gpt4 and zetavg/ShareGPT-Processed.
|
[
"# Dataset Card for \"sharegpt\"\n\nCombined and filtered from shibing624/sharegpt_gpt4 and zetavg/ShareGPT-Processed."
] |
[
"TAGS\n#task_categories-text-generation #task_categories-conversational #size_categories-1K<n<10K #language-Chinese #region-us \n",
"# Dataset Card for \"sharegpt\"\n\nCombined and filtered from shibing624/sharegpt_gpt4 and zetavg/ShareGPT-Processed."
] |
[
44,
40
] |
[
"passage: TAGS\n#task_categories-text-generation #task_categories-conversational #size_categories-1K<n<10K #language-Chinese #region-us \n# Dataset Card for \"sharegpt\"\n\nCombined and filtered from shibing624/sharegpt_gpt4 and zetavg/ShareGPT-Processed."
] |
e55b90cf9c9b1de0a21ef7a05f61edc300d2caff
|
# Dataset Card for "face-partuv2beautifulluv-ffhq8-samples"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
kasvii/face-partuv2beautifulluv-ffhq8-samples
|
[
"region:us"
] |
2023-08-21T09:00:34+00:00
|
{"dataset_info": {"features": [{"name": "original_image", "dtype": "image"}, {"name": "edit_prompt", "dtype": "string"}, {"name": "edited_image", "dtype": "image"}, {"name": "control_image", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 5773523.0, "num_examples": 8}], "download_size": 3581792, "dataset_size": 5773523.0}}
|
2023-08-21T09:00:39+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "face-partuv2beautifulluv-ffhq8-samples"
More Information needed
|
[
"# Dataset Card for \"face-partuv2beautifulluv-ffhq8-samples\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"face-partuv2beautifulluv-ffhq8-samples\"\n\nMore Information needed"
] |
[
6,
27
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"face-partuv2beautifulluv-ffhq8-samples\"\n\nMore Information needed"
] |
e3b23c0285a1b6c0b93f25e3e09da560b5af86c0
|
# Dataset of michishio/満潮/満潮 (Kantai Collection)
This is the dataset of michishio/満潮/満潮 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `twintails, hair_bun, double_bun, light_brown_hair, short_twintails, brown_eyes, bow, yellow_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:----------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 488.08 MiB | [Download](https://huggingface.co/datasets/CyberHarem/michishio_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 310.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/michishio_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1182 | 682.88 MiB | [Download](https://huggingface.co/datasets/CyberHarem/michishio_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 445.23 MiB | [Download](https://huggingface.co/datasets/CyberHarem/michishio_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1182 | 911.94 MiB | [Download](https://huggingface.co/datasets/CyberHarem/michishio_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/michishio_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 6 |  |  |  |  |  | 1girl, armband, black_apron, red_jacket, solo, track_jacket, bandana, one-hour_drawing_challenge, upper_body, white_background, blush, looking_at_viewer, simple_background |
| 1 | 32 |  |  |  |  |  | 1girl, pinafore_dress, white_shirt, green_bowtie, solo, long_sleeves, looking_at_viewer, white_background, black_dress, simple_background, cowboy_shot, blush, school_uniform, twitter_username, one-hour_drawing_challenge |
| 2 | 7 |  |  |  |  |  | 1girl, kneehighs, long_sleeves, pinafore_dress, simple_background, solo, white_background, white_shirt, black_socks, looking_at_viewer, green_bowtie, black_dress, full_body, grey_socks |
| 3 | 5 |  |  |  |  |  | 1girl, adapted_turret, black_dress, black_socks, cannon, green_bowtie, kneehighs, long_sleeves, machinery, pinafore_dress, rigging, solo, torpedo_launcher, white_background, white_shirt, school_uniform, simple_background, standing, torpedo_tubes, character_name, full_body, grey_socks, looking_at_viewer, open_mouth, white_panties |
| 4 | 7 |  |  |  |  |  | long_hair, long_sleeves, pinafore_dress, white_shirt, school_uniform, kneehighs, 2girls, black_hair, simple_background, white_background, 3girls, bowtie, brown_hair, short_hair, smile, thighhighs |
| 5 | 9 |  |  |  |  |  | pleated_skirt, short_sleeves, white_shirt, 1girl, simple_background, solo, suspender_skirt, blush, grey_skirt, white_background, arm_warmers, ascot, looking_at_viewer, brown_hair, crossed_arms |
| 6 | 9 |  |  |  |  |  | 1girl, brown_hair, school_uniform, shirt, solo, suspenders, short_hair, arm_warmers, looking_at_viewer, pleated_skirt, blush, kneehighs |
| 7 | 6 |  |  |  |  |  | 1girl, short_sleeves, solo, white_gloves, looking_at_viewer, official_alternate_costume, simple_background, thighhighs, two-tone_dress, white_background, abyssal_ship, checkered_clothes, cowboy_shot, frilled_dress, white_dress |
| 8 | 9 |  |  |  |  |  | 1girl, detached_collar, playboy_bunny, rabbit_ears, black_leotard, fake_animal_ears, looking_at_viewer, solo, strapless_leotard, wrist_cuffs, black_pantyhose, simple_background, green_bowtie, rabbit_tail, white_background, alternate_costume, blush, gloves, short_hair, sitting, small_breasts, twitter_username |
| 9 | 10 |  |  |  |  |  | 1girl, solo, blush, looking_at_viewer, navel, cowboy_shot, simple_background, small_breasts, white_background, black_bikini, one-hour_drawing_challenge, collarbone, dated, open_mouth, twitter_username |
| 10 | 15 |  |  |  |  |  | 1girl, looking_at_viewer, solo, school_swimsuit, blue_one-piece_swimsuit, cowboy_shot, simple_background, small_breasts, white_background, blush, covered_navel |
| 11 | 5 |  |  |  |  |  | 1girl, blush, completely_nude, small_breasts, looking_at_viewer, open_mouth, solo, nipples, ass, looking_back, navel, pussy, sitting |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | armband | black_apron | red_jacket | solo | track_jacket | bandana | one-hour_drawing_challenge | upper_body | white_background | blush | looking_at_viewer | simple_background | pinafore_dress | white_shirt | green_bowtie | long_sleeves | black_dress | cowboy_shot | school_uniform | twitter_username | kneehighs | black_socks | full_body | grey_socks | adapted_turret | cannon | machinery | rigging | torpedo_launcher | standing | torpedo_tubes | character_name | open_mouth | white_panties | long_hair | 2girls | black_hair | 3girls | bowtie | brown_hair | short_hair | smile | thighhighs | pleated_skirt | short_sleeves | suspender_skirt | grey_skirt | arm_warmers | ascot | crossed_arms | shirt | suspenders | white_gloves | official_alternate_costume | two-tone_dress | abyssal_ship | checkered_clothes | frilled_dress | white_dress | detached_collar | playboy_bunny | rabbit_ears | black_leotard | fake_animal_ears | strapless_leotard | wrist_cuffs | black_pantyhose | rabbit_tail | alternate_costume | gloves | sitting | small_breasts | navel | black_bikini | collarbone | dated | school_swimsuit | blue_one-piece_swimsuit | covered_navel | completely_nude | nipples | ass | looking_back | pussy |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:----------|:--------------|:-------------|:-------|:---------------|:----------|:-----------------------------|:-------------|:-------------------|:--------|:--------------------|:--------------------|:-----------------|:--------------|:---------------|:---------------|:--------------|:--------------|:-----------------|:-------------------|:------------|:--------------|:------------|:-------------|:-----------------|:---------|:------------|:----------|:-------------------|:-----------|:----------------|:-----------------|:-------------|:----------------|:------------|:---------|:-------------|:---------|:---------|:-------------|:-------------|:--------|:-------------|:----------------|:----------------|:------------------|:-------------|:--------------|:--------|:---------------|:--------|:-------------|:---------------|:-----------------------------|:-----------------|:---------------|:--------------------|:----------------|:--------------|:------------------|:----------------|:--------------|:----------------|:-------------------|:--------------------|:--------------|:------------------|:--------------|:--------------------|:---------|:----------|:----------------|:--------|:---------------|:-------------|:--------|:------------------|:--------------------------|:----------------|:------------------|:----------|:------|:---------------|:--------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 32 |  |  |  |  |  | X | | | | X | | | X | | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 7 |  |  |  |  |  | X | | | | X | | | | | X | | X | X | X | X | X | X | X | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 5 |  |  |  |  |  | X | | | | X | | | | | X | | X | X | X | X | X | X | X | | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 7 |  |  |  |  |  | | | | | | | | | | X | | | X | X | X | | X | | | X | | X | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 9 |  |  |  |  |  | X | | | | X | | | | | X | X | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 9 |  |  |  |  |  | X | | | | X | | | | | | X | X | | | | | | | | X | | X | | | | | | | | | | | | | | | | | | | X | X | | | X | | | | X | | | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 6 |  |  |  |  |  | X | | | | X | | | | | X | | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | | X | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 9 |  |  |  |  |  | X | | | | X | | | | | X | X | X | X | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | |
| 9 | 10 |  |  |  |  |  | X | | | | X | | | X | | X | X | X | X | | | | | | X | | X | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | |
| 10 | 15 |  |  |  |  |  | X | | | | X | | | | | X | X | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | X | X | X | | | | | |
| 11 | 5 |  |  |  |  |  | X | | | | X | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | | | | | | | X | X | X | X | X |
|
CyberHarem/michishio_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T09:30:44+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T08:39:55+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of michishio/満潮/満潮 (Kantai Collection)
==============================================
This is the dataset of michishio/満潮/満潮 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'twintails, hair\_bun, double\_bun, light\_brown\_hair, short\_twintails, brown\_eyes, bow, yellow\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
589876c02ecf001fbe8f66c5b66f5bff13726818
|
**Product Name** - [CardioFlex](https://cardioflex-heart-health-formula.jimdosite.com/)
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**
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**How does CardioFlex work?**
-----------------------------
The support provided by [CardioFlex](https://cardioflex-usa.clubeo.com/page/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html) takes a multidimensional approach that addresses the primary causes of poor cardiovascular health. It plays a part in improving other aspects of health that help improve the way you live your everyday life. Below, we look at how [CardioFlex](https://cardioflex-usa.clubeo.com/page/cardioflex-reviews-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html) works inside the body and why everyone suffering from poor heart health should take it.
**CardioFlex Benefits**
-----------------------
According to Get [CardioFlex](https://www.townscript.com/e/cardioflex-424034), you can experience all of the following benefits by taking CardioFlex daily:
**Support a Healthy Heart:** [CardioFlex](https://pdfhost.io/v/KRq~yrnnQ_CardioFlex_Reduce_The_Risk_Of_Heart_Strokes_Manage_Blood_Pressure_And_Blood_Vessels) claims to support a healthy heart as you age. Typically, your heart health declines with age, which is why heart attacks and strokes are more common among older adults. With [CardioFlex](https://www.fuzia.com/article_detail/799515/cardioflex-usa-reviews-reduce-the-risk-of-heart-strokes), however, you can support heart health as you get older, helping you maintain good heart health.
**Maintain Cardio Health:** The makers of [CardioFlex](https://www.sympla.com.br/evento/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels/2128170) also advertise the formula’s ability to maintain cardio health “well into old age.” Your cardiovascular health is crucial for longevity.
**Increase Energy Levels:** CardioFlex claims to raise energy levels and help you get back to enjoying life to the fullest. Many people with cardiovascular issues experience low energy, poor endurance, and difficulty breathing, among other issues, making it difficult to be active. CardioFlex claims to help by increasing energy levels.
**Support Strong Arteries:** The best arteries are strong and flexible, allowing blood to easily flow through with minimal resistance. CardioFlex supports strong arteries using a blend of natural and powerful ingredients to support arterial health. Some of the antioxidant ingredients in CardioFlex, for example, can support artery health.
**Support Healthy Blood:** CardioFlex uses a unique formula to support healthy blood. The makers of CardioFlex claim their supplement will lead to “improved circulation and overall health.” By improving your circulation and overall health, you can support cardiovascular health by making it easier for your heart to pump blood throughout your body.
**Enhance Fitness Levels:** CardioFlex enhances fitness levels by supporting muscle growth and strong bones, helping you play tennis, hike, ride your bike, and do other things you love.
[.png)](https://www.healthsupplement24x7.com/get-cardioflex)
### _**[Get Exclusive Details about CardioFlex on Official Website!](https://www.healthsupplement24x7.com/get-cardioflex)**_
**CardioFlex Ingredients**
--------------------------
[CardioFlex](https://cardioflex.wixsite.com/cardioflex) contains nine ingredients. The manufacturer describes these ingredients as “hypertension healers” because of their effects on blood pressure.
Here are all nine active ingredients in Cardio Flex and how they work, according to the manufacturer:
**Psyllium Powder:**
Psyllium powder is a type of fiber found in many supplements – including fiber and digestion supplements. However, it’s also known for its effects on blood pressure. Studies show increasing daily fiber intake can lower blood pressure. According to the manufacturer of Cardio Flex, the psyllium powder within the formula lowers PLR-15 levels, improves blood circulation, and reduces the risk of heart disease.
**Acai Berry:**
One of the first “superfood” berries that rose to prominence, acai berry continues to be a popular health supplement ingredient. According to Cardio Flex, acai berry can lower PLR-15 levels, regulate blood sugar levels, and improve immune function, among other benefits. Acai berry works because it’s rich with vitamin C, one of nature’s best antioxidants. Vitamin C and other antioxidants can support healthy inflammation throughout your body, making it easier for your heart to work as it’s supposed to work.
**Inulin**:
nulin is the second source of fiber in Cardio Flex. Like psyllium, inulin can lower PLR-15 levels, according to the manufacturer of Cardio Flex. It also helps with weight loss and “destroys harmful cancer cells,” according to the manufacturer – which is a benefit not typically advertised with fiber supplements. Overall, inulin works in a similar way to other types of fiber: it can make you feel full, which helps with weight loss. Plus, it also encourages digestive regularity while supporting healthy blood pressure and blood flow. Inulin is also a popular prebiotic fiber because it fuels your gut bacteria, and many people take inulin daily for digestive health.
**Slippery Elm Bark:**
Slippery elm bark is best-known for its natural laxative properties, and it’s found in many digestive supplements for that reason. According to the manufacturer of Cardio Flex, however, slippery elm bark can also support healthy blood pressure by lowering PLR-15 levels. Any time a supplement improves digestion, it can also help with blood pressure because it makes it easier for your body to do its job. Plus, the slippery elm bark in Cardio Flex rejuvenates skin and nails, according to the manufacturer.
**Chlorella:**
Chlorella is a green superfood powder prized for its effects on health and wellness. Some take it daily for heart health. According to the manufacturer of Cardio Flex, chlorella supports healthy blood pressure by lowering PLR-15 levels. It also promotes hair growth and lowers cholesterol, among other benefits.
**Black Walnut:**
Black walnut is a popular digestive health supplement ingredient – similar to inulin, slippery elm bark, and psyllium husk. Black walnut is known for its ability to detoxify the body and support digestive regularity. However, the makers of Cardio Flex claim black walnut also lowers PLR-15 levels, which helps with blood pressure. In fact, the manufacturer advertises other effects linked to black walnut, including the fact it “reduces the risk of cancer” and “detoxifies the liver.”
**Ginger Root:**
Ginger root has a long history of use in traditional Chinese medicine and other natural medicine practices around the world. Some take ginger daily for heart health, blood pressure, and blood flow. According to the makers of Cardio Flex, ginger lowers PLR-15 levels while also improving brain function and reducing anxiety. High levels of anxiety are associated with high blood pressure, and many find ginger can help.
**Hyssop Leaf:**
Hyssop leaf lowers PLR-15 levels and improves blood flow by providing your body with a rich source of antioxidants. Antioxidants support healthy inflammation throughout the body – including along your blood vessels, which makes it easier for your heart to do its job. When your heart can pump blood more easily, it lowers blood pressure. Hyssop leaf is a member of the mint family, and its leaves have similar aromatic properties to mint.
**Papaya Fruit:**
The ninth and final ingredient in Cardio Flex is papaya fruit. According to the makers of CardioFlex, the papaya fruit in the supplement lowers PLR-15 levels, reduces the risk of heart disease, and regulates blood sugar. Many people with high blood pressure also tend to have high blood sugar levels. It’s part of a group of conditions called metabolic syndrome. The papaya fruit in Cardio Flex could support cardiovascular health and overall health in multiple ways.
[](https://www.healthsupplement24x7.com/get-cardioflex)
### _**[Click Here to Learn More about How Cardio Flex Ingredients helps you](https://www.healthsupplement24x7.com/get-cardioflex)**_
**How should Cardio Flex be taken?**
------------------------------------
Although this product is formulated with natural ingredients and produced under excellent certified conditions, we cannot consume it whenever we want. So the manufacturers promised us the best dosage to lower blood pressure. Use the product for at least a month to get the best benefits. You should take two capsules per day with the packaged ingredients. You can take them with any other prescription because they are fairly easy to swallow.
**Is it safe or Any Side Effects?**
-----------------------------------
Because it advocates an all-natural method of lowering blood pressure, [Cardio Flex](https://events.humanitix.com/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels) is considered safe. Each bottle is said to have been manufactured in the USA, specifically in a sterile environment at an FDA-approved, cGMP-certified facility. Even so, this supplement is not recommended for people who are pregnant, nursing or under 18 years of age. Before making a purchase, anyone with pre-existing medical conditions should consult a medical professional.
**How Much Does It Cost?**
--------------------------
The [Cardio Flex](https://devfolio.co/projects/cardioflex-3f52) Dietary supplement can be purchased only from the official website at discounted rates. You can choose any of the three packages given below-
● Good Value Package - Buy 1 bottle of Cardio Flex (30-day supply) for just $59. You are entitled to free shipping in the U.S. on this deal.
● Great Value Package- Buy 3 bottles of Cardio Flex (90-day supply) for just $55 per bottle. You can save $150 on this deal with free shipping for U.S. customers.
● Best Value Package- Buy 6 bottles of Cardio Flex (180-day supply) for $41 per bottle. You can save $360 on this deal along with free shipping for U.S. customers.
[.png)](https://www.healthsupplement24x7.com/get-cardioflex)
### _**[(LOWEST PRICE GUARANTEED) Click to Order Cardio Flex Today!](https://www.healthsupplement24x7.com/get-cardioflex)**_
**Our 100% “60 Days Money Back” Satisfaction Guarantee**
--------------------------------------------------------
[Cardio Flex](https://form.jotform.com/cardioflex/cardio-flex-reviews) supplement offers a cash-back guarantee, offering risk-free investment. You can get money-back assurance on every purchase you make on this website.
You should return the product within 60 days from the date of purchase to claim the refund. You can contact the customer support team if you have any doubts about a refund. They will provide clear instructions to file the refund.
It is risk-free to test the product and understand how it works. Make sure that the organic supplement will deliver the desired outcome.
**Where Can You Buy The Cardio Flex Supplement?**
-------------------------------------------------
The only place to get the [Cardio Flex](https://colab.research.google.com/drive/12g0W24CCB-dzmcSbdcKBHjJueHQNJNI5) is on the official website. They do not exist in any traditional brick-and-mortar or internet retailers.
So it is exclusively available from the official site. Ensure you only buy the [Cardio Flex](https://colab.research.google.com/drive/1ZWFxrm8QBhbA5Jo_Rska0ShKDcHVPpoI) from the official source above to guarantee a genuine source.
When you buy the supplement there directly, you can also take advantage of incredible discounts and other benefits, which is another benefit of this website.
**Final Word**
--------------
Heart issues affect millions of adults globally. [CardioFlex](https://www.scoop.it/topic/cardioflex) is a dietary formula from Nutriomo Labs Pte Ltd consisting of three potent nutrients dubbed CSP that may improve heart health.
[CardioFlex](https://colab.research.google.com/drive/15atWdqH32JhICbjR2BIUJJyFTQs0Kppv) daily supplies the heart with nutrients, minerals, and antioxidants essential in augmenting overall health. COQ10, Shilajit, and PQQ are the three active nutrients in [CardioFlex](https://colab.research.google.com/drive/1bHAbtcughjJ5JWHpXc_hQj2oGjlFm926). The trio work by elevating energy levels, lowering unhealthy cholesterol, improving the circulatory system, and strengthening the arteries. Visit the official website to order [CardioFlex](https://colab.research.google.com/drive/1NJq4-As7rbKyTKduxIXNmXydXy7YaXWO) today.
[.png)](https://www.healthsupplement24x7.com/get-cardioflex)
### _**[(EXCLUSIVE DEAL) Click to buy CardioFlex at Amazing Prices!](https://www.healthsupplement24x7.com/get-cardioflex)**_
_**[https://cardioflex-usa.hashnode.dev/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels](https://cardioflex-usa.hashnode.dev/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels)**_
_**[https://healthsupplements24x7.blogspot.com/2023/08/cardioflex.html](https://healthsupplements24x7.blogspot.com/2023/08/cardioflex.html)**_
_**[https://cardioflex-heart-health-formula.jimdosite.com/](https://cardioflex-heart-health-formula.jimdosite.com/)**_
_**[https://soundcloud.com/cardio-flex-352456878/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels](https://soundcloud.com/cardio-flex-352456878/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels)**_
_**[https://cardioflex-usa.clubeo.com](https://cardioflex-usa.clubeo.com)**_
_**[https://www.scoop.it/topic/cardioflex](https://www.scoop.it/topic/cardioflex)**_
_**[https://cardioflex-usa.clubeo.com/calendar/2023/08/21/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels](https://cardioflex-usa.clubeo.com/calendar/2023/08/21/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels)**_
_**[https://cardioflex-usa.clubeo.com/page/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html](https://cardioflex-usa.clubeo.com/page/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html)**_
_**[https://cardioflex-usa.clubeo.com/page/cardioflex-reviews-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html](https://cardioflex-usa.clubeo.com/page/cardioflex-reviews-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels.html)**_
_**[https://www.townscript.com/e/cardioflex-424034](https://www.townscript.com/e/cardioflex-424034)**_
_**[https://pdfhost.io/v/KRq~yrnnQ\_CardioFlex\_Reduce\_The\_Risk\_Of\_Heart\_Strokes\_Manage\_Blood\_Pressure\_And\_Blood\_Vessels](https://pdfhost.io/v/KRq~yrnnQ_CardioFlex_Reduce_The_Risk_Of_Heart_Strokes_Manage_Blood_Pressure_And_Blood_Vessels)**_
_**[https://www.fuzia.com/article\_detail/799515/cardioflex-usa-reviews-reduce-the-risk-of-heart-strokes](https://www.fuzia.com/article_detail/799515/cardioflex-usa-reviews-reduce-the-risk-of-heart-strokes)**_
_**[https://www.sympla.com.br/evento/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels/2128170](https://www.sympla.com.br/evento/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels/2128170)**_
_**[https://colab.research.google.com/drive/15atWdqH32JhICbjR2BIUJJyFTQs0Kppv](https://colab.research.google.com/drive/15atWdqH32JhICbjR2BIUJJyFTQs0Kppv)**_
_**[https://colab.research.google.com/drive/1bHAbtcughjJ5JWHpXc\_hQj2oGjlFm926](https://colab.research.google.com/drive/1bHAbtcughjJ5JWHpXc_hQj2oGjlFm926)**_
_**[https://colab.research.google.com/drive/1NJq4-As7rbKyTKduxIXNmXydXy7YaXWO](https://colab.research.google.com/drive/1NJq4-As7rbKyTKduxIXNmXydXy7YaXWO)**_
_**[https://colab.research.google.com/drive/12g0W24CCB-dzmcSbdcKBHjJueHQNJNI5](https://colab.research.google.com/drive/12g0W24CCB-dzmcSbdcKBHjJueHQNJNI5)**_
_**[https://colab.research.google.com/drive/1ZWFxrm8QBhbA5Jo\_Rska0ShKDcHVPpoI](https://colab.research.google.com/drive/1ZWFxrm8QBhbA5Jo_Rska0ShKDcHVPpoI)**_
_**[https://cardioflex.wixsite.com/cardioflex](https://cardioflex.wixsite.com/cardioflex)**_
_**[https://form.jotform.com/cardioflex/cardio-flex-reviews](https://form.jotform.com/cardioflex/cardio-flex-reviews)**_
_**[https://mcmiirm-sproonds-staafy.yolasite.com/](https://mcmiirm-sproonds-staafy.yolasite.com/)**_
_**[https://devfolio.co/projects/cardioflex-3f52](https://devfolio.co/projects/cardioflex-3f52)**_
_**[https://events.humanitix.com/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels](https://events.humanitix.com/cardioflex-reduce-the-risk-of-heart-strokes-manage-blood-pressure-and-blood-vessels)**_
|
cardioflex/cardioflex
|
[
"region:us"
] |
2023-08-21T09:38:34+00:00
|
{}
|
2023-08-21T09:39:00+00:00
|
[] |
[] |
TAGS
#region-us
|
Product Name - CardioFlex
Category\- Improves Heart health
Dosage - Direction Two Capsule Per Day
Customer Rating - 4.9/5.0
CardioFlex Side Effects - No negative complaints reported so far
Refund Policy - 60 Day Money-Back Guarantee
OFFICIAL WEBSITE - URL
CardioFlex is a dietary supplement that supports a healthy heart naturally. The lifestyle of individuals has evolved drastically, and with this evolution, mankind has seen a rise in individuals suffering from heart-related diseases. CardioFlex is a revolutionary health supplement that can help you take care of your heart. It supports your cardiovascular system, along with helping you increase energy and maintain strong fitness levels.
](URL
### _Get Exclusive Details about CardioFlex on Official Website!_
CardioFlex Ingredients
--------------------------
CardioFlex contains nine ingredients. The manufacturer describes these ingredients as “hypertension healers” because of their effects on blood pressure.
Here are all nine active ingredients in Cardio Flex and how they work, according to the manufacturer:
Psyllium Powder:
Psyllium powder is a type of fiber found in many supplements – including fiber and digestion supplements. However, it’s also known for its effects on blood pressure. Studies show increasing daily fiber intake can lower blood pressure. According to the manufacturer of Cardio Flex, the psyllium powder within the formula lowers PLR-15 levels, improves blood circulation, and reduces the risk of heart disease.
Acai Berry:
One of the first “superfood” berries that rose to prominence, acai berry continues to be a popular health supplement ingredient. According to Cardio Flex, acai berry can lower PLR-15 levels, regulate blood sugar levels, and improve immune function, among other benefits. Acai berry works because it’s rich with vitamin C, one of nature’s best antioxidants. Vitamin C and other antioxidants can support healthy inflammation throughout your body, making it easier for your heart to work as it’s supposed to work.
Inulin:
nulin is the second source of fiber in Cardio Flex. Like psyllium, inulin can lower PLR-15 levels, according to the manufacturer of Cardio Flex. It also helps with weight loss and “destroys harmful cancer cells,” according to the manufacturer – which is a benefit not typically advertised with fiber supplements. Overall, inulin works in a similar way to other types of fiber: it can make you feel full, which helps with weight loss. Plus, it also encourages digestive regularity while supporting healthy blood pressure and blood flow. Inulin is also a popular prebiotic fiber because it fuels your gut bacteria, and many people take inulin daily for digestive health.
Slippery Elm Bark:
Slippery elm bark is best-known for its natural laxative properties, and it’s found in many digestive supplements for that reason. According to the manufacturer of Cardio Flex, however, slippery elm bark can also support healthy blood pressure by lowering PLR-15 levels. Any time a supplement improves digestion, it can also help with blood pressure because it makes it easier for your body to do its job. Plus, the slippery elm bark in Cardio Flex rejuvenates skin and nails, according to the manufacturer.
Chlorella:
Chlorella is a green superfood powder prized for its effects on health and wellness. Some take it daily for heart health. According to the manufacturer of Cardio Flex, chlorella supports healthy blood pressure by lowering PLR-15 levels. It also promotes hair growth and lowers cholesterol, among other benefits.
Black Walnut:
Black walnut is a popular digestive health supplement ingredient – similar to inulin, slippery elm bark, and psyllium husk. Black walnut is known for its ability to detoxify the body and support digestive regularity. However, the makers of Cardio Flex claim black walnut also lowers PLR-15 levels, which helps with blood pressure. In fact, the manufacturer advertises other effects linked to black walnut, including the fact it “reduces the risk of cancer” and “detoxifies the liver.”
Ginger Root:
Ginger root has a long history of use in traditional Chinese medicine and other natural medicine practices around the world. Some take ginger daily for heart health, blood pressure, and blood flow. According to the makers of Cardio Flex, ginger lowers PLR-15 levels while also improving brain function and reducing anxiety. High levels of anxiety are associated with high blood pressure, and many find ginger can help.
Hyssop Leaf:
Hyssop leaf lowers PLR-15 levels and improves blood flow by providing your body with a rich source of antioxidants. Antioxidants support healthy inflammation throughout the body – including along your blood vessels, which makes it easier for your heart to do its job. When your heart can pump blood more easily, it lowers blood pressure. Hyssop leaf is a member of the mint family, and its leaves have similar aromatic properties to mint.
Papaya Fruit:
The ninth and final ingredient in Cardio Flex is papaya fruit. According to the makers of CardioFlex, the papaya fruit in the supplement lowers PLR-15 levels, reduces the risk of heart disease, and regulates blood sugar. Many people with high blood pressure also tend to have high blood sugar levels. It’s part of a group of conditions called metabolic syndrome. The papaya fruit in Cardio Flex could support cardiovascular health and overall health in multiple ways.
 for just $59. You are entitled to free shipping in the U.S. on this deal.
● Great Value Package- Buy 3 bottles of Cardio Flex (90-day supply) for just $55 per bottle. You can save $150 on this deal with free shipping for U.S. customers.
● Best Value Package- Buy 6 bottles of Cardio Flex (180-day supply) for $41 per bottle. You can save $360 on this deal along with free shipping for U.S. customers.
 Click to Order Cardio Flex Today!_
Our 100% “60 Days Money Back” Satisfaction Guarantee
--------------------------------------------------------
Cardio Flex supplement offers a cash-back guarantee, offering risk-free investment. You can get money-back assurance on every purchase you make on this website.
You should return the product within 60 days from the date of purchase to claim the refund. You can contact the customer support team if you have any doubts about a refund. They will provide clear instructions to file the refund.
It is risk-free to test the product and understand how it works. Make sure that the organic supplement will deliver the desired outcome.
Where Can You Buy The Cardio Flex Supplement?
-------------------------------------------------
The only place to get the Cardio Flex is on the official website. They do not exist in any traditional brick-and-mortar or internet retailers.
So it is exclusively available from the official site. Ensure you only buy the Cardio Flex from the official source above to guarantee a genuine source.
When you buy the supplement there directly, you can also take advantage of incredible discounts and other benefits, which is another benefit of this website.
Final Word
--------------
Heart issues affect millions of adults globally. CardioFlex is a dietary formula from Nutriomo Labs Pte Ltd consisting of three potent nutrients dubbed CSP that may improve heart health.
CardioFlex daily supplies the heart with nutrients, minerals, and antioxidants essential in augmenting overall health. COQ10, Shilajit, and PQQ are the three active nutrients in CardioFlex. The trio work by elevating energy levels, lowering unhealthy cholesterol, improving the circulatory system, and strengthening the arteries. Visit the official website to order CardioFlex today.
 Click to buy CardioFlex at Amazing Prices!_
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[
"### _Visit the Official Website to Order CardioFlex!_\n\nWhat is CardioFlex?\n-----------------------\n\nNature’s formula CardioFlex is a revolutionary formula that helps to reduce the plaque from arteries & blood vessels and promote good cardiovascular function. Plaque buildups in the arteries might increase the heart attack and stroke risk. Thus, the CardioFlex supplement eradicates plaque build-up and supports a healthy heart. It is formulated as a supplement or powder to promote healthy blood vessels and improve blood circulation to the heart. Natural ingredients have been researched by great scientists, which delivers incredible results to the users. CardioFlex supplement lowers clogging arteries & blood clotting and prevents people from high blood pressure and cholesterol levels. Studies state that thousands have changed their life and reversed heart health with this proven formula. This supplement helps users live healthy lives without strokes and heart attacks.\n\nHow does CardioFlex work?\n-----------------------------\n\nThe support provided by CardioFlex takes a multidimensional approach that addresses the primary causes of poor cardiovascular health. It plays a part in improving other aspects of health that help improve the way you live your everyday life. Below, we look at how CardioFlex works inside the body and why everyone suffering from poor heart health should take it.\n\nCardioFlex Benefits\n-----------------------\n\nAccording to Get CardioFlex, you can experience all of the following benefits by taking CardioFlex daily:\n\nSupport a Healthy Heart: CardioFlex claims to support a healthy heart as you age. Typically, your heart health declines with age, which is why heart attacks and strokes are more common among older adults. With CardioFlex, however, you can support heart health as you get older, helping you maintain good heart health.\n\nMaintain Cardio Health: The makers of CardioFlex also advertise the formula’s ability to maintain cardio health “well into old age.” Your cardiovascular health is crucial for longevity.\n\nIncrease Energy Levels: CardioFlex claims to raise energy levels and help you get back to enjoying life to the fullest. Many people with cardiovascular issues experience low energy, poor endurance, and difficulty breathing, among other issues, making it difficult to be active. CardioFlex claims to help by increasing energy levels.\n\nSupport Strong Arteries: The best arteries are strong and flexible, allowing blood to easily flow through with minimal resistance. CardioFlex supports strong arteries using a blend of natural and powerful ingredients to support arterial health. Some of the antioxidant ingredients in CardioFlex, for example, can support artery health.\n\nSupport Healthy Blood: CardioFlex uses a unique formula to support healthy blood. The makers of CardioFlex claim their supplement will lead to “improved circulation and overall health.” By improving your circulation and overall health, you can support cardiovascular health by making it easier for your heart to pump blood throughout your body.\n\nEnhance Fitness Levels: CardioFlex enhances fitness levels by supporting muscle growth and strong bones, helping you play tennis, hike, ride your bike, and do other things you love.\n\n![.png)](URL",
"### _Get Exclusive Details about CardioFlex on Official Website!_\n\nCardioFlex Ingredients\n--------------------------\n\nCardioFlex contains nine ingredients. The manufacturer describes these ingredients as “hypertension healers” because of their effects on blood pressure.\n\nHere are all nine active ingredients in Cardio Flex and how they work, according to the manufacturer:\n\nPsyllium Powder:\n\nPsyllium powder is a type of fiber found in many supplements – including fiber and digestion supplements. However, it’s also known for its effects on blood pressure. Studies show increasing daily fiber intake can lower blood pressure. According to the manufacturer of Cardio Flex, the psyllium powder within the formula lowers PLR-15 levels, improves blood circulation, and reduces the risk of heart disease.\n\nAcai Berry:\n\nOne of the first “superfood” berries that rose to prominence, acai berry continues to be a popular health supplement ingredient. According to Cardio Flex, acai berry can lower PLR-15 levels, regulate blood sugar levels, and improve immune function, among other benefits. Acai berry works because it’s rich with vitamin C, one of nature’s best antioxidants. Vitamin C and other antioxidants can support healthy inflammation throughout your body, making it easier for your heart to work as it’s supposed to work.\n\nInulin:\n\nnulin is the second source of fiber in Cardio Flex. Like psyllium, inulin can lower PLR-15 levels, according to the manufacturer of Cardio Flex. It also helps with weight loss and “destroys harmful cancer cells,” according to the manufacturer – which is a benefit not typically advertised with fiber supplements. Overall, inulin works in a similar way to other types of fiber: it can make you feel full, which helps with weight loss. Plus, it also encourages digestive regularity while supporting healthy blood pressure and blood flow. Inulin is also a popular prebiotic fiber because it fuels your gut bacteria, and many people take inulin daily for digestive health.\n\nSlippery Elm Bark:\n\nSlippery elm bark is best-known for its natural laxative properties, and it’s found in many digestive supplements for that reason. According to the manufacturer of Cardio Flex, however, slippery elm bark can also support healthy blood pressure by lowering PLR-15 levels. Any time a supplement improves digestion, it can also help with blood pressure because it makes it easier for your body to do its job. Plus, the slippery elm bark in Cardio Flex rejuvenates skin and nails, according to the manufacturer.\n\nChlorella:\n\nChlorella is a green superfood powder prized for its effects on health and wellness. Some take it daily for heart health. According to the manufacturer of Cardio Flex, chlorella supports healthy blood pressure by lowering PLR-15 levels. It also promotes hair growth and lowers cholesterol, among other benefits.\n\nBlack Walnut:\n\nBlack walnut is a popular digestive health supplement ingredient – similar to inulin, slippery elm bark, and psyllium husk. Black walnut is known for its ability to detoxify the body and support digestive regularity. However, the makers of Cardio Flex claim black walnut also lowers PLR-15 levels, which helps with blood pressure. In fact, the manufacturer advertises other effects linked to black walnut, including the fact it “reduces the risk of cancer” and “detoxifies the liver.”\n\nGinger Root:\n\nGinger root has a long history of use in traditional Chinese medicine and other natural medicine practices around the world. Some take ginger daily for heart health, blood pressure, and blood flow. According to the makers of Cardio Flex, ginger lowers PLR-15 levels while also improving brain function and reducing anxiety. High levels of anxiety are associated with high blood pressure, and many find ginger can help.\n\nHyssop Leaf:\n\nHyssop leaf lowers PLR-15 levels and improves blood flow by providing your body with a rich source of antioxidants. Antioxidants support healthy inflammation throughout the body – including along your blood vessels, which makes it easier for your heart to do its job. When your heart can pump blood more easily, it lowers blood pressure. Hyssop leaf is a member of the mint family, and its leaves have similar aromatic properties to mint.\n\nPapaya Fruit:\n\nThe ninth and final ingredient in Cardio Flex is papaya fruit. According to the makers of CardioFlex, the papaya fruit in the supplement lowers PLR-15 levels, reduces the risk of heart disease, and regulates blood sugar. Many people with high blood pressure also tend to have high blood sugar levels. It’s part of a group of conditions called metabolic syndrome. The papaya fruit in Cardio Flex could support cardiovascular health and overall health in multiple ways.\n\n![](URL",
"### _Click Here to Learn More about How Cardio Flex Ingredients helps you_\n\nHow should Cardio Flex be taken?\n------------------------------------\n\nAlthough this product is formulated with natural ingredients and produced under excellent certified conditions, we cannot consume it whenever we want. So the manufacturers promised us the best dosage to lower blood pressure. Use the product for at least a month to get the best benefits. You should take two capsules per day with the packaged ingredients. You can take them with any other prescription because they are fairly easy to swallow.\n\nIs it safe or Any Side Effects?\n-----------------------------------\n\nBecause it advocates an all-natural method of lowering blood pressure, Cardio Flex is considered safe. Each bottle is said to have been manufactured in the USA, specifically in a sterile environment at an FDA-approved, cGMP-certified facility. Even so, this supplement is not recommended for people who are pregnant, nursing or under 18 years of age. Before making a purchase, anyone with pre-existing medical conditions should consult a medical professional. \n\nHow Much Does It Cost?\n--------------------------\n\nThe Cardio Flex Dietary supplement can be purchased only from the official website at discounted rates. You can choose any of the three packages given below-\n\n● Good Value Package - Buy 1 bottle of Cardio Flex (30-day supply) for just $59. You are entitled to free shipping in the U.S. on this deal.\n\n● Great Value Package- Buy 3 bottles of Cardio Flex (90-day supply) for just $55 per bottle. You can save $150 on this deal with free shipping for U.S. customers.\n\n● Best Value Package- Buy 6 bottles of Cardio Flex (180-day supply) for $41 per bottle. You can save $360 on this deal along with free shipping for U.S. customers.\n\n![.png)](URL",
"### _(LOWEST PRICE GUARANTEED) Click to Order Cardio Flex Today!_\n\nOur 100% “60 Days Money Back” Satisfaction Guarantee\n--------------------------------------------------------\n\nCardio Flex supplement offers a cash-back guarantee, offering risk-free investment. You can get money-back assurance on every purchase you make on this website.\n\nYou should return the product within 60 days from the date of purchase to claim the refund. You can contact the customer support team if you have any doubts about a refund. They will provide clear instructions to file the refund.\n\nIt is risk-free to test the product and understand how it works. Make sure that the organic supplement will deliver the desired outcome.\n\nWhere Can You Buy The Cardio Flex Supplement?\n-------------------------------------------------\n\nThe only place to get the Cardio Flex is on the official website. They do not exist in any traditional brick-and-mortar or internet retailers.\n\nSo it is exclusively available from the official site. Ensure you only buy the Cardio Flex from the official source above to guarantee a genuine source.\n\nWhen you buy the supplement there directly, you can also take advantage of incredible discounts and other benefits, which is another benefit of this website.\n\nFinal Word\n--------------\n\nHeart issues affect millions of adults globally. CardioFlex is a dietary formula from Nutriomo Labs Pte Ltd consisting of three potent nutrients dubbed CSP that may improve heart health.\n\nCardioFlex daily supplies the heart with nutrients, minerals, and antioxidants essential in augmenting overall health. COQ10, Shilajit, and PQQ are the three active nutrients in CardioFlex. The trio work by elevating energy levels, lowering unhealthy cholesterol, improving the circulatory system, and strengthening the arteries. Visit the official website to order CardioFlex today.\n\n![.png)](URL",
"### _(EXCLUSIVE DEAL) Click to buy CardioFlex at Amazing Prices!_\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL_\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL"
] |
[
"TAGS\n#region-us \n",
"### _Visit the Official Website to Order CardioFlex!_\n\nWhat is CardioFlex?\n-----------------------\n\nNature’s formula CardioFlex is a revolutionary formula that helps to reduce the plaque from arteries & blood vessels and promote good cardiovascular function. Plaque buildups in the arteries might increase the heart attack and stroke risk. Thus, the CardioFlex supplement eradicates plaque build-up and supports a healthy heart. It is formulated as a supplement or powder to promote healthy blood vessels and improve blood circulation to the heart. Natural ingredients have been researched by great scientists, which delivers incredible results to the users. CardioFlex supplement lowers clogging arteries & blood clotting and prevents people from high blood pressure and cholesterol levels. Studies state that thousands have changed their life and reversed heart health with this proven formula. This supplement helps users live healthy lives without strokes and heart attacks.\n\nHow does CardioFlex work?\n-----------------------------\n\nThe support provided by CardioFlex takes a multidimensional approach that addresses the primary causes of poor cardiovascular health. It plays a part in improving other aspects of health that help improve the way you live your everyday life. Below, we look at how CardioFlex works inside the body and why everyone suffering from poor heart health should take it.\n\nCardioFlex Benefits\n-----------------------\n\nAccording to Get CardioFlex, you can experience all of the following benefits by taking CardioFlex daily:\n\nSupport a Healthy Heart: CardioFlex claims to support a healthy heart as you age. Typically, your heart health declines with age, which is why heart attacks and strokes are more common among older adults. With CardioFlex, however, you can support heart health as you get older, helping you maintain good heart health.\n\nMaintain Cardio Health: The makers of CardioFlex also advertise the formula’s ability to maintain cardio health “well into old age.” Your cardiovascular health is crucial for longevity.\n\nIncrease Energy Levels: CardioFlex claims to raise energy levels and help you get back to enjoying life to the fullest. Many people with cardiovascular issues experience low energy, poor endurance, and difficulty breathing, among other issues, making it difficult to be active. CardioFlex claims to help by increasing energy levels.\n\nSupport Strong Arteries: The best arteries are strong and flexible, allowing blood to easily flow through with minimal resistance. CardioFlex supports strong arteries using a blend of natural and powerful ingredients to support arterial health. Some of the antioxidant ingredients in CardioFlex, for example, can support artery health.\n\nSupport Healthy Blood: CardioFlex uses a unique formula to support healthy blood. The makers of CardioFlex claim their supplement will lead to “improved circulation and overall health.” By improving your circulation and overall health, you can support cardiovascular health by making it easier for your heart to pump blood throughout your body.\n\nEnhance Fitness Levels: CardioFlex enhances fitness levels by supporting muscle growth and strong bones, helping you play tennis, hike, ride your bike, and do other things you love.\n\n![.png)](URL",
"### _Get Exclusive Details about CardioFlex on Official Website!_\n\nCardioFlex Ingredients\n--------------------------\n\nCardioFlex contains nine ingredients. The manufacturer describes these ingredients as “hypertension healers” because of their effects on blood pressure.\n\nHere are all nine active ingredients in Cardio Flex and how they work, according to the manufacturer:\n\nPsyllium Powder:\n\nPsyllium powder is a type of fiber found in many supplements – including fiber and digestion supplements. However, it’s also known for its effects on blood pressure. Studies show increasing daily fiber intake can lower blood pressure. According to the manufacturer of Cardio Flex, the psyllium powder within the formula lowers PLR-15 levels, improves blood circulation, and reduces the risk of heart disease.\n\nAcai Berry:\n\nOne of the first “superfood” berries that rose to prominence, acai berry continues to be a popular health supplement ingredient. According to Cardio Flex, acai berry can lower PLR-15 levels, regulate blood sugar levels, and improve immune function, among other benefits. Acai berry works because it’s rich with vitamin C, one of nature’s best antioxidants. Vitamin C and other antioxidants can support healthy inflammation throughout your body, making it easier for your heart to work as it’s supposed to work.\n\nInulin:\n\nnulin is the second source of fiber in Cardio Flex. Like psyllium, inulin can lower PLR-15 levels, according to the manufacturer of Cardio Flex. It also helps with weight loss and “destroys harmful cancer cells,” according to the manufacturer – which is a benefit not typically advertised with fiber supplements. Overall, inulin works in a similar way to other types of fiber: it can make you feel full, which helps with weight loss. Plus, it also encourages digestive regularity while supporting healthy blood pressure and blood flow. Inulin is also a popular prebiotic fiber because it fuels your gut bacteria, and many people take inulin daily for digestive health.\n\nSlippery Elm Bark:\n\nSlippery elm bark is best-known for its natural laxative properties, and it’s found in many digestive supplements for that reason. According to the manufacturer of Cardio Flex, however, slippery elm bark can also support healthy blood pressure by lowering PLR-15 levels. Any time a supplement improves digestion, it can also help with blood pressure because it makes it easier for your body to do its job. Plus, the slippery elm bark in Cardio Flex rejuvenates skin and nails, according to the manufacturer.\n\nChlorella:\n\nChlorella is a green superfood powder prized for its effects on health and wellness. Some take it daily for heart health. According to the manufacturer of Cardio Flex, chlorella supports healthy blood pressure by lowering PLR-15 levels. It also promotes hair growth and lowers cholesterol, among other benefits.\n\nBlack Walnut:\n\nBlack walnut is a popular digestive health supplement ingredient – similar to inulin, slippery elm bark, and psyllium husk. Black walnut is known for its ability to detoxify the body and support digestive regularity. However, the makers of Cardio Flex claim black walnut also lowers PLR-15 levels, which helps with blood pressure. In fact, the manufacturer advertises other effects linked to black walnut, including the fact it “reduces the risk of cancer” and “detoxifies the liver.”\n\nGinger Root:\n\nGinger root has a long history of use in traditional Chinese medicine and other natural medicine practices around the world. Some take ginger daily for heart health, blood pressure, and blood flow. According to the makers of Cardio Flex, ginger lowers PLR-15 levels while also improving brain function and reducing anxiety. High levels of anxiety are associated with high blood pressure, and many find ginger can help.\n\nHyssop Leaf:\n\nHyssop leaf lowers PLR-15 levels and improves blood flow by providing your body with a rich source of antioxidants. Antioxidants support healthy inflammation throughout the body – including along your blood vessels, which makes it easier for your heart to do its job. When your heart can pump blood more easily, it lowers blood pressure. Hyssop leaf is a member of the mint family, and its leaves have similar aromatic properties to mint.\n\nPapaya Fruit:\n\nThe ninth and final ingredient in Cardio Flex is papaya fruit. According to the makers of CardioFlex, the papaya fruit in the supplement lowers PLR-15 levels, reduces the risk of heart disease, and regulates blood sugar. Many people with high blood pressure also tend to have high blood sugar levels. It’s part of a group of conditions called metabolic syndrome. The papaya fruit in Cardio Flex could support cardiovascular health and overall health in multiple ways.\n\n![](URL",
"### _Click Here to Learn More about How Cardio Flex Ingredients helps you_\n\nHow should Cardio Flex be taken?\n------------------------------------\n\nAlthough this product is formulated with natural ingredients and produced under excellent certified conditions, we cannot consume it whenever we want. So the manufacturers promised us the best dosage to lower blood pressure. Use the product for at least a month to get the best benefits. You should take two capsules per day with the packaged ingredients. You can take them with any other prescription because they are fairly easy to swallow.\n\nIs it safe or Any Side Effects?\n-----------------------------------\n\nBecause it advocates an all-natural method of lowering blood pressure, Cardio Flex is considered safe. Each bottle is said to have been manufactured in the USA, specifically in a sterile environment at an FDA-approved, cGMP-certified facility. Even so, this supplement is not recommended for people who are pregnant, nursing or under 18 years of age. Before making a purchase, anyone with pre-existing medical conditions should consult a medical professional. \n\nHow Much Does It Cost?\n--------------------------\n\nThe Cardio Flex Dietary supplement can be purchased only from the official website at discounted rates. You can choose any of the three packages given below-\n\n● Good Value Package - Buy 1 bottle of Cardio Flex (30-day supply) for just $59. You are entitled to free shipping in the U.S. on this deal.\n\n● Great Value Package- Buy 3 bottles of Cardio Flex (90-day supply) for just $55 per bottle. You can save $150 on this deal with free shipping for U.S. customers.\n\n● Best Value Package- Buy 6 bottles of Cardio Flex (180-day supply) for $41 per bottle. You can save $360 on this deal along with free shipping for U.S. customers.\n\n![.png)](URL",
"### _(LOWEST PRICE GUARANTEED) Click to Order Cardio Flex Today!_\n\nOur 100% “60 Days Money Back” Satisfaction Guarantee\n--------------------------------------------------------\n\nCardio Flex supplement offers a cash-back guarantee, offering risk-free investment. You can get money-back assurance on every purchase you make on this website.\n\nYou should return the product within 60 days from the date of purchase to claim the refund. You can contact the customer support team if you have any doubts about a refund. They will provide clear instructions to file the refund.\n\nIt is risk-free to test the product and understand how it works. Make sure that the organic supplement will deliver the desired outcome.\n\nWhere Can You Buy The Cardio Flex Supplement?\n-------------------------------------------------\n\nThe only place to get the Cardio Flex is on the official website. They do not exist in any traditional brick-and-mortar or internet retailers.\n\nSo it is exclusively available from the official site. Ensure you only buy the Cardio Flex from the official source above to guarantee a genuine source.\n\nWhen you buy the supplement there directly, you can also take advantage of incredible discounts and other benefits, which is another benefit of this website.\n\nFinal Word\n--------------\n\nHeart issues affect millions of adults globally. CardioFlex is a dietary formula from Nutriomo Labs Pte Ltd consisting of three potent nutrients dubbed CSP that may improve heart health.\n\nCardioFlex daily supplies the heart with nutrients, minerals, and antioxidants essential in augmenting overall health. COQ10, Shilajit, and PQQ are the three active nutrients in CardioFlex. The trio work by elevating energy levels, lowering unhealthy cholesterol, improving the circulatory system, and strengthening the arteries. Visit the official website to order CardioFlex today.\n\n![.png)](URL",
"### _(EXCLUSIVE DEAL) Click to buy CardioFlex at Amazing Prices!_\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL_\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL\n\n_URL"
] |
[
6,
692,
1085,
409,
407,
71
] |
[
"passage: TAGS\n#region-us \n",
"passage: ### _Visit the Official Website to Order CardioFlex!_\n\nWhat is CardioFlex?\n-----------------------\n\nNature’s formula CardioFlex is a revolutionary formula that helps to reduce the plaque from arteries & blood vessels and promote good cardiovascular function. Plaque buildups in the arteries might increase the heart attack and stroke risk. Thus, the CardioFlex supplement eradicates plaque build-up and supports a healthy heart. It is formulated as a supplement or powder to promote healthy blood vessels and improve blood circulation to the heart. Natural ingredients have been researched by great scientists, which delivers incredible results to the users. CardioFlex supplement lowers clogging arteries & blood clotting and prevents people from high blood pressure and cholesterol levels. Studies state that thousands have changed their life and reversed heart health with this proven formula. This supplement helps users live healthy lives without strokes and heart attacks.\n\nHow does CardioFlex work?\n-----------------------------\n\nThe support provided by CardioFlex takes a multidimensional approach that addresses the primary causes of poor cardiovascular health. It plays a part in improving other aspects of health that help improve the way you live your everyday life. Below, we look at how CardioFlex works inside the body and why everyone suffering from poor heart health should take it.\n\nCardioFlex Benefits\n-----------------------\n\nAccording to Get CardioFlex, you can experience all of the following benefits by taking CardioFlex daily:\n\nSupport a Healthy Heart: CardioFlex claims to support a healthy heart as you age. Typically, your heart health declines with age, which is why heart attacks and strokes are more common among older adults. With CardioFlex, however, you can support heart health as you get older, helping you maintain good heart health.\n\nMaintain Cardio Health: The makers of CardioFlex also advertise the formula’s ability to maintain cardio health “well into old age.” Your cardiovascular health is crucial for longevity.\n\nIncrease Energy Levels: CardioFlex claims to raise energy levels and help you get back to enjoying life to the fullest. Many people with cardiovascular issues experience low energy, poor endurance, and difficulty breathing, among other issues, making it difficult to be active. CardioFlex claims to help by increasing energy levels.\n\nSupport Strong Arteries: The best arteries are strong and flexible, allowing blood to easily flow through with minimal resistance. CardioFlex supports strong arteries using a blend of natural and powerful ingredients to support arterial health. Some of the antioxidant ingredients in CardioFlex, for example, can support artery health.\n\nSupport Healthy Blood: CardioFlex uses a unique formula to support healthy blood. The makers of CardioFlex claim their supplement will lead to “improved circulation and overall health.” By improving your circulation and overall health, you can support cardiovascular health by making it easier for your heart to pump blood throughout your body.\n\nEnhance Fitness Levels: CardioFlex enhances fitness levels by supporting muscle growth and strong bones, helping you play tennis, hike, ride your bike, and do other things you love.\n\n![.png)](URL",
"passage: ### _Get Exclusive Details about CardioFlex on Official Website!_\n\nCardioFlex Ingredients\n--------------------------\n\nCardioFlex contains nine ingredients. The manufacturer describes these ingredients as “hypertension healers” because of their effects on blood pressure.\n\nHere are all nine active ingredients in Cardio Flex and how they work, according to the manufacturer:\n\nPsyllium Powder:\n\nPsyllium powder is a type of fiber found in many supplements – including fiber and digestion supplements. However, it’s also known for its effects on blood pressure. Studies show increasing daily fiber intake can lower blood pressure. According to the manufacturer of Cardio Flex, the psyllium powder within the formula lowers PLR-15 levels, improves blood circulation, and reduces the risk of heart disease.\n\nAcai Berry:\n\nOne of the first “superfood” berries that rose to prominence, acai berry continues to be a popular health supplement ingredient. According to Cardio Flex, acai berry can lower PLR-15 levels, regulate blood sugar levels, and improve immune function, among other benefits. Acai berry works because it’s rich with vitamin C, one of nature’s best antioxidants. Vitamin C and other antioxidants can support healthy inflammation throughout your body, making it easier for your heart to work as it’s supposed to work.\n\nInulin:\n\nnulin is the second source of fiber in Cardio Flex. Like psyllium, inulin can lower PLR-15 levels, according to the manufacturer of Cardio Flex. It also helps with weight loss and “destroys harmful cancer cells,” according to the manufacturer – which is a benefit not typically advertised with fiber supplements. Overall, inulin works in a similar way to other types of fiber: it can make you feel full, which helps with weight loss. Plus, it also encourages digestive regularity while supporting healthy blood pressure and blood flow. Inulin is also a popular prebiotic fiber because it fuels your gut bacteria, and many people take inulin daily for digestive health.\n\nSlippery Elm Bark:\n\nSlippery elm bark is best-known for its natural laxative properties, and it’s found in many digestive supplements for that reason. According to the manufacturer of Cardio Flex, however, slippery elm bark can also support healthy blood pressure by lowering PLR-15 levels. Any time a supplement improves digestion, it can also help with blood pressure because it makes it easier for your body to do its job. Plus, the slippery elm bark in Cardio Flex rejuvenates skin and nails, according to the manufacturer.\n\nChlorella:\n\nChlorella is a green superfood powder prized for its effects on health and wellness. Some take it daily for heart health. According to the manufacturer of Cardio Flex, chlorella supports healthy blood pressure by lowering PLR-15 levels. It also promotes hair growth and lowers cholesterol, among other benefits.\n\nBlack Walnut:\n\nBlack walnut is a popular digestive health supplement ingredient – similar to inulin, slippery elm bark, and psyllium husk. Black walnut is known for its ability to detoxify the body and support digestive regularity. However, the makers of Cardio Flex claim black walnut also lowers PLR-15 levels, which helps with blood pressure. In fact, the manufacturer advertises other effects linked to black walnut, including the fact it “reduces the risk of cancer” and “detoxifies the liver.”\n\nGinger Root:\n\nGinger root has a long history of use in traditional Chinese medicine and other natural medicine practices around the world. Some take ginger daily for heart health, blood pressure, and blood flow. According to the makers of Cardio Flex, ginger lowers PLR-15 levels while also improving brain function and reducing anxiety. High levels of anxiety are associated with high blood pressure, and many find ginger can help.\n\nHyssop Leaf:\n\nHyssop leaf lowers PLR-15 levels and improves blood flow by providing your body with a rich source of antioxidants. Antioxidants support healthy inflammation throughout the body – including along your blood vessels, which makes it easier for your heart to do its job. When your heart can pump blood more easily, it lowers blood pressure. Hyssop leaf is a member of the mint family, and its leaves have similar aromatic properties to mint.\n\nPapaya Fruit:\n\nThe ninth and final ingredient in Cardio Flex is papaya fruit. According to the makers of CardioFlex, the papaya fruit in the supplement lowers PLR-15 levels, reduces the risk of heart disease, and regulates blood sugar. Many people with high blood pressure also tend to have high blood sugar levels. It’s part of a group of conditions called metabolic syndrome. The papaya fruit in Cardio Flex could support cardiovascular health and overall health in multiple ways.\n\n for just $59. You are entitled to free shipping in the U.S. on this deal.\n\n● Great Value Package- Buy 3 bottles of Cardio Flex (90-day supply) for just $55 per bottle. You can save $150 on this deal with free shipping for U.S. customers.\n\n● Best Value Package- Buy 6 bottles of Cardio Flex (180-day supply) for $41 per bottle. You can save $360 on this deal along with free shipping for U.S. customers.\n\n![.png)](URL"
] |
c6969fc0348eddc9ceb54c281799332d357ee8e5
|
# 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]
|
shhossain/book-text-classifier
|
[
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:fill-mask",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"region:us"
] |
2023-08-21T09:39:17+00:00
|
{"language": ["en"], "license": "mit", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification", "text-generation", "fill-mask"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "index", "dtype": "int64"}, {"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 118863628.4954102, "num_examples": 77650}, {"name": "test", "num_bytes": 29716672.504589804, "num_examples": 19413}], "download_size": 98048351, "dataset_size": 148580301}}
|
2023-08-26T08:02:57+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-text-classification #task_categories-text-generation #task_categories-fill-mask #size_categories-10K<n<100K #language-English #license-mit #region-us
|
# 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.
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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
|
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"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
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"#### Who are the annotators?",
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"## Considerations for Using the Data",
"### Social Impact of Dataset",
"### Discussion of Biases",
"### Other Known Limitations",
"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
"### Contributions"
] |
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"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
"### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
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"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
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"passage: TAGS\n#task_categories-text-classification #task_categories-text-generation #task_categories-fill-mask #size_categories-10K<n<100K #language-English #license-mit #region-us \n# Dataset Card for Dataset Name## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
101de062efac85539ad6d289c96ec763d61e4787
|
# Dataset Card for Evaluation run of meta-llama/Llama-2-70b-hf
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/meta-llama/Llama-2-70b-hf
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [meta-llama/Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf",
"harness_gsm8k_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-03T01:14:42.713769](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf/blob/main/results_2023-12-03T01-14-42.713769.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.5405610310841547,
"acc_stderr": 0.013727093010429788
},
"harness|gsm8k|5": {
"acc": 0.5405610310841547,
"acc_stderr": 0.013727093010429788
}
}
```
### 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]
|
open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf
|
[
"region:us"
] |
2023-08-21T10:06:07+00:00
|
{"pretty_name": "Evaluation run of meta-llama/Llama-2-70b-hf", "dataset_summary": "Dataset automatically created during the evaluation run of model [meta-llama/Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\nTo load the details from a run, you can for instance do the following:\n```python\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf\",\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-12-03T01:14:42.713769](https://huggingface.co/datasets/open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf/blob/main/results_2023-12-03T01-14-42.713769.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.5405610310841547,\n \"acc_stderr\": 0.013727093010429788\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.5405610310841547,\n \"acc_stderr\": 0.013727093010429788\n }\n}\n```", "repo_url": "https://huggingface.co/meta-llama/Llama-2-70b-hf", "leaderboard_url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "point_of_contact": "[email protected]", "configs": [{"config_name": "harness_arc_challenge_25", "data_files": [{"split": "2023_08_22T09_05_23.035851", "path": ["**/details_harness|arc:challenge|25_2023-08-22T09:05:23.035851.parquet"]}, {"split": "2023_08_22T10_47_05.866748", "path": ["**/details_harness|arc:challenge|25_2023-08-22T10:47:05.866748.parquet"]}, {"split": "2023_08_22T13_42_09.433095", "path": ["**/details_harness|arc:challenge|25_2023-08-22T13:42:09.433095.parquet"]}, {"split": "2023_08_22T13_47_53.141854", "path": ["**/details_harness|arc:challenge|25_2023-08-22T13:47:53.141854.parquet"]}, {"split": "latest", "path": ["**/details_harness|arc:challenge|25_2023-08-22T13:47:53.141854.parquet"]}]}, {"config_name": "harness_drop_3", "data_files": [{"split": "2023_09_08T23_38_08.931556", "path": ["**/details_harness|drop|3_2023-09-08T23-38-08.931556.parquet"]}, {"split": "2023_09_18T06_46_44.905361", "path": ["**/details_harness|drop|3_2023-09-18T06-46-44.905361.parquet"]}, {"split": "latest", "path": ["**/details_harness|drop|3_2023-09-18T06-46-44.905361.parquet"]}]}, {"config_name": "harness_gsm8k_5", "data_files": [{"split": "2023_09_08T23_38_08.931556", "path": ["**/details_harness|gsm8k|5_2023-09-08T23-38-08.931556.parquet"]}, {"split": "2023_09_18T06_46_44.905361", "path": ["**/details_harness|gsm8k|5_2023-09-18T06-46-44.905361.parquet"]}, {"split": "2023_12_03T01_14_42.713769", "path": ["**/details_harness|gsm8k|5_2023-12-03T01-14-42.713769.parquet"]}, {"split": "latest", "path": 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|
2023-12-03T01:14:51+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for Evaluation run of meta-llama/Llama-2-70b-hf
## Dataset Description
- Homepage:
- Repository: URL
- Paper:
- Leaderboard: URL
- Point of Contact: clementine@URL
### Dataset Summary
Dataset automatically created during the evaluation run of model meta-llama/Llama-2-70b-hf on the Open LLM Leaderboard.
The dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).
To load the details from a run, you can for instance do the following:
## Latest results
These are the latest results from run 2023-12-03T01:14:42.713769(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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 Card for Evaluation run of meta-llama/Llama-2-70b-hf",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model meta-llama/Llama-2-70b-hf on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-12-03T01:14:42.713769(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of meta-llama/Llama-2-70b-hf",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model meta-llama/Llama-2-70b-hf on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-12-03T01:14:42.713769(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
] |
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[
"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of meta-llama/Llama-2-70b-hf## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL### Dataset Summary\n\nDataset automatically created during the evaluation run of model meta-llama/Llama-2-70b-hf on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 11 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:## Latest results\n\nThese are the latest results from run 2023-12-03T01:14:42.713769(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
e29a912c9923427bb31f3ff96f96009b596a5939
|
# Dataset Card for Evaluation run of tiiuae/falcon-40b
## Dataset Description
- **Homepage:**
- **Repository:** https://huggingface.co/tiiuae/falcon-40b
- **Paper:**
- **Leaderboard:** https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
- **Point of Contact:** [email protected]
### Dataset Summary
Dataset automatically created during the evaluation run of model [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).
To load the details from a run, you can for instance do the following:
```python
from datasets import load_dataset
data = load_dataset("open-llm-leaderboard/details_tiiuae__falcon-40b",
"harness_gsm8k_5",
split="train")
```
## Latest results
These are the [latest results from run 2023-12-03T19:45:58.201621](https://huggingface.co/datasets/open-llm-leaderboard/details_tiiuae__falcon-40b/blob/main/results_2023-12-03T19-45-58.201621.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
```python
{
"all": {
"acc": 0.21455648218347234,
"acc_stderr": 0.011307604104052885
},
"harness|gsm8k|5": {
"acc": 0.21455648218347234,
"acc_stderr": 0.011307604104052885
}
}
```
### 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]
|
open-llm-leaderboard/details_tiiuae__falcon-40b
|
[
"region:us"
] |
2023-08-21T10:07:51+00:00
|
{"pretty_name": "Evaluation run of tiiuae/falcon-40b", "dataset_summary": "Dataset automatically created during the evaluation run of model [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)).\n\nTo load the details from a run, you can for instance do the following:\n```python\nfrom datasets import load_dataset\ndata = load_dataset(\"open-llm-leaderboard/details_tiiuae__falcon-40b\",\n\t\"harness_gsm8k_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2023-12-03T19:45:58.201621](https://huggingface.co/datasets/open-llm-leaderboard/details_tiiuae__falcon-40b/blob/main/results_2023-12-03T19-45-58.201621.json)(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):\n\n```python\n{\n \"all\": {\n \"acc\": 0.21455648218347234,\n \"acc_stderr\": 0.011307604104052885\n },\n \"harness|gsm8k|5\": {\n \"acc\": 0.21455648218347234,\n \"acc_stderr\": 0.011307604104052885\n }\n}\n```", "repo_url": "https://huggingface.co/tiiuae/falcon-40b", "leaderboard_url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "point_of_contact": "[email protected]", "configs": [{"config_name": "harness_arc_challenge_25", "data_files": [{"split": "2023_08_21T22_49_59.134750", "path": ["**/details_harness|arc:challenge|25_2023-08-21T22:49:59.134750.parquet"]}, {"split": "latest", "path": ["**/details_harness|arc:challenge|25_2023-08-21T22:49:59.134750.parquet"]}]}, {"config_name": "harness_drop_3", "data_files": [{"split": "2023_09_08T21_43_04.856041", "path": ["**/details_harness|drop|3_2023-09-08T21-43-04.856041.parquet"]}, {"split": "latest", "path": 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{"config_name": "results", "data_files": [{"split": "2023_08_21T11_07_51.058817", "path": ["results_2023-08-21T11:07:51.058817.parquet"]}, {"split": "2023_08_21T11_30_10.858708", "path": ["results_2023-08-21T11:30:10.858708.parquet"]}, {"split": "2023_08_21T22_49_59.134750", "path": ["results_2023-08-21T22:49:59.134750.parquet"]}, {"split": "2023_08_28T20_17_39.708485", "path": ["results_2023-08-28T20:17:39.708485.parquet"]}, {"split": "2023_09_08T21_43_04.856041", "path": ["results_2023-09-08T21-43-04.856041.parquet"]}, {"split": "2023_12_03T19_45_58.201621", "path": ["results_2023-12-03T19-45-58.201621.parquet"]}, {"split": "latest", "path": ["results_2023-12-03T19-45-58.201621.parquet"]}]}]}
|
2023-12-03T19:46:05+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for Evaluation run of tiiuae/falcon-40b
## Dataset Description
- Homepage:
- Repository: URL
- Paper:
- Leaderboard: URL
- Point of Contact: clementine@URL
### Dataset Summary
Dataset automatically created during the evaluation run of model tiiuae/falcon-40b on the Open LLM Leaderboard.
The dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional configuration "results" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).
To load the details from a run, you can for instance do the following:
## Latest results
These are the latest results from run 2023-12-03T19:45:58.201621(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the "latest" split for each eval):
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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 Card for Evaluation run of tiiuae/falcon-40b",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model tiiuae/falcon-40b on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-12-03T19:45:58.201621(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for Evaluation run of tiiuae/falcon-40b",
"## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL",
"### Dataset Summary\n\nDataset automatically created during the evaluation run of model tiiuae/falcon-40b on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:",
"## Latest results\n\nThese are the latest results from run 2023-12-03T19:45:58.201621(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):",
"### Supported Tasks and Leaderboards",
"### Languages",
"## Dataset Structure",
"### Data Instances",
"### Data Fields",
"### Data Splits",
"## Dataset Creation",
"### Curation Rationale",
"### Source Data",
"#### Initial Data Collection and Normalization",
"#### Who are the source language producers?",
"### Annotations",
"#### 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"
] |
[
6,
18,
31,
167,
66,
10,
4,
6,
6,
5,
5,
5,
7,
4,
10,
10,
5,
5,
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8,
8,
7,
8,
7,
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5
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[
"passage: TAGS\n#region-us \n# Dataset Card for Evaluation run of tiiuae/falcon-40b## Dataset Description\n\n- Homepage: \n- Repository: URL\n- Paper: \n- Leaderboard: URL\n- Point of Contact: clementine@URL### Dataset Summary\n\nDataset automatically created during the evaluation run of model tiiuae/falcon-40b on the Open LLM Leaderboard.\n\nThe dataset is composed of 124 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 6 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The \"train\" split is always pointing to the latest results.\n\nAn additional configuration \"results\" store all the aggregated results of the run (and is used to compute and display the aggregated metrics on the Open LLM Leaderboard).\n\nTo load the details from a run, you can for instance do the following:## Latest results\n\nThese are the latest results from run 2023-12-03T19:45:58.201621(note that their might be results for other tasks in the repos if successive evals didn't cover the same tasks. You find each in the results and the \"latest\" split for each eval):### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
5968b4c0777e3307dc9cd14114aa20ac9083e640
|
# Dataset of kagerou/陽炎 (Kantai Collection)
This is the dataset of kagerou/陽炎 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `brown_hair, twintails, long_hair, ribbon, ahoge, hair_ribbon, purple_eyes, green_ribbon, neck_ribbon, white_ribbon, yellow_ribbon`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 480.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kagerou_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 317.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kagerou_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1209 | 698.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kagerou_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 442.69 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kagerou_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1209 | 906.73 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kagerou_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kagerou_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 14 |  |  |  |  |  | 1girl, bike_shorts, black_gloves, fingerless_gloves, looking_at_viewer, pleated_skirt, school_uniform, short_sleeves, shorts_under_skirt, solo, white_shirt, grey_vest, cowboy_shot, simple_background, grey_skirt, black_vest, white_background, black_shorts, dress_shirt, smile, standing |
| 1 | 8 |  |  |  |  |  | 1girl, grey_vest, pleated_skirt, school_uniform, short_sleeves, solo, white_gloves, white_shirt, looking_at_viewer, simple_background, smile, grey_skirt, white_background, upper_body, blush, one_eye_closed |
| 2 | 15 |  |  |  |  |  | 1girl, school_uniform, short_sleeves, solo, upper_body, white_shirt, black_vest, grey_vest, simple_background, white_background, looking_at_viewer, gloves, smile |
| 3 | 6 |  |  |  |  |  | 1girl, black_gloves, black_vest, school_uniform, short_sleeves, solo, upper_body, white_shirt, fingerless_gloves, grey_vest, looking_at_viewer, grin |
| 4 | 6 |  |  |  |  |  | 1girl, open_mouth, school_uniform, short_sleeves, solo, vest, white_gloves, looking_at_viewer, shirt, :d, blush, pleated_skirt, twitter_username |
| 5 | 9 |  |  |  |  |  | 1girl, looking_at_viewer, solo, collarbone, navel, small_breasts, blush, white_panties, white_bra, underwear_only, cowboy_shot, medium_breasts, open_mouth, smile, white_background |
| 6 | 5 |  |  |  |  |  | 1girl, blue_sky, cloud, cowboy_shot, day, looking_at_viewer, side-tie_bikini_bottom, solo, outdoors, smile, white_bikini, ocean, collarbone, front-tie_top, medium_breasts, navel, open_mouth, rock, sitting, small_breasts, standing |
| 7 | 9 |  |  |  |  |  | 1girl, cowboy_shot, looking_at_viewer, solo, alternate_costume, blue_one-piece_swimsuit, collarbone, competition_swimsuit, standing, gradient_background, school_swimsuit, smile, covered_navel, medium_breasts, open_mouth, simple_background, white_background, white_jacket |
| 8 | 6 |  |  |  |  |  | 1girl, alternate_costume, gym_shirt, gym_uniform, solo, white_shirt, blue_buruma, cowboy_shot, looking_at_viewer, short_sleeves, t-shirt |
| 9 | 17 |  |  |  |  |  | 1girl, solo, looking_at_viewer, detached_collar, alternate_costume, playboy_bunny, strapless_leotard, black_leotard, fake_animal_ears, rabbit_ears, cleavage, medium_breasts, wrist_cuffs, black_pantyhose, bowtie, cowboy_shot, open_mouth, simple_background, smile, blush, small_breasts, white_background, covered_navel |
| 10 | 13 |  |  |  |  |  | 1girl, solo, looking_at_viewer, enmaided, open_mouth, white_apron, cowboy_shot, frilled_apron, maid_headdress, smile, black_dress, gloves, gradient_background, short_sleeves, simple_background, skirt, thighhighs |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | bike_shorts | black_gloves | fingerless_gloves | looking_at_viewer | pleated_skirt | school_uniform | short_sleeves | shorts_under_skirt | solo | white_shirt | grey_vest | cowboy_shot | simple_background | grey_skirt | black_vest | white_background | black_shorts | dress_shirt | smile | standing | white_gloves | upper_body | blush | one_eye_closed | gloves | grin | open_mouth | vest | shirt | :d | twitter_username | collarbone | navel | small_breasts | white_panties | white_bra | underwear_only | medium_breasts | blue_sky | cloud | day | side-tie_bikini_bottom | outdoors | white_bikini | ocean | front-tie_top | rock | sitting | alternate_costume | blue_one-piece_swimsuit | competition_swimsuit | gradient_background | school_swimsuit | covered_navel | white_jacket | gym_shirt | gym_uniform | blue_buruma | t-shirt | detached_collar | playboy_bunny | strapless_leotard | black_leotard | fake_animal_ears | rabbit_ears | cleavage | wrist_cuffs | black_pantyhose | bowtie | enmaided | white_apron | frilled_apron | maid_headdress | black_dress | skirt | thighhighs |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------------|:---------------|:--------------------|:--------------------|:----------------|:-----------------|:----------------|:---------------------|:-------|:--------------|:------------|:--------------|:--------------------|:-------------|:-------------|:-------------------|:---------------|:--------------|:--------|:-----------|:---------------|:-------------|:--------|:-----------------|:---------|:-------|:-------------|:-------|:--------|:-----|:-------------------|:-------------|:--------|:----------------|:----------------|:------------|:-----------------|:-----------------|:-----------|:--------|:------|:-------------------------|:-----------|:---------------|:--------|:----------------|:-------|:----------|:--------------------|:--------------------------|:-----------------------|:----------------------|:------------------|:----------------|:---------------|:------------|:--------------|:--------------|:----------|:------------------|:----------------|:--------------------|:----------------|:-------------------|:--------------|:-----------|:--------------|:------------------|:---------|:-----------|:--------------|:----------------|:-----------------|:--------------|:--------|:-------------|
| 0 | 14 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 8 |  |  |  |  |  | X | | | | X | X | X | X | | X | X | X | | X | X | | X | | | X | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 15 |  |  |  |  |  | X | | | | X | | X | X | | X | X | X | | X | | X | X | | | X | | | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | | X | X | X | | X | X | | X | X | X | | | | X | | | | | | | X | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | | | | X | X | X | X | | X | | | | | | | | | | | | X | | X | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 9 |  |  |  |  |  | X | | | | X | | | | | X | | | X | | | | X | | | X | | | | X | | | | X | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | | | | X | | | | | X | | | X | | | | | | | X | X | | | | | | | X | | | | | X | X | X | | | | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 9 |  |  |  |  |  | X | | | | X | | | | | X | | | X | X | | | X | | | X | X | | | | | | | X | | | | | X | | | | | | X | | | | | | | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | |
| 8 | 6 |  |  |  |  |  | X | | | | X | | | X | | X | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | |
| 9 | 17 |  |  |  |  |  | X | | | | X | | | | | X | | | X | X | | | X | | | X | | | | X | | | | X | | | | | | | X | | | | X | | | | | | | | | | | X | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | | | | | | | |
| 10 | 13 |  |  |  |  |  | X | | | | X | | | X | | X | | | X | X | | | | | | X | | | | | | X | | X | | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X |
|
CyberHarem/kagerou_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T10:09:20+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T06:46:58+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kagerou/陽炎 (Kantai Collection)
=========================================
This is the dataset of kagerou/陽炎 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'brown\_hair, twintails, long\_hair, ribbon, ahoge, hair\_ribbon, purple\_eyes, green\_ribbon, neck\_ribbon, white\_ribbon, yellow\_ribbon', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
df5cdf9392c1f0fb56eac1c38fc1256426b24afe
|
# Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context
Libriheavy is a labeled version of [Librilight](https://github.com/facebookresearch/libri-light), read our [paper](https://arxiv.org/abs/2309.08105) for more details.
See https://github.com/k2-fsa/libriheavy for more details.
## Citation
```
@misc{kang2023libriheavy,
title={Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context},
author={Wei Kang and Xiaoyu Yang and Zengwei Yao and Fangjun Kuang and Yifan Yang and Liyong Guo and Long Lin and Daniel Povey},
year={2023},
eprint={2309.08105},
archivePrefix={arXiv},
primaryClass={eess.AS}
}
```
|
pkufool/libriheavy
|
[
"license:apache-2.0",
"arxiv:2309.08105",
"region:us"
] |
2023-08-21T10:20:42+00:00
|
{"license": "apache-2.0"}
|
2023-09-19T10:35:45+00:00
|
[
"2309.08105"
] |
[] |
TAGS
#license-apache-2.0 #arxiv-2309.08105 #region-us
|
# Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context
Libriheavy is a labeled version of Librilight, read our paper for more details.
See URL for more details.
|
[
"# Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context\n\nLibriheavy is a labeled version of Librilight, read our paper for more details.\n\nSee URL for more details."
] |
[
"TAGS\n#license-apache-2.0 #arxiv-2309.08105 #region-us \n",
"# Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context\n\nLibriheavy is a labeled version of Librilight, read our paper for more details.\n\nSee URL for more details."
] |
[
22,
45
] |
[
"passage: TAGS\n#license-apache-2.0 #arxiv-2309.08105 #region-us \n# Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context\n\nLibriheavy is a labeled version of Librilight, read our paper for more details.\n\nSee URL for more details."
] |
de54630cc6fdecd97e48ce30644c080d3be026a8
|
# Dataset of kamoi/神威 (Kantai Collection)
This is the dataset of kamoi/神威 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `headband, long_hair, folded_ponytail, blue_eyes, white_hair, breasts, sidelocks, large_breasts, thick_eyebrows, hair_between_eyes`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 571.44 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamoi_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 348.17 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamoi_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1189 | 736.93 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamoi_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 516.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamoi_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1189 | 994.21 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kamoi_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/kamoi_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 5 |  |  |  |  |  | 1girl, ainu_clothes, bandana, cowboy_shot, cropped_jacket, long_sleeves, looking_at_viewer, pelvic_curtain, sideboob, simple_background, sleeveless_dress, solo, white_dress, wrist_guards, black_thighhighs, blush, white_background, chain, grey_background, smile |
| 1 | 5 |  |  |  |  |  | 1girl, ainu_clothes, bandana, black_thighhighs, cropped_jacket, long_sleeves, open_mouth, sideboob, sleeveless_dress, solo, white_dress, wrist_guards, blush, looking_at_viewer, pelvic_curtain, sitting, blue_headband |
| 2 | 11 |  |  |  |  |  | 1girl, ainu_clothes, ass, long_sleeves, looking_at_viewer, sideboob, blush, cropped_jacket, looking_back, simple_background, solo, wrist_guards, black_thighhighs, white_background, white_panties, fundoshi, white_dress, from_behind, sleeveless_dress, bandana, cowboy_shot, open_mouth |
| 3 | 6 |  |  |  |  |  | 1girl, ainu_clothes, blush, long_sleeves, looking_at_viewer, pelvic_curtain, sideboob, simple_background, solo, white_background, white_dress, side-tie_panties, smile, white_panties, black_thighhighs, cropped_jacket, closed_mouth, covered_navel, cowboy_shot |
| 4 | 5 |  |  |  |  |  | 1girl, looking_at_viewer, solo, twitter_username, white_bikini, blue_headband, blush, simple_background, white_background, navel, open_mouth, cleavage, collarbone, cowboy_shot, eyepatch_bikini, grey_eyes, one-hour_drawing_challenge, upper_body |
| 5 | 14 |  |  |  |  |  | 1girl, hetero, 1boy, blush, open_mouth, penis, solo_focus, thighhighs, ainu_clothes, nipples, sex, vaginal, bar_censor, long_sleeves, clothing_aside, cropped_jacket, sweat, breasts_out, nude, cum_in_pussy, navel, panties, pubic_hair |
| 6 | 16 |  |  |  |  |  | 1girl, yukata, solo, hair_flower, blue_kimono, looking_at_viewer, alternate_costume, food, obi, open_mouth, striped_kimono, blush, corn, upper_body, white_background |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | ainu_clothes | bandana | cowboy_shot | cropped_jacket | long_sleeves | looking_at_viewer | pelvic_curtain | sideboob | simple_background | sleeveless_dress | solo | white_dress | wrist_guards | black_thighhighs | blush | white_background | chain | grey_background | smile | open_mouth | sitting | blue_headband | ass | looking_back | white_panties | fundoshi | from_behind | side-tie_panties | closed_mouth | covered_navel | twitter_username | white_bikini | navel | cleavage | collarbone | eyepatch_bikini | grey_eyes | one-hour_drawing_challenge | upper_body | hetero | 1boy | penis | solo_focus | thighhighs | nipples | sex | vaginal | bar_censor | clothing_aside | sweat | breasts_out | nude | cum_in_pussy | panties | pubic_hair | yukata | hair_flower | blue_kimono | alternate_costume | food | obi | striped_kimono | corn |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:----------|:--------------|:-----------------|:---------------|:--------------------|:-----------------|:-----------|:--------------------|:-------------------|:-------|:--------------|:---------------|:-------------------|:--------|:-------------------|:--------|:------------------|:--------|:-------------|:----------|:----------------|:------|:---------------|:----------------|:-----------|:--------------|:-------------------|:---------------|:----------------|:-------------------|:---------------|:--------|:-----------|:-------------|:------------------|:------------|:-----------------------------|:-------------|:---------|:-------|:--------|:-------------|:-------------|:----------|:------|:----------|:-------------|:-----------------|:--------|:--------------|:-------|:---------------|:----------|:-------------|:---------|:--------------|:--------------|:--------------------|:-------|:------|:-----------------|:-------|
| 0 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 5 |  |  |  |  |  | X | X | X | | X | X | X | X | X | | X | X | X | X | X | X | | | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 11 |  |  |  |  |  | X | X | X | X | X | X | X | | X | X | X | X | X | X | X | X | X | | | | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | X | | X | X | X | X | X | X | X | | X | X | | X | X | X | | | X | | | | | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 5 |  |  |  |  |  | X | | | X | | | X | | | X | | X | | | | X | X | | | | X | | X | | | | | | | | | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 14 |  |  |  |  |  | X | X | | | X | X | | | | | | | | | | X | | | | | X | | | | | | | | | | | | | X | | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | |
| 6 | 16 |  |  |  |  |  | X | | | | | | X | | | | | X | | | | X | X | | | | X | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X |
|
CyberHarem/kamoi_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T10:24:25+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T20:10:35+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of kamoi/神威 (Kantai Collection)
=======================================
This is the dataset of kamoi/神威 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'headband, long\_hair, folded\_ponytail, blue\_eyes, white\_hair, breasts, sidelocks, large\_breasts, thick\_eyebrows, hair\_between\_eyes', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
d47d3791671e4ff620f92f4ad3430654c9da4ef0
|
# 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]
|
raoulduke420/mattdilworth
|
[
"task_categories:image-classification",
"size_categories:n<1K",
"language:en",
"license:creativeml-openrail-m",
"man",
"region:us"
] |
2023-08-21T10:27:35+00:00
|
{"language": ["en"], "license": "creativeml-openrail-m", "size_categories": ["n<1K"], "task_categories": ["image-classification"], "pretty_name": "Matt Dilworth", "tags": ["man"]}
|
2023-08-21T10:44:52+00:00
|
[] |
[
"en"
] |
TAGS
#task_categories-image-classification #size_categories-n<1K #language-English #license-creativeml-openrail-m #man #region-us
|
# 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.
### Supported Tasks and Leaderboards
### Languages
## Dataset Structure
### Data Instances
### Data Fields
### Data Splits
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### 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 Card for Dataset Name",
"## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:",
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"### Supported Tasks and Leaderboards",
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] |
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"### Social Impact of Dataset",
"### Discussion of Biases",
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"## Additional Information",
"### Dataset Curators",
"### Licensing Information",
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"passage: TAGS\n#task_categories-image-classification #size_categories-n<1K #language-English #license-creativeml-openrail-m #man #region-us \n# Dataset Card for Dataset Name## Dataset Description\n\n- Homepage: \n- Repository: \n- Paper: \n- Leaderboard: \n- Point of Contact:### Dataset Summary\n\nThis dataset card aims to be a base template for new datasets. It has been generated using this raw template.### Supported Tasks and Leaderboards### Languages## Dataset Structure### Data Instances### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### 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"
] |
6a8640ad933231e6687918c541f0f51d2b59c0ee
|
# Dataset Card for "fw_squad_num_bi_train_10000_eval_100"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
tyzhu/fw_squad_num_bi_train_10000_eval_100
|
[
"region:us"
] |
2023-08-21T11:01:30+00:00
|
{"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "train_doc2id", "path": "data/train_doc2id-*"}, {"split": "train_id2doc", "path": "data/train_id2doc-*"}, {"split": "train_find_word", "path": "data/train_find_word-*"}, {"split": "eval_find_word", "path": "data/eval_find_word-*"}]}], "dataset_info": {"features": [{"name": "inputs", "dtype": "string"}, {"name": "targets", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 16281583, "num_examples": 30200}, {"name": "train_doc2id", "num_bytes": 7868014, "num_examples": 10100}, {"name": "train_id2doc", "num_bytes": 7898314, "num_examples": 10100}, {"name": "train_find_word", "num_bytes": 515255, "num_examples": 10000}, {"name": "eval_find_word", "num_bytes": 5268, "num_examples": 100}], "download_size": 20171340, "dataset_size": 32568434}}
|
2023-08-21T11:01:49+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "fw_squad_num_bi_train_10000_eval_100"
More Information needed
|
[
"# Dataset Card for \"fw_squad_num_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"fw_squad_num_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
[
6,
29
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[
"passage: TAGS\n#region-us \n# Dataset Card for \"fw_squad_num_bi_train_10000_eval_100\"\n\nMore Information needed"
] |
d7cc6c6db99a3148c4b78e387c3663227accc49a
|
# Dataset Card for "Immunology_Janeway"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
zxvix/Immunology_Janeway
|
[
"region:us"
] |
2023-08-21T11:03:54+00:00
|
{"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2915593, "num_examples": 5918}, {"name": "test", "num_bytes": 324049, "num_examples": 657}], "download_size": 1886821, "dataset_size": 3239642}}
|
2023-08-21T11:04:01+00:00
|
[] |
[] |
TAGS
#region-us
|
# Dataset Card for "Immunology_Janeway"
More Information needed
|
[
"# Dataset Card for \"Immunology_Janeway\"\n\nMore Information needed"
] |
[
"TAGS\n#region-us \n",
"# Dataset Card for \"Immunology_Janeway\"\n\nMore Information needed"
] |
[
6,
17
] |
[
"passage: TAGS\n#region-us \n# Dataset Card for \"Immunology_Janeway\"\n\nMore Information needed"
] |
933ff6f73ac3cb43218cddec973312edc2cf7bbd
|
# Dataset of hayasui/速吸/速吸 (Kantai Collection)
This is the dataset of hayasui/速吸/速吸 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are `short_hair, black_hair, grey_eyes, breasts`, which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by [DeepGHS Team](https://github.com/deepghs)([huggingface organization](https://huggingface.co/deepghs)).
## List of Packages
| Name | Images | Size | Download | Type | Description |
|:-----------------|---------:|:-----------|:--------------------------------------------------------------------------------------------------------------------------|:-----------|:---------------------------------------------------------------------|
| raw | 500 | 421.41 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayasui_kantaicollection/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 277.79 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayasui_kantaicollection/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1106 | 567.47 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayasui_kantaicollection/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 389.29 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayasui_kantaicollection/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1106 | 744.34 MiB | [Download](https://huggingface.co/datasets/CyberHarem/hayasui_kantaicollection/resolve/main/dataset-stage3-p480-1200.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for [waifuc](https://deepghs.github.io/waifuc/main/tutorials/installation/index.html) loading. If you need this, just run the following code
```python
import os
import zipfile
from huggingface_hub import hf_hub_download
from waifuc.source import LocalSource
# download raw archive file
zip_file = hf_hub_download(
repo_id='CyberHarem/hayasui_kantaicollection',
repo_type='dataset',
filename='dataset-raw.zip',
)
# extract files to your directory
dataset_dir = 'dataset_dir'
os.makedirs(dataset_dir, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zf:
zf.extractall(dataset_dir)
# load the dataset with waifuc
source = LocalSource(dataset_dir)
for item in source:
print(item.image, item.meta['filename'], item.meta['tags'])
```
## List of Clusters
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | Tags |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 8 |  |  |  |  |  | 1girl, long_sleeves, looking_at_viewer, smile, solo, track_jacket, upper_body, zipper, open_mouth, blue_eyes, twitter_username, white_jacket, white_background, hair_between_eyes, simple_background, turtleneck |
| 1 | 10 |  |  |  |  |  | 1girl, black_skirt, long_sleeves, looking_at_viewer, pleated_skirt, solo, track_jacket, zipper, miniskirt, open_mouth, blush, :d |
| 2 | 9 |  |  |  |  |  | 1girl, looking_at_viewer, simple_background, solo, track_jacket, open_mouth, pleated_skirt, white_background, black_skirt, miniskirt, smile, long_sleeves, bag |
| 3 | 6 |  |  |  |  |  | 1girl, black_skirt, gym_shirt, open_jacket, pleated_skirt, simple_background, solo, track_jacket, white_background, looking_at_viewer, miniskirt, blush, cowboy_shot, long_sleeves, white_shirt, hair_between_eyes, large_breasts, open_mouth, smile, zipper |
| 4 | 6 |  |  |  |  |  | 1girl, black_skirt, miniskirt, pleated_skirt, track_jacket, white_panties, long_sleeves, looking_at_viewer, pantyshot, solo, ass, open_mouth, standing, multiple_views, socks |
| 5 | 5 |  |  |  |  |  | 1girl, blush, gym_shirt, gym_uniform, looking_at_viewer, short_sleeves, solo, hair_between_eyes, open_mouth, red_buruma, simple_background, smile, sweat, white_shirt, large_breasts, twitter_username, white_background, blue_eyes, heart, navel |
| 6 | 6 |  |  |  |  |  | 1girl, black_skirt, hooded_sweater, hoodie, official_alternate_costume, grey_sweater, pleated_skirt, solo, holding, looking_at_viewer, open_mouth, alcohol, mug, sitting, smile |
| 7 | 6 |  |  |  |  |  | 1boy, 1girl, bar_censor, blush, hetero, penis, solo_focus, track_jacket, fellatio, brown_hair, cum |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | long_sleeves | looking_at_viewer | smile | solo | track_jacket | upper_body | zipper | open_mouth | blue_eyes | twitter_username | white_jacket | white_background | hair_between_eyes | simple_background | turtleneck | black_skirt | pleated_skirt | miniskirt | blush | :d | bag | gym_shirt | open_jacket | cowboy_shot | white_shirt | large_breasts | white_panties | pantyshot | ass | standing | multiple_views | socks | gym_uniform | short_sleeves | red_buruma | sweat | heart | navel | hooded_sweater | hoodie | official_alternate_costume | grey_sweater | holding | alcohol | mug | sitting | 1boy | bar_censor | hetero | penis | solo_focus | fellatio | brown_hair | cum |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:--------------------|:--------|:-------|:---------------|:-------------|:---------|:-------------|:------------|:-------------------|:---------------|:-------------------|:--------------------|:--------------------|:-------------|:--------------|:----------------|:------------|:--------|:-----|:------|:------------|:--------------|:--------------|:--------------|:----------------|:----------------|:------------|:------|:-----------|:-----------------|:--------|:--------------|:----------------|:-------------|:--------|:--------|:--------|:-----------------|:---------|:-----------------------------|:---------------|:----------|:----------|:------|:----------|:-------|:-------------|:---------|:--------|:-------------|:-----------|:-------------|:------|
| 0 | 8 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 10 |  |  |  |  |  | X | X | X | | X | X | | X | X | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 9 |  |  |  |  |  | X | X | X | X | X | X | | | X | | | | X | | X | | X | X | X | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | X | X | X | X | X | X | | X | X | | | | X | X | X | | X | X | X | X | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 6 |  |  |  |  |  | X | X | X | | X | X | | | X | | | | | | | | X | X | X | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 5 |  |  |  |  |  | X | | X | X | X | | | | X | X | X | | X | X | X | | | | | X | | | X | | | X | X | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | X | | X | X | X | | | | X | | | | | | | | X | X | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | |
| 7 | 6 |  |  |  |  |  | X | | | | | X | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X |
|
CyberHarem/hayasui_kantaicollection
|
[
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] |
2023-08-21T11:06:25+00:00
|
{"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]}
|
2024-01-15T18:18:23+00:00
|
[] |
[] |
TAGS
#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us
|
Dataset of hayasui/速吸/速吸 (Kantai Collection)
============================================
This is the dataset of hayasui/速吸/速吸 (Kantai Collection), containing 500 images and their tags.
The core tags of this character are 'short\_hair, black\_hair, grey\_eyes, breasts', which are pruned in this dataset.
Images are crawled from many sites (e.g. danbooru, pixiv, zerochan ...), the auto-crawling system is powered by DeepGHS Team(huggingface organization).
List of Packages
----------------
### Load Raw Dataset with Waifuc
We provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code
List of Clusters
----------------
List of tag clustering result, maybe some outfits can be mined here.
### Raw Text Version
### Table Version
|
[
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
"TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n",
"### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.",
"### Raw Text Version",
"### Table Version"
] |
[
44,
61,
5,
4
] |
[
"passage: TAGS\n#task_categories-text-to-image #size_categories-n<1K #license-mit #art #not-for-all-audiences #region-us \n### Load Raw Dataset with Waifuc\n\n\nWe provide raw dataset (including tagged images) for waifuc loading. If you need this, just run the following code\n\n\nList of Clusters\n----------------\n\n\nList of tag clustering result, maybe some outfits can be mined here.### Raw Text Version### Table Version"
] |
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