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a915d9bde3669589c28233e984a5389a666a848b | robopg/slot | [
"license:apache-2.0",
"region:us"
] | 2024-01-15T07:06:03+00:00 | {"license": "apache-2.0"} | 2024-01-15T07:06:03+00:00 |
|
092997d918804c8d8d45df2ca7ba20d56e041309 | bbokyeong/gen_data | [
"region:us"
] | 2024-01-15T07:17:26+00:00 | {} | 2024-01-15T07:18:35+00:00 |
|
0a43fbc3297a923a67c8c43f0a4f48619f20acf9 | latchuk/fabiow | [
"region:us"
] | 2024-01-15T07:18:39+00:00 | {} | 2024-01-15T07:19:06+00:00 |
|
f125808ce749c0f57851970723046d1581eef5ba |
# Dataset of tatari_kogasa/祟小傘 (Touhou)
This is the dataset of tatari_kogasa/祟小傘 (Touhou), containing 27 images and their tags.
The core tags of this character are `blue_hair, red_eyes, blue_eyes, heterochromia, breasts, short_hair, medium_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 | 27 | 25.34 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tatari_kogasa_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 27 | 16.34 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tatari_kogasa_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 52 | 30.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tatari_kogasa_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 27 | 22.84 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tatari_kogasa_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 52 | 40.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/tatari_kogasa_touhou/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/tatari_kogasa_touhou',
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, solo, nipples, blush, karakasa_obake, purple_umbrella, tongue, navel, panties, nude, open_clothes, pussy, shirt |
| 1 | 6 |  |  |  |  |  | 1girl, alternate_hair_length, long_hair, solo, dress, smile, aged_up, cleavage |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | nipples | blush | karakasa_obake | purple_umbrella | tongue | navel | panties | nude | open_clothes | pussy | shirt | alternate_hair_length | long_hair | dress | smile | aged_up | cleavage |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:----------|:--------|:-----------------|:------------------|:---------|:--------|:----------|:-------|:---------------|:--------|:--------|:------------------------|:------------|:--------|:--------|:----------|:-----------|
| 0 | 18 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | |
| 1 | 6 |  |  |  |  |  | X | X | | | | | | | | | | | | X | X | X | X | X | X |
| CyberHarem/tatari_kogasa_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T07:20:09+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T07:24:18+00:00 |
da2e99195bf44017d7c8c7d81570e1191fefbda6 | damojay/oas_tamil_from_eng | [
"region:us"
] | 2024-01-15T07:31:59+00:00 | {} | 2024-01-15T07:33:02+00:00 |
|
267eb4425b4d9ac37ba03d9c20de2b4e2f3736dd | HES-XPLAIN/SportsImageClassificationOld | [
"task_categories:image-classification",
"size_categories:100M<n<1B",
"language:en",
"sports",
"region:us"
] | 2024-01-15T07:32:08+00:00 | {"language": ["en"], "size_categories": ["100M<n<1B"], "task_categories": ["image-classification"], "tags": ["sports"]} | 2024-01-15T09:46:43+00:00 |
|
6d0622015e854d23c177f9619098424ede30b604 | alikli/code | [
"license:apache-2.0",
"region:us"
] | 2024-01-15T07:32:15+00:00 | {"license": "apache-2.0"} | 2024-01-15T08:08:39+00:00 |
|
6cbb9ea8172a6d7a81486df69665de7308913c8d | skinplaydata/skindiease | [
"license:unknown",
"region:us"
] | 2024-01-15T07:37:46+00:00 | {"license": "unknown"} | 2024-01-15T07:46:56+00:00 |
|
9c9867ca40b8d7dfcb96b555d05c3d48b1769d8c | yeajinmin/News-NER-dataset-ForKoGPT2 | [
"region:us"
] | 2024-01-15T07:43:56+00:00 | {"dataset_info": {"features": [{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}, {"name": "labels", "sequence": "int64"}], "splits": [{"name": "train", "num_bytes": 55688441.819743976, "num_examples": 120113}, {"name": "test", "num_bytes": 13922458.180256024, "num_examples": 30029}], "download_size": 17862664, "dataset_size": 69610900.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-15T07:44:15+00:00 |
|
9326c002c5d2380e2a3508f1f13d1867aae75a79 | qkrwnstj/cubism-journal | [
"region:us"
] | 2024-01-15T07:51:26+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 4452339.0, "num_examples": 20}], "download_size": 4429181, "dataset_size": 4452339.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T07:51:31+00:00 |
|
52c4ff1da157b3bdac76519fb8ec1c91c4a6a7ff | kamii/openslr_northernuk | [
"region:us"
] | 2024-01-15T08:00:33+00:00 | {} | 2024-01-15T09:00:01+00:00 |
|
cc0ffb66a1b325cbca08fb0021565ddb161de2d4 |
Dataset of URLs of articles on Zenn ([zenn.dev](https://zenn.dev/))
| p1atdev/zenn-articles-20240115 | [
"size_categories:10K<n<100K",
"language:ja",
"license:cc0-1.0",
"code",
"region:us"
] | 2024-01-15T08:03:26+00:00 | {"language": ["ja"], "license": "cc0-1.0", "size_categories": ["10K<n<100K"], "tags": ["code"]} | 2024-01-15T08:12:24+00:00 |
26469123750bf624a8f9b9613adda4b2652db396 | Atipico1/squad_v2_only_unanswerable | [
"region:us"
] | 2024-01-15T08:07:41+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answers", "sequence": [{"name": "text", "dtype": "string"}, {"name": "answer_start", "dtype": "int32"}]}], "splits": [{"name": "train", "num_bytes": 44644852.272898614, "num_examples": 49443}], "download_size": 6924554, "dataset_size": 44644852.272898614}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:07:47+00:00 |
|
83f162f482ae8aaf4ffa7cfbab0f22f7f7a7a584 | # Dataset Card for "bagel_sft_binarized"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | jan-hq/bagel_sft_binarized | [
"region:us"
] | 2024-01-15T08:09:40+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "messages", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 956516282.0643299, "num_examples": 562673}, {"name": "test", "num_bytes": 50344035.86689805, "num_examples": 29615}], "download_size": 628477131, "dataset_size": 1006860317.9312279}} | 2024-01-15T08:10:33+00:00 |
bd46b4a1f3076cda0ff81b0e9bc3b5e2d149a999 | fcolt99/combined_dataset | [
"region:us"
] | 2024-01-15T08:12:39+00:00 | {"dataset_info": {"features": [{"name": "message_id", "dtype": "string"}, {"name": "parent_id", "dtype": "string"}, {"name": "user_id", "dtype": "string"}, {"name": "created_date", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "role", "dtype": "string"}, {"name": "lang", "dtype": "string"}, {"name": "review_count", "dtype": "int64"}, {"name": "review_result", "dtype": "bool"}, {"name": "deleted", "dtype": "bool"}, {"name": "rank", "dtype": "float64"}, {"name": "synthetic", "dtype": "bool"}, {"name": "model_name", "dtype": "null"}, {"name": "detoxify", "struct": [{"name": "identity_attack", "dtype": "float64"}, {"name": "insult", "dtype": "float64"}, {"name": "obscene", "dtype": "float64"}, {"name": "severe_toxicity", "dtype": "float64"}, {"name": "sexual_explicit", "dtype": "float64"}, {"name": "threat", "dtype": "float64"}, {"name": "toxicity", "dtype": "float64"}]}, {"name": "message_tree_id", "dtype": "string"}, {"name": "tree_state", "dtype": "string"}, {"name": "emojis", "struct": [{"name": "count", "sequence": "int64"}, {"name": "name", "sequence": "string"}]}, {"name": "labels", "struct": [{"name": "count", "sequence": "int64"}, {"name": "name", "sequence": "string"}, {"name": "value", "sequence": "float64"}]}], "splits": [{"name": "train", "num_bytes": 87349400, "num_examples": 81037}, {"name": "validation", "num_bytes": 3267472, "num_examples": 3001}], "download_size": 31617744, "dataset_size": 90616872}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-15T08:12:44+00:00 |
|
dc887bb63699fd5c50a39d96eab315369303c107 | shrms/chart_dataset | [
"region:us"
] | 2024-01-15T08:14:14+00:00 | {"dataset_info": {"features": [{"name": "image_file", "dtype": "string"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 11391822, "num_examples": 38634}], "download_size": 3135404, "dataset_size": 11391822}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-16T04:59:38+00:00 |
|
95ad05a61d5f0a98103839cebb7908ed074d9696 | SoorajK1/sentiment_analysis_dataset-16c2d88a-9e71-49be-a846-443ea058041f | [
"region:us"
] | 2024-01-15T08:15:09+00:00 | {} | 2024-01-15T08:15:10+00:00 |
|
33fa43b90eb3365c9c9242f5b078ed6d15561624 | SoorajK1/sentiment_analysis_dataset-92f2ad6c-0376-4ce9-be36-3c6f26f144d7 | [
"region:us"
] | 2024-01-15T08:15:43+00:00 | {} | 2024-01-15T08:15:46+00:00 |
|
89d7187fae86a2aa035c3004d72b611f200eca28 | SoorajK1/sentiment_analysis_dataset-f1bf9ea2-9a69-4087-9fbd-967c243e9303 | [
"region:us"
] | 2024-01-15T08:16:32+00:00 | {} | 2024-01-15T11:26:47+00:00 |
|
2328abac558ea6143b12d7ab1fc68721348537c9 | HKUST-FYPHO2/audio-infos | [
"region:us"
] | 2024-01-15T08:18:50+00:00 | {"dataset_info": {"features": [{"name": "chords", "sequence": "int64"}, {"name": "chord_times", "sequence": "float64"}, {"name": "beats", "sequence": "float64"}, {"name": "downbeats", "sequence": "float64"}, {"name": "sample_rate", "dtype": "int64"}, {"name": "genre", "dtype": "string"}, {"name": "audio_name", "dtype": "string"}, {"name": "url", "dtype": "string"}, {"name": "playlist", "dtype": "string"}, {"name": "time_accessed", "dtype": "int64"}, {"name": "views", "dtype": "int64"}, {"name": "length", "dtype": "int64"}, {"name": "rating", "dtype": "string"}, {"name": "age_restricted", "dtype": "bool"}], "splits": [{"name": "train", "num_bytes": 10545532, "num_examples": 1495}], "download_size": 2617793, "dataset_size": 10545532}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:18:53+00:00 |
|
1e129f07e29f756dbc2039c0ad2e5de8bf8fbce8 |
# Dataset of orange (Touhou)
This is the dataset of orange (Touhou), containing 48 images and their tags.
The core tags of this character are `long_hair, red_hair, hat, red_eyes, bow, hair_bow, 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 | 48 | 27.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/orange_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 48 | 22.45 MiB | [Download](https://huggingface.co/datasets/CyberHarem/orange_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 76 | 36.10 MiB | [Download](https://huggingface.co/datasets/CyberHarem/orange_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 48 | 26.90 MiB | [Download](https://huggingface.co/datasets/CyberHarem/orange_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 76 | 41.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/orange_touhou/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/orange_touhou',
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 | 23 |  |  |  |  |  | 1girl, solo, puffy_short_sleeves, shirt, shoes, vest, white_bow, yellow_headwear, yellow_shorts, full_body, smile, holding, open_mouth, socks, looking_at_viewer, simple_background, white_background, white_footwear |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | puffy_short_sleeves | shirt | shoes | vest | white_bow | yellow_headwear | yellow_shorts | full_body | smile | holding | open_mouth | socks | looking_at_viewer | simple_background | white_background | white_footwear |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:----------------------|:--------|:--------|:-------|:------------|:------------------|:----------------|:------------|:--------|:----------|:-------------|:--------|:--------------------|:--------------------|:-------------------|:-----------------|
| 0 | 23 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| CyberHarem/orange_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T08:24:01+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T08:42:52+00:00 |
7aa94d4524a53130cd19fd5e583f6ea521a28b17 |
# Dataset of nishida_satono/里乃爾子田 (Touhou)
This is the dataset of nishida_satono/里乃爾子田 (Touhou), containing 315 images and their tags.
The core tags of this character are `brown_hair, hat, black_headwear, bangs, bow, purple_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 | 315 | 249.33 MiB | [Download](https://huggingface.co/datasets/CyberHarem/nishida_satono_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 315 | 181.19 MiB | [Download](https://huggingface.co/datasets/CyberHarem/nishida_satono_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 633 | 339.29 MiB | [Download](https://huggingface.co/datasets/CyberHarem/nishida_satono_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 315 | 233.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/nishida_satono_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 633 | 421.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/nishida_satono_touhou/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/nishida_satono_touhou',
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 |  |  |  |  |  | 2girls, pink_dress, puffy_short_sleeves, short_hair_with_long_locks, smile, green_dress, looking_at_viewer, tate_eboshi, waist_apron, green_hair, pink_eyes, solo_focus, bamboo, frills, white_apron, holding, purple_dress |
| 1 | 24 |  |  |  |  |  | 1girl, puffy_short_sleeves, short_hair_with_long_locks, solo, waist_apron, looking_at_viewer, pink_dress, smile, open_mouth, tate_eboshi, white_apron, pink_eyes, blush, breasts, holding |
| 2 | 42 |  |  |  |  |  | black_socks, short_hair_with_long_locks, pink_dress, looking_at_viewer, smile, tate_eboshi, waist_apron, 1girl, solo, kneehighs, pink_footwear, puffy_short_sleeves, holding, simple_background, full_body, mary_janes, white_background, open_mouth, purple_dress |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 2girls | pink_dress | puffy_short_sleeves | short_hair_with_long_locks | smile | green_dress | looking_at_viewer | tate_eboshi | waist_apron | green_hair | pink_eyes | solo_focus | bamboo | frills | white_apron | holding | purple_dress | 1girl | solo | open_mouth | blush | breasts | black_socks | kneehighs | pink_footwear | simple_background | full_body | mary_janes | white_background |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:---------|:-------------|:----------------------|:-----------------------------|:--------|:--------------|:--------------------|:--------------|:--------------|:-------------|:------------|:-------------|:---------|:---------|:--------------|:----------|:---------------|:--------|:-------|:-------------|:--------|:----------|:--------------|:------------|:----------------|:--------------------|:------------|:-------------|:-------------------|
| 0 | 9 |  |  |  |  |  | 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 | X | | | | | | | |
| 2 | 42 |  |  |  |  |  | | X | X | X | X | | X | X | X | | | | | | | X | X | X | X | X | | | X | X | X | X | X | X | X |
| CyberHarem/nishida_satono_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T08:24:20+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T09:37:38+00:00 |
ce741174523773288c10f675deb6e60df807db4b | anu111/coading | [
"size_categories:10K<n<100K",
"license:mit",
"code",
"region:us"
] | 2024-01-15T08:27:21+00:00 | {"license": "mit", "size_categories": ["10K<n<100K"], "tags": ["code"]} | 2024-01-15T08:28:47+00:00 |
|
3c769b0d306e6f5c4e4db753da785cab6c220d0d | A3KLFG/1232456 | [
"license:apache-2.0",
"region:us"
] | 2024-01-15T08:30:05+00:00 | {"license": "apache-2.0"} | 2024-01-15T08:30:05+00:00 |
|
01e92792c3226ca246e74e15e722bcd779fb473d | thanhtlx/fix-cmg-time-split-type-cluster-pdg | [
"license:apache-2.0",
"region:us"
] | 2024-01-15T08:32:54+00:00 | {"license": "apache-2.0"} | 2024-01-15T08:33:20+00:00 |
|
7d49f509fec1d8a6d35b1b808fcb064eea498918 | sarahahatee/lasl | [
"region:us"
] | 2024-01-15T08:33:25+00:00 | {} | 2024-01-15T08:38:48+00:00 |
|
8191416fe15d057e85f7414ac4b57008e9924f02 | presencesw/dataset1 | [
"region:us"
] | 2024-01-15T08:47:13+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 34776605, "num_examples": 13500}], "download_size": 21213166, "dataset_size": 34776605}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:47:20+00:00 |
|
67abee7e848453f2ce627ac7a1bea9dbb97a2141 | presencesw/dataset2 | [
"region:us"
] | 2024-01-15T08:47:21+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 34920701, "num_examples": 13500}], "download_size": 21314705, "dataset_size": 34920701}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:47:29+00:00 |
|
39318f8700ecdde3105827dd6c734f312efff131 | presencesw/dataset3 | [
"region:us"
] | 2024-01-15T08:47:30+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 23125707, "num_examples": 9000}], "download_size": 14110602, "dataset_size": 23125707}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:47:35+00:00 |
|
7de73d7e98b2505f788a274392ad18e4e70c3855 | presencesw/dataset4 | [
"region:us"
] | 2024-01-15T08:47:54+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 19516857, "num_examples": 7579}, {"name": "validation", "num_bytes": 2580228, "num_examples": 1000}, {"name": "test", "num_bytes": 1038094, "num_examples": 400}], "download_size": 14140459, "dataset_size": 23135179}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-15T08:48:03+00:00 |
|
d4acf71b760e73a269d93447ef2e56940595befd | ERROR: type should be string, got "\nhttps://huggingface.co/datasets/jkhedri/psychology-dataset\n\nthis but split for DPO and regular sft. for fun, nothing serious" | Sao10K/psychology-dataset-pairs | [
"region:us"
] | 2024-01-15T08:47:58+00:00 | {} | 2024-01-15T08:49:08+00:00 |
d79af07e969a6678fcbbe819956840425816468f | # Norwegian Courts
Parallel corpus of Nynorsk and Bokmål from Norwegian Court transcriptions.
The data originates from the [OPUS project](https://opus.nlpl.eu/ELRC-Courts_Norway-v1.php). | kardosdrur/norwegian-courts | [
"task_categories:sentence-similarity",
"language:nb",
"language:nn",
"license:mit",
"region:us"
] | 2024-01-15T08:50:13+00:00 | {"language": ["nb", "nn"], "license": "mit", "task_categories": ["sentence-similarity"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}], "dataset_info": {"features": [{"name": "nb", "dtype": "string"}, {"name": "nn", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 156464.72295514512, "num_examples": 909}, {"name": "test", "num_bytes": 39245.27704485488, "num_examples": 228}], "download_size": 120454, "dataset_size": 195710}} | 2024-01-15T08:53:19+00:00 |
ab2a02aade3b424ac193cb93dee93e23a87f442b | p1atdev/stackexchanges | [
"license:cc-by-sa-3.0",
"region:us"
] | 2024-01-15T08:54:03+00:00 | {"license": "cc-by-sa-3.0", "dataset_info": [{"config_name": "anime.stackexchange.com", "features": [{"name": "question", "struct": [{"name": "accepted_answer_id", "dtype": "string"}, {"name": "answer_count", "dtype": "int64"}, {"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "favorite_count", "dtype": "int64"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}, {"name": "title", "dtype": "string"}, {"name": "view_count", "dtype": "int64"}]}, {"name": "answers", "list": [{"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "parent_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}]}, {"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 32533359, "num_examples": 12318}], "download_size": 19104522, "dataset_size": 32533359}, {"config_name": "anime.stackexchange.com_simple", "features": [{"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "question_body", "dtype": "string"}, {"name": "question_score", "dtype": "int64"}, {"name": "accepted_answer_body", "dtype": "string"}, {"name": "accepted_answer_score", "dtype": "int64"}, {"name": "popular_answer_body", "dtype": "string"}, {"name": "popular_answer_score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 29800087, "num_examples": 12318}], "download_size": 18536497, "dataset_size": 29800087}, {"config_name": "default", "features": [{"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "question_body", "dtype": "string"}, {"name": "question_score", "dtype": "int64"}, {"name": "accepted_answer_body", "dtype": "string"}, {"name": "accepted_answer_score", "dtype": "int64"}, {"name": "popular_answer_body", "dtype": "string"}, {"name": "popular_answer_score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}], "splits": [{"name": "anime.stackexchange.com_simple", "num_bytes": 29800087, "num_examples": 12318}, {"name": "japanese.stackexchange.com_simple", "num_bytes": 67358026, "num_examples": 28850}, {"name": "ja.stackoverflow.com_simple", "num_bytes": 115174959, "num_examples": 30820}], "download_size": 117381584, "dataset_size": 212333072}, {"config_name": "ja.stackoverflow.com", "features": [{"name": "question", "struct": [{"name": "accepted_answer_id", "dtype": "string"}, {"name": "answer_count", "dtype": "int64"}, {"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "favorite_count", "dtype": "int64"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}, {"name": "title", "dtype": "string"}, {"name": "view_count", "dtype": "int64"}]}, {"name": "answers", "list": [{"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "parent_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}]}, {"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 114614992, "num_examples": 30820}], "download_size": 55495217, "dataset_size": 114614992}, {"config_name": "ja.stackoverflow.com_simple", "features": [{"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "question_body", "dtype": "string"}, {"name": "question_score", "dtype": "int64"}, {"name": "accepted_answer_body", "dtype": "string"}, {"name": "accepted_answer_score", "dtype": "int64"}, {"name": "popular_answer_body", "dtype": "string"}, {"name": "popular_answer_score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 115174959, "num_examples": 30820}], "download_size": 57385116, "dataset_size": 115174959}, {"config_name": "japanese.stackexchange.com", "features": [{"name": "question", "struct": [{"name": "accepted_answer_id", "dtype": "string"}, {"name": "answer_count", "dtype": "int64"}, {"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "favorite_count", "dtype": "int64"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}, {"name": "title", "dtype": "string"}, {"name": "view_count", "dtype": "int64"}]}, {"name": "answers", "list": [{"name": "body", "dtype": "string"}, {"name": "comment_count", "dtype": "int64"}, {"name": "content_license", "dtype": "string"}, {"name": "creation_date", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "last_activity_date", "dtype": "string"}, {"name": "last_edit_date", "dtype": "string"}, {"name": "last_editor_user_id", "dtype": "string"}, {"name": "owner_user_id", "dtype": "string"}, {"name": "parent_id", "dtype": "string"}, {"name": "post_type", "dtype": "string"}, {"name": "score", "dtype": "int64"}]}, {"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 68978827, "num_examples": 28850}], "download_size": 39676257, "dataset_size": 68978827}, {"config_name": "japanese.stackexchange.com_simple", "features": [{"name": "id", "dtype": "string"}, {"name": "accepted_answer_id", "dtype": "string"}, {"name": "popular_answer_id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "question_body", "dtype": "string"}, {"name": "question_score", "dtype": "int64"}, {"name": "accepted_answer_body", "dtype": "string"}, {"name": "accepted_answer_score", "dtype": "int64"}, {"name": "popular_answer_body", "dtype": "string"}, {"name": "popular_answer_score", "dtype": "int64"}, {"name": "tags", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 67358026, "num_examples": 28850}], "download_size": 41459971, "dataset_size": 67358026}], "configs": [{"config_name": "anime.stackexchange.com", "data_files": [{"split": "train", "path": "anime.stackexchange.com/train-*"}]}, {"config_name": "anime.stackexchange.com_simple", "data_files": [{"split": "train", "path": "anime.stackexchange.com_simple/train-*"}]}, {"config_name": "default", "data_files": [{"split": "anime.stackexchange.com_simple", "path": "data/anime.stackexchange.com_simple-*"}, {"split": "japanese.stackexchange.com_simple", "path": "data/japanese.stackexchange.com_simple-*"}, {"split": "ja.stackoverflow.com_simple", "path": "data/ja.stackoverflow.com_simple-*"}]}, {"config_name": "ja.stackoverflow.com", "data_files": [{"split": "train", "path": "ja.stackoverflow.com/train-*"}]}, {"config_name": "ja.stackoverflow.com_simple", "data_files": [{"split": "train", "path": "ja.stackoverflow.com_simple/train-*"}]}, {"config_name": "japanese.stackexchange.com", "data_files": [{"split": "train", "path": "japanese.stackexchange.com/train-*"}]}, {"config_name": "japanese.stackexchange.com_simple", "data_files": [{"split": "train", "path": "japanese.stackexchange.com_simple/train-*"}]}]} | 2024-01-15T09:08:08+00:00 |
|
7b210db79e304bc583b7779a0f94fbfa190139b2 | Atipico1/squad_v2_unique_questions | [
"region:us"
] | 2024-01-15T08:54:29+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answers", "sequence": [{"name": "text", "dtype": "string"}, {"name": "answer_start", "dtype": "int32"}]}, {"name": "masked_query", "dtype": "string"}, {"name": "query_embedding", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 190748153, "num_examples": 47491}], "download_size": 184171177, "dataset_size": 190748153}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T08:54:48+00:00 |
|
afba34367a8609a1d0044eded531548ab71a58cf |
<h1 align="center"> Executable Code Actions Elicit Better LLM Agents </h1>
<p align="center">
<a href="https://github.com/xingyaoww/code-act">💻 Code</a>
•
<a href="https://arxiv.org/abs/2402.01030">📃 Paper</a>
•
<a href="https://huggingface.co/datasets/xingyaoww/code-act" >🤗 Data (CodeActInstruct)</a>
•
<a href="https://huggingface.co/xingyaoww/CodeActAgent-Mistral-7b-v0.1" >🤗 Model (CodeActAgent-Mistral-7b-v0.1)</a>
•
<a href="https://chat.xwang.dev/">🤖 Chat with CodeActAgent!</a>
</p>
We propose to use executable Python **code** to consolidate LLM agents’ **act**ions into a unified action space (**CodeAct**).
Integrated with a Python interpreter, CodeAct can execute code actions and dynamically revise prior actions or emit new actions upon new observations (e.g., code execution results) through multi-turn interactions.
## Why CodeAct?
Our extensive analysis of 17 LLMs on API-Bank and a newly curated benchmark [M<sup>3</sup>ToolEval](docs/EVALUATION.md) shows that CodeAct outperforms widely used alternatives like Text and JSON (up to 20% higher success rate). Please check our paper for more detailed analysis!
*Comparison between CodeAct and Text / JSON as action.*
*Quantitative results comparing CodeAct and {Text, JSON} on M<sup>3</sup>ToolEval.*
## 📁 CodeActInstruct
We collect an instruction-tuning dataset CodeActInstruct that consists of 7k multi-turn interactions using CodeAct. Dataset is release at [huggingface dataset 🤗](https://huggingface.co/datasets/xingyaoww/code-act). Please refer to the paper and [this section](#-data-generation-optional) for details of data collection.
*Dataset Statistics. Token statistics are computed using Llama-2 tokenizer.*
## 🪄 CodeActAgent
Trained on **CodeActInstruct** and general conversaions, **CodeActAgent** excels at out-of-domain agent tasks compared to open-source models of the same size, while not sacrificing generic performance (e.g., knowledge, dialog). We release two variants of CodeActAgent:
- **CodeActAgent-Mistral-7b-v0.1** (recommended, [model link](https://huggingface.co/xingyaoww/CodeActAgent-Mistral-7b-v0.1)): using Mistral-7b-v0.1 as the base model with 32k context window.
- **CodeActAgent-Llama-7b** ([model link](https://huggingface.co/xingyaoww/CodeActAgent-Llama-2-7b)): using Llama-2-7b as the base model with 4k context window.
*Evaluation results for CodeActAgent. ID and OD stand for in-domain and out-of-domain evaluation correspondingly. Overall averaged performance normalizes the MT-Bench score to be consistent with other tasks and excludes in-domain tasks for fair comparison.*
Please check out [our paper](TODO) and [code](https://github.com/xingyaoww/code-act) for more details about data collection, model training, and evaluation.
## 📚 Citation
```bibtex
@misc{wang2024executable,
title={Executable Code Actions Elicit Better LLM Agents},
author={Xingyao Wang and Yangyi Chen and Lifan Yuan and Yizhe Zhang and Yunzhu Li and Hao Peng and Heng Ji},
year={2024},
eprint={2402.01030},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
| xingyaoww/code-act | [
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:en",
"license:apache-2.0",
"llm-agent",
"llm",
"instruction-tuning",
"arxiv:2402.01030",
"region:us"
] | 2024-01-15T08:59:02+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["1K<n<10K"], "task_categories": ["text-generation"], "configs": [{"config_name": "default", "data_files": [{"split": "codeact", "path": "data/codeact-*"}, {"split": "general", "path": "data/general-*"}]}], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "conversations", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}], "splits": [{"name": "codeact", "num_bytes": 34936511, "num_examples": 7139}, {"name": "general", "num_bytes": 250817144, "num_examples": 71246}], "download_size": 123084833, "dataset_size": 285753655}, "tags": ["llm-agent", "llm", "instruction-tuning"]} | 2024-02-05T05:23:24+00:00 |
3eaf866e383514ca3c63c15c32f276676094e8a8 | PPPAAAA/montage | [
"region:us"
] | 2024-01-15T09:10:51+00:00 | {} | 2024-01-15T09:10:51+00:00 |
|
169cb70b431ba0a1a86896af354cdc3e8f3c4dbc | nirantk/dbpedia-entities-mistral-embeddings-100K | [
"region:us"
] | 2024-01-15T09:15:47+00:00 | {"dataset_info": {"features": [{"name": "_id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "combined_text", "dtype": "string"}, {"name": "embedding", "sequence": "float64"}], "splits": [{"name": "train", "num_bytes": 893578748, "num_examples": 100000}], "download_size": 252132402, "dataset_size": 893578748}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T09:41:12+00:00 |
|
b5977f5cb476c4c18f6dc4025aa8900138c750fc | # Dataset Card for "VIVOS_CommonVoice_FOSD_NoiseControl_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | tuanmanh28/VIVOS_CommonVoice_FOSD_NoiseControl_dataset | [
"region:us"
] | 2024-01-15T09:16:58+00:00 | {"dataset_info": {"features": [{"name": "audio", "dtype": {"audio": {"sampling_rate": 16000}}}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2741051024.0, "num_examples": 39585}, {"name": "test", "num_bytes": 249790491.52, "num_examples": 5108}], "download_size": 2921057376, "dataset_size": 2990841515.52}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-15T09:18:34+00:00 |
53d14e1631b3d299bf144921b42089dd2c2cfd7c | ShreeyaVenneti/50entries_Whisper_GT_AverageCSR_CSR_AS_REFERENCE | [
"region:us"
] | 2024-01-15T09:18:04+00:00 | {} | 2024-01-15T09:18:19+00:00 |
|
f3fb708fee2352a6643c3a81140ad2493c072a98 |
# Dataset of ebisu_eika (Touhou)
This is the dataset of ebisu_eika (Touhou), containing 132 images and their tags.
The core tags of this character are `bangs, long_hair, red_eyes, blonde_hair`, 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 | 132 | 122.76 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ebisu_eika_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 132 | 81.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ebisu_eika_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 266 | 155.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ebisu_eika_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 132 | 112.74 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ebisu_eika_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 266 | 196.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/ebisu_eika_touhou/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/ebisu_eika_touhou',
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, barefoot, frilled_shirt, frilled_skirt, full_body, long_earlobes, looking_at_viewer, puffy_short_sleeves, skirt_set, solo, white_shirt, white_skirt, blouse, brown_eyes, rock, simple_background, sitting, stone, white_background, dark-skinned_female, open_mouth, toes, :d, blush_stickers, feet, medium_hair |
| 1 | 5 |  |  |  |  |  | 1girl, long_earlobes, open_mouth, puffy_short_sleeves, solo, white_shirt, frilled_shirt, looking_at_viewer, rock, stone, white_skirt, :d, blush, holding, jellyfish, skirt_set, upper_body |
| 2 | 5 |  |  |  |  |  | 1girl, long_earlobes, puffy_short_sleeves, solo, upper_body, dress, open_mouth, simple_background, white_shirt, looking_at_viewer, white_background, blush_stickers, brown_eyes, grey_hair |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | barefoot | frilled_shirt | frilled_skirt | full_body | long_earlobes | looking_at_viewer | puffy_short_sleeves | skirt_set | solo | white_shirt | white_skirt | blouse | brown_eyes | rock | simple_background | sitting | stone | white_background | dark-skinned_female | open_mouth | toes | :d | blush_stickers | feet | medium_hair | blush | holding | jellyfish | upper_body | dress | grey_hair |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-----------|:----------------|:----------------|:------------|:----------------|:--------------------|:----------------------|:------------|:-------|:--------------|:--------------|:---------|:-------------|:-------|:--------------------|:----------|:--------|:-------------------|:----------------------|:-------------|:-------|:-----|:-----------------|:-------|:--------------|:--------|:----------|:------------|:-------------|:--------|:------------|
| 0 | 8 |  |  |  |  |  | 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 | | | | | | |
| 1 | 5 |  |  |  |  |  | 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 |
| CyberHarem/ebisu_eika_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T09:19:19+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T09:46:59+00:00 |
e9520a30715abd039dcdac1a0c1a51337da61fef |
# Dataset of meira (Touhou)
This is the dataset of meira (Touhou), containing 77 images and their tags.
The core tags of this character are `purple_hair, ponytail, long_hair, purple_eyes, ribbon, hair_ribbon, bangs`, 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 | 77 | 63.34 MiB | [Download](https://huggingface.co/datasets/CyberHarem/meira_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 77 | 43.56 MiB | [Download](https://huggingface.co/datasets/CyberHarem/meira_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 136 | 75.45 MiB | [Download](https://huggingface.co/datasets/CyberHarem/meira_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 77 | 58.72 MiB | [Download](https://huggingface.co/datasets/CyberHarem/meira_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 136 | 98.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/meira_touhou/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/meira_touhou',
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 | 30 |  |  |  |  |  | 1girl, katana, japanese_clothes, solo, sheath |
| 1 | 11 |  |  |  |  |  | 1girl, holding_sword, katana, long_sleeves, looking_at_viewer, solo, wide_sleeves, white_ribbon, closed_mouth, pants, simple_background, very_long_hair, white_background, white_kimono, full_body, hakama, sheath |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | katana | japanese_clothes | solo | sheath | holding_sword | long_sleeves | looking_at_viewer | wide_sleeves | white_ribbon | closed_mouth | pants | simple_background | very_long_hair | white_background | white_kimono | full_body | hakama |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------|:-------------------|:-------|:---------|:----------------|:---------------|:--------------------|:---------------|:---------------|:---------------|:--------|:--------------------|:-----------------|:-------------------|:---------------|:------------|:---------|
| 0 | 30 |  |  |  |  |  | X | X | X | X | X | | | | | | | | | | | | | |
| 1 | 11 |  |  |  |  |  | X | X | | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| CyberHarem/meira_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T09:19:21+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T09:41:58+00:00 |
1948f55622b3dc317904c02ae6aa8555c7312fc2 | ShreeyaVenneti/50entries_regression_AverageCSR_CSR_AS_REFERENCE | [
"region:us"
] | 2024-01-15T09:23:41+00:00 | {} | 2024-01-15T09:23:56+00:00 |
|
269154dc31b124335622cb0a37c38a0a878940b3 | # Dataset Card for "myriade_ontologie"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | gguichard/myriade_ontologie | [
"region:us"
] | 2024-01-15T09:26:57+00:00 | {"dataset_info": {"features": [{"name": "tokens", "sequence": "string"}, {"name": "wn_sens", "sequence": "int64"}, {"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}, {"name": "labels", "sequence": "int64"}], "splits": [{"name": "train", "num_bytes": 13863915, "num_examples": 43590}], "download_size": 0, "dataset_size": 13863915}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-23T08:03:15+00:00 |
f962690d562f21428279f11094b81ec32fd5f4e0 |
# ShareGPT4 Dataset
ShareGPT4 is a cleaned version of the OpenChat-ShareGPT4 Dataset, designed for training conversational AI models. This dataset contains a collection of conversations, with each conversation consisting of two main features: role and value.
## Dataset Info
- **Features**:
- **conversations**:
- **role** (string): The role of the speaker in the conversation.
- **value** (string): The actual conversation text.
- **Splits**:
- **train**:
- Number of examples: 6144
- Size: 30,322,763 bytes
- **Download Size**: 15,605,374 bytes
- **Dataset Size**: 30,322,763 bytes
## Configs
- **Config Name**: default
- **Data Files**:
- **split**: train
- **path**: data/train-*
For more information on how to use this dataset with the Hugging Face library, please refer to their documentation. | erfanzar/ShareGPT4 | [
"region:us"
] | 2024-01-15T09:30:01+00:00 | {"dataset_info": {"features": [{"name": "conversations", "list": [{"name": "role", "dtype": "string"}, {"name": "value", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 30322763, "num_examples": 6144}], "download_size": 15605374, "dataset_size": 30322763}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-18T17:52:38+00:00 |
a5a26c8bf7c36ccb0870e9bb94474c021fcfd757 | # Dataset Card for "VietnameseNewsparquet"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | tmnam20/Vietnamese-News | [
"region:us"
] | 2024-01-15T09:30:14+00:00 | {"dataset_info": [{"config_name": "all", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 23505962013, "num_examples": 2421826}], "download_size": 10986340753, "dataset_size": 23505962013}, {"config_name": "baochinhphu", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 733982734, "num_examples": 58400}], "download_size": 312699305, "dataset_size": 733982734}, {"config_name": "dantri", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1265117393, "num_examples": 100396}], "download_size": 551235606, "dataset_size": 1265117393}, {"config_name": "laodong", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2939780592, "num_examples": 392668}], "download_size": 0, "dataset_size": 2939780592}, {"config_name": "qdnd", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2731532774, "num_examples": 259691}], "download_size": 0, "dataset_size": 2731532774}, {"config_name": "vietnamnet", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 14103390400, "num_examples": 1444898}], "download_size": 6773926864, "dataset_size": 14103390400}, {"config_name": "vnexpress", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1235989143, "num_examples": 133438}], "download_size": 537754843, "dataset_size": 1235989143}, {"config_name": "vtc", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 230258605, "num_examples": 10440}], "download_size": 66975140, "dataset_size": 230258605}, {"config_name": "zingnews", "features": [{"name": "title", "dtype": "string"}, {"name": "description", "dtype": "string"}, {"name": "content", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "url", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 265910372, "num_examples": 21895}], "download_size": 124252870, "dataset_size": 265910372}], "configs": [{"config_name": "all", "data_files": [{"split": "train", "path": "all/train-*"}]}, {"config_name": "baochinhphu", "data_files": [{"split": "train", "path": "baochinhphu/train-*"}]}, {"config_name": "dantri", "data_files": [{"split": "train", "path": "dantri/train-*"}]}, {"config_name": "laodong", "data_files": [{"split": "train", "path": "laodong/train-*"}]}, {"config_name": "qdnd", "data_files": [{"split": "train", "path": "qdnd/train-*"}]}, {"config_name": "vietnamnet", "data_files": [{"split": "train", "path": "vietnamnet/train-*"}]}, {"config_name": "vnexpress", "data_files": [{"split": "train", "path": "vnexpress/train-*"}]}, {"config_name": "vtc", "data_files": [{"split": "train", "path": "vtc/train-*"}]}, {"config_name": "zingnews", "data_files": [{"split": "train", "path": "zingnews/train-*"}]}]} | 2024-01-16T06:48:40+00:00 |
938c5e7aef57803acebbadf8f24809e077d5b5dc | shing3232/imatrix | [
"region:us"
] | 2024-01-15T09:30:26+00:00 | {} | 2024-01-15T09:32:25+00:00 |
|
2ffe82b0092c705c8354e798eb120c427927c8d5 | yuekai/aishell_whisper_large_v3_fbank_lhotse | [
"region:us"
] | 2024-01-15T09:31:23+00:00 | {} | 2024-01-15T09:39:32+00:00 |
|
6b143af444900f125e011165f2dbebcd669027b9 |
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | abhika-m/fava-flagged-demo | [
"region:us"
] | 2024-01-15T09:31:53+00:00 | {"configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data.csv"}]}]} | 2024-02-17T14:07:32+00:00 |
565bd237380654d23cc18caaa1a71cee73160af2 | # Dataset Card for "quality_counter_512"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | AIRI-NLP/quality_counter_512 | [
"region:us"
] | 2024-01-15T09:32:22+00:00 | {"dataset_info": {"features": [{"name": "context", "dtype": "string"}, {"name": "word", "dtype": "string"}, {"name": "claim", "dtype": "string"}, {"name": "label", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 64206836, "num_examples": 2640}, {"name": "validation", "num_bytes": 18498688, "num_examples": 740}, {"name": "test", "num_bytes": 56239972, "num_examples": 2300}], "download_size": 4494295, "dataset_size": 138945496}} | 2024-01-15T09:32:29+00:00 |
114e50a43cb499815b64a397179421e1aa12c358 | picas9dan/ontobuiltenv_2024-01-15_17.31.44 | [
"region:us"
] | 2024-01-15T09:33:19+00:00 | {} | 2024-01-16T01:51:20+00:00 |
|
0cbf2e5facdbd3bb3b3b570d5946eeb5aca334df | presencesw/webglm_test_v2 | [
"region:us"
] | 2024-01-15T09:35:35+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}, {"name": "len", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 54302.7270474311, "num_examples": 21}, {"name": "validation", "num_bytes": 295057.992, "num_examples": 114}, {"name": "test", "num_bytes": 255117.03, "num_examples": 98}], "download_size": 575766, "dataset_size": 604477.7490474312}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-15T09:35:43+00:00 |
|
347eeb81381950b59ee372ee57cd02626b8f51c6 | joey1895/new02 | [
"license:apache-2.0",
"region:us"
] | 2024-01-15T09:43:13+00:00 | {"license": "apache-2.0"} | 2024-01-16T08:48:59+00:00 |
|
855b94e901261cbb536a1ef3f0e26c36f006b1b8 |
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
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#### Data Collection and Processing
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[More Information Needed]
#### Who are the source data producers?
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[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
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#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
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[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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[More Information Needed] | davanstrien/fake-gated-dataset | [
"region:us"
] | 2024-01-15T09:50:13+00:00 | {"extra_gated_prompt": "You agree to not use the dataset to conduct experiments that cause harm to human subjects.", "extra_gated_fields": {"Full Name": "text", "Email": "text", "Researcher Google Scholar Page": "text", "I understand that this Dataset and the videos are protected by copyrights": "checkbox", "I agree to use this dataset for non-commercial use ONLY": "checkbox"}} | 2024-01-15T09:54:14+00:00 |
96d1c80c8287041b2eb8eb1bcd3ac8b4883afa3e | presencesw/webglm_test_translated | [
"region:us"
] | 2024-01-15T09:56:47+00:00 | {"dataset_info": {"features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}, {"name": "references", "sequence": "string"}, {"name": "len", "dtype": "int64"}, {"name": "question_vi", "dtype": "string"}, {"name": "answer_vi", "dtype": "string"}, {"name": "references_vi", "sequence": "string"}], "splits": [{"name": "train", "num_bytes": 243843, "num_examples": 21}], "download_size": 152819, "dataset_size": 243843}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-15T10:34:40+00:00 |
|
8b433864320029658abfba4a7727849058336ecc | IveniumMarketing/map-marketo | [
"task_categories:text-generation",
"size_categories:n<1K",
"language:en",
"license:openrail",
"region:us"
] | 2024-01-15T10:02:50+00:00 | {"language": ["en"], "license": "openrail", "size_categories": ["n<1K"], "task_categories": ["text-generation"], "pretty_name": "map"} | 2024-01-15T10:16:01+00:00 |
|
396fc847240e2298d527e4e96bc521dbe0f49f9b | # Spanish Passage Retrieval
This repository provides data from https://mklab.iti.gr/results/spanish-passage-retrieval-dataset/ as a HF dataset.
The data is not present in the repository but is downloaded on the fly.
There is an S2S (retrieve passages/sentences that are marked as relevant) and an
S2P (retrieve documents that contain relevant passages/sentences) version of the retrieval task. The respective corpuses are called `'corpus.sentences'` and `'corpus.documents'`.
The qrel data is contained in `'qrels.s2s'` and `'qrels.s2p'`, which hold space-separated lists of relevant documents. | jinaai/spanish_passage_retrieval | [
"region:eu"
] | 2024-01-15T10:08:21+00:00 | {} | 2024-01-18T11:28:44+00:00 |
0d61a3eb2087c21f4f63f199bca5f225ddaf03ac | # TMMLU+ : Large scale traditional chinese massive multitask language understanding
<p align="center">
<img src="https://huggingface.co/datasets/ikala/tmmluplus/resolve/main/cover.png" alt="A close-up image of a neat paper note with a white background. The text 'TMMLU+' is written horizontally across the center of the note in bold, black. Join us to work in multimodal LLM : https://ikala.ai/recruit/" style="max-width: 400" width=400 />
</p>
We present TMMLU+, a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset featuring 66 subjects, ranging from elementary to professional level.
The TMMLU+ dataset is six times larger and contains more balanced subjects compared to its predecessor, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We have included benchmark results in TMMLU+ from closed-source models and 20 open-weight Chinese large language models, with parameters ranging from 1.8B to 72B. The benchmark results show that Traditional Chinese variants still lag behind those trained on major Simplified Chinese models.
```python
from datasets import load_dataset
task_list = [
'engineering_math', 'dentistry', 'traditional_chinese_medicine_clinical_medicine', 'clinical_psychology', 'technical', 'culinary_skills', 'mechanical', 'logic_reasoning', 'real_estate',
'general_principles_of_law', 'finance_banking', 'anti_money_laundering', 'ttqav2', 'marketing_management', 'business_management', 'organic_chemistry', 'advance_chemistry',
'physics', 'secondary_physics', 'human_behavior', 'national_protection', 'jce_humanities', 'politic_science', 'agriculture', 'official_document_management',
'financial_analysis', 'pharmacy', 'educational_psychology', 'statistics_and_machine_learning', 'management_accounting', 'introduction_to_law', 'computer_science', 'veterinary_pathology',
'accounting', 'fire_science', 'optometry', 'insurance_studies', 'pharmacology', 'taxation', 'trust_practice', 'geography_of_taiwan', 'physical_education', 'auditing', 'administrative_law',
'education_(profession_level)', 'economics', 'veterinary_pharmacology', 'nautical_science', 'occupational_therapy_for_psychological_disorders',
'basic_medical_science', 'macroeconomics', 'trade', 'chinese_language_and_literature', 'tve_design', 'junior_science_exam', 'junior_math_exam', 'junior_chinese_exam',
'junior_social_studies', 'tve_mathematics', 'tve_chinese_language', 'tve_natural_sciences', 'junior_chemistry', 'music', 'education', 'three_principles_of_people',
'taiwanese_hokkien',
'linear_algebra'
]
for task in task_list:
val = load_dataset('ZoneTwelve/tmmluplus', task)['validation']
dev = load_dataset('ZoneTwelve/tmmluplus', task)['train']
test = load_dataset('ZoneTwelve/tmmluplus', task)['test']
```
For each dataset split
```python
for row in test:
print(row)
break
>> Dataset({
features: ['question', 'A', 'B', 'C', 'D', 'answer'],
num_rows: 11
})
```
Statistic on all four categories : STEM, Social Science, Humanities, Other
| Category | Test | Dev | Validation |
|----------------------------------|-------|------|------------|
| STEM | 3458 | 70 | 385 |
| Social Sciences | 5958 | 90 | 665 |
| Humanities | 1763 | 35 | 197 |
| Other (Business, Health, Misc.) | 8939 | 135 | 995 |
| **Total** | 20118 | 330 | 2242 |
## Benchmark on direct prompting
| model | STEM | Social Science | Humanities | Other | Average |
|------------|------------|------------|------------|------------|------------|
| [Qwen/Qwen-72B](https://huggingface.co/Qwen/Qwen-72B) | 61.12 | 71.65 | 63.00 | 61.31 |64.27|
| gpt-4-0613 | 60.36 | 67.36 | 56.03 | 57.62 |60.34|
| [Qwen/Qwen-72B-Chat](https://huggingface.co/Qwen/Qwen-72B-Chat) | 55.15 | 66.20 | 55.65 | 57.19 |58.55|
| [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) | 46.94 | 56.69 | 49.43 | 48.81 |50.47|
| Gemini-pro | 45.38 | 57.29 | 48.80 | 48.21 |49.92|
| [01-ai/Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat) | 40.24 | 56.77 | 53.99 | 47.58 |49.64|
| [Qwen/Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat) | 43.86 | 53.29 | 44.78 | 45.13 |46.77|
| [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat) | 39.62 | 50.24 | 44.44 | 44.26 |44.64|
| Claude-1.3 | 42.65 | 49.33 | 42.16 | 44.14 |44.57|
| gpt-3.5-turbo-0613 | 41.56 | 46.72 | 36.73 | 42.03 |41.76|
| [CausalLM/14B](https://huggingface.co/CausalLM/14B) | 39.83 | 44.50 | 39.61 | 41.97 |41.48|
| [Skywork/Skywork-13B-base](https://huggingface.co/Skywork/Skywork-13B-base) | 36.93 | 47.27 | 41.04 | 40.10 |41.33|
| [Qwen/Qwen-7B](https://huggingface.co/Qwen/Qwen-7B) | 37.53 | 45.48 | 38.09 | 38.96 |40.01|
| [Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) | 33.32 | 44.64 | 40.27 | 39.89 |39.53|
| [vivo-ai/BlueLM-7B-Base](https://huggingface.co/vivo-ai/BlueLM-7B-Base) | 33.94 | 41.52 | 37.38 | 38.74 |37.90|
| [baichuan-inc/Baichuan2-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat) | 29.64 | 43.73 | 37.36 | 39.88 |37.65|
| [Qwen/Qwen-1_8B](https://huggingface.co/Qwen/Qwen-1_8B) | 32.65 | 38.95 | 38.34 | 35.27 |36.30|
| Claude-2 | 39.65 | 39.09 | 28.59 | 37.47 |36.20|
| [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) | 31.05 | 39.31 | 35.64 | 35.60 |35.40|
| [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat) | 29.82 | 42.29 | 34.24 | 34.31 |35.17|
| [CausalLM/7B](https://huggingface.co/CausalLM/7B) | 31.03 | 38.17 | 35.87 | 35.39 |35.11|
| [Azure99/blossom-v3_1-mistral-7b](https://huggingface.co/Azure99/blossom-v3_1-mistral-7b) | 32.80 | 36.91 | 32.36 | 34.53 |34.15|
| [microsoft/Orca-2-13b](https://huggingface.co/microsoft/Orca-2-13b) | 24.69 | 39.18 | 33.60 | 31.99 |32.37|
| [Qwen/Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat) | 26.60 | 36.36 | 31.81 | 31.96 |31.68|
| [TigerResearch/tigerbot-13b-chat-v3](https://huggingface.co/TigerResearch/tigerbot-13b-chat-v3) | 24.73 | 29.63 | 25.72 | 27.22 |26.82|
| [hongyin/mistral-7b-80k](https://huggingface.co/hongyin/mistral-7b-80k) | 24.26 | 23.76 | 22.56 | 24.57 |23.79|
| [deepseek-ai/deepseek-llm-67b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat) | 19.10 | 26.06 | 21.51 | 21.77 |22.11|
| [yentinglin/Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) | 18.53 | 27.65 | 17.77 | 21.49 |21.36|
| [GeneZC/MiniChat-3B](https://huggingface.co/GeneZC/MiniChat-3B) | 17.66 | 23.35 | 22.71 | 20.34 |21.02|
| [LinkSoul/Chinese-Llama-2-7b](https://huggingface.co/LinkSoul/Chinese-Llama-2-7b) | 16.55 | 18.39 | 12.97 | 16.13 |16.01|
| [yentinglin/Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) | 14.99 | 16.23 | 15.00 | 16.22 |15.61|
| Claude-instant-1 | 12.52 | 17.13 | 15.10 | 13.57 |14.58|
| [FlagAlpha/Atom-7B](https://huggingface.co/FlagAlpha/Atom-7B) | 5.60 | 13.57 | 7.71 | 11.84 |9.68|
Results via [ievals](https://github.com/iKala/ievals) ( settings : 0-shot direct answering )
# Citation
```
@article{ikala2023eval,
title={An Improved Traditional Chinese Evaluation Suite for Foundation Model},
author={Tam, Zhi-Rui and Pai, Ya-Ting},
journal={arXiv},
year={2023}
}
```
> CONTENT WARNING
> This is a modification of ikala/tmmluplus, with minor alterations made to facilitate the implementation for lm-evaluation-harness purposes.
> [More details on Discussions](https://huggingface.co/datasets/ZoneTwelve/tmmluplus/discussions/1) | ZoneTwelve/tmmluplus | [
"task_categories:question-answering",
"size_categories:100K<n<1M",
"language:zh",
"license:other",
"traditional chinese",
"finance",
"medical",
"taiwan",
"benchmark",
"zh-tw",
"zh-hant",
"region:us"
] | 2024-01-15T10:09:59+00:00 | {"language": ["zh"], "license": "other", "size_categories": ["100K<n<1M"], "task_categories": ["question-answering"], "pretty_name": "tmmlu++", "license_name": "creative-commons-by-nc", "tags": ["traditional chinese", "finance", "medical", "taiwan", "benchmark", "zh-tw", "zh-hant"], "configs": [{"config_name": "engineering_math", "datafiles": [{"split": "train", "path": "data/engineering_math_dev.csv"}, {"split": "validation", "path": "data/engineering_math_val.csv"}, {"split": "test", "path": "data/engineering_math_test.csv"}]}, {"config_name": "dentistry", "datafiles": [{"split": "train", "path": "data/dentistry_dev.csv"}, {"split": "validation", "path": "data/dentistry_val.csv"}, {"split": "test", "path": "data/dentistry_test.csv"}]}, {"config_name": "traditional_chinese_medicine_clinical_medicine", "datafiles": [{"split": "train", "path": "data/traditional_chinese_medicine_clinical_medicine_dev.csv"}, {"split": "validation", "path": "data/traditional_chinese_medicine_clinical_medicine_val.csv"}, {"split": "test", "path": "data/traditional_chinese_medicine_clinical_medicine_test.csv"}]}, {"config_name": "clinical_psychology", "datafiles": [{"split": "train", "path": "data/clinical_psychology_dev.csv"}, {"split": "validation", "path": "data/clinical_psychology_val.csv"}, {"split": "test", "path": "data/clinical_psychology_test.csv"}]}, {"config_name": "technical", "datafiles": [{"split": "train", "path": "data/technical_dev.csv"}, {"split": "validation", "path": "data/technical_val.csv"}, {"split": "test", "path": "data/technical_test.csv"}]}, {"config_name": "culinary_skills", "datafiles": [{"split": "train", "path": "data/culinary_skills_dev.csv"}, {"split": "validation", "path": "data/culinary_skills_val.csv"}, {"split": "test", "path": "data/culinary_skills_test.csv"}]}, {"config_name": "mechanical", "datafiles": [{"split": "train", "path": "data/mechanical_dev.csv"}, {"split": "validation", "path": "data/mechanical_val.csv"}, {"split": "test", "path": "data/mechanical_test.csv"}]}, {"config_name": "logic_reasoning", "datafiles": [{"split": "train", "path": "data/logic_reasoning_dev.csv"}, {"split": "validation", "path": "data/logic_reasoning_val.csv"}, {"split": "test", "path": "data/logic_reasoning_test.csv"}]}, {"config_name": "real_estate", "datafiles": [{"split": "train", "path": "data/real_estate_dev.csv"}, {"split": "validation", "path": "data/real_estate_val.csv"}, {"split": "test", "path": "data/real_estate_test.csv"}]}, {"config_name": "general_principles_of_law", "datafiles": [{"split": "train", "path": "data/general_principles_of_law_dev.csv"}, {"split": "validation", "path": "data/general_principles_of_law_val.csv"}, {"split": "test", "path": "data/general_principles_of_law_test.csv"}]}, {"config_name": "finance_banking", "datafiles": [{"split": "train", "path": "data/finance_banking_dev.csv"}, {"split": "validation", "path": "data/finance_banking_val.csv"}, {"split": "test", "path": "data/finance_banking_test.csv"}]}, {"config_name": "anti_money_laundering", "datafiles": [{"split": "train", "path": "data/anti_money_laundering_dev.csv"}, {"split": "validation", "path": "data/anti_money_laundering_val.csv"}, {"split": "test", "path": "data/anti_money_laundering_test.csv"}]}, {"config_name": "ttqav2", "datafiles": [{"split": "train", "path": "data/ttqav2_dev.csv"}, {"split": "validation", "path": "data/ttqav2_val.csv"}, {"split": "test", "path": "data/ttqav2_test.csv"}]}, {"config_name": "marketing_management", "datafiles": [{"split": "train", "path": "data/marketing_management_dev.csv"}, {"split": "validation", "path": "data/marketing_management_val.csv"}, {"split": "test", "path": "data/marketing_management_test.csv"}]}, {"config_name": "business_management", "datafiles": [{"split": "train", "path": "data/business_management_dev.csv"}, {"split": "validation", "path": "data/business_management_val.csv"}, {"split": "test", "path": "data/business_management_test.csv"}]}, {"config_name": "organic_chemistry", "datafiles": [{"split": "train", "path": "data/organic_chemistry_dev.csv"}, {"split": "validation", "path": "data/organic_chemistry_val.csv"}, {"split": "test", "path": "data/organic_chemistry_test.csv"}]}, {"config_name": "advance_chemistry", "datafiles": [{"split": "train", "path": "data/advance_chemistry_dev.csv"}, {"split": "validation", "path": "data/advance_chemistry_val.csv"}, {"split": "test", "path": "data/advance_chemistry_test.csv"}]}, {"config_name": "physics", "datafiles": [{"split": "train", "path": "data/physics_dev.csv"}, {"split": "validation", "path": "data/physics_val.csv"}, {"split": "test", "path": "data/physics_test.csv"}]}, {"config_name": "secondary_physics", "datafiles": [{"split": "train", "path": "data/secondary_physics_dev.csv"}, {"split": "validation", "path": "data/secondary_physics_val.csv"}, {"split": "test", "path": "data/secondary_physics_test.csv"}]}, {"config_name": "human_behavior", "datafiles": [{"split": "train", "path": "data/human_behavior_dev.csv"}, {"split": "validation", "path": "data/human_behavior_val.csv"}, {"split": "test", "path": "data/human_behavior_test.csv"}]}, {"config_name": "national_protection", "datafiles": [{"split": "train", "path": "data/national_protection_dev.csv"}, {"split": "validation", "path": "data/national_protection_val.csv"}, {"split": "test", "path": "data/national_protection_test.csv"}]}, {"config_name": "jce_humanities", "datafiles": [{"split": "train", "path": "data/jce_humanities_dev.csv"}, {"split": "validation", "path": "data/jce_humanities_val.csv"}, {"split": "test", "path": "data/jce_humanities_test.csv"}]}, {"config_name": "politic_science", "datafiles": [{"split": "train", "path": "data/politic_science_dev.csv"}, {"split": "validation", "path": "data/politic_science_val.csv"}, {"split": "test", "path": "data/politic_science_test.csv"}]}, {"config_name": "agriculture", "datafiles": [{"split": "train", "path": "data/agriculture_dev.csv"}, {"split": "validation", "path": "data/agriculture_val.csv"}, {"split": "test", "path": "data/agriculture_test.csv"}]}, {"config_name": "official_document_management", "datafiles": [{"split": "train", "path": "data/official_document_management_dev.csv"}, {"split": "validation", "path": "data/official_document_management_val.csv"}, {"split": "test", "path": "data/official_document_management_test.csv"}]}, {"config_name": "financial_analysis", "datafiles": [{"split": "train", "path": "data/financial_analysis_dev.csv"}, {"split": "validation", "path": "data/financial_analysis_val.csv"}, {"split": "test", "path": "data/financial_analysis_test.csv"}]}, {"config_name": "pharmacy", "datafiles": [{"split": "train", "path": "data/pharmacy_dev.csv"}, {"split": "validation", "path": "data/pharmacy_val.csv"}, {"split": "test", "path": "data/pharmacy_test.csv"}]}, {"config_name": "educational_psychology", "datafiles": [{"split": "train", "path": "data/educational_psychology_dev.csv"}, {"split": "validation", "path": "data/educational_psychology_val.csv"}, {"split": "test", "path": "data/educational_psychology_test.csv"}]}, {"config_name": "statistics_and_machine_learning", "datafiles": [{"split": "train", "path": "data/statistics_and_machine_learning_dev.csv"}, {"split": "validation", "path": "data/statistics_and_machine_learning_val.csv"}, {"split": "test", "path": "data/statistics_and_machine_learning_test.csv"}]}, {"config_name": "management_accounting", "datafiles": [{"split": "train", "path": "data/management_accounting_dev.csv"}, {"split": "validation", "path": "data/management_accounting_val.csv"}, {"split": "test", "path": "data/management_accounting_test.csv"}]}, {"config_name": "introduction_to_law", "datafiles": [{"split": "train", "path": "data/introduction_to_law_dev.csv"}, {"split": "validation", "path": "data/introduction_to_law_val.csv"}, {"split": "test", "path": "data/introduction_to_law_test.csv"}]}, {"config_name": "computer_science", "datafiles": [{"split": "train", "path": "data/computer_science_dev.csv"}, {"split": "validation", "path": "data/computer_science_val.csv"}, {"split": "test", "path": "data/computer_science_test.csv"}]}, {"config_name": "veterinary_pathology", "datafiles": [{"split": "train", "path": "data/veterinary_pathology_dev.csv"}, {"split": "validation", "path": "data/veterinary_pathology_val.csv"}, {"split": "test", "path": "data/veterinary_pathology_test.csv"}]}, {"config_name": "accounting", "datafiles": [{"split": "train", "path": "data/accounting_dev.csv"}, {"split": "validation", "path": "data/accounting_val.csv"}, {"split": "test", "path": "data/accounting_test.csv"}]}, {"config_name": "fire_science", "datafiles": [{"split": "train", "path": "data/fire_science_dev.csv"}, {"split": "validation", "path": "data/fire_science_val.csv"}, {"split": "test", "path": "data/fire_science_test.csv"}]}, {"config_name": "optometry", "datafiles": [{"split": "train", "path": "data/optometry_dev.csv"}, {"split": "validation", "path": "data/optometry_val.csv"}, {"split": "test", "path": "data/optometry_test.csv"}]}, {"config_name": "insurance_studies", "datafiles": [{"split": "train", "path": "data/insurance_studies_dev.csv"}, {"split": "validation", "path": "data/insurance_studies_val.csv"}, {"split": "test", "path": "data/insurance_studies_test.csv"}]}, {"config_name": "pharmacology", "datafiles": [{"split": "train", "path": "data/pharmacology_dev.csv"}, {"split": "validation", "path": "data/pharmacology_val.csv"}, {"split": "test", "path": "data/pharmacology_test.csv"}]}, {"config_name": "taxation", "datafiles": [{"split": "train", "path": "data/taxation_dev.csv"}, {"split": "validation", "path": "data/taxation_val.csv"}, {"split": "test", "path": "data/taxation_test.csv"}]}, {"config_name": "trust_practice", "datafiles": [{"split": "train", "path": "data/trust_practice_dev.csv"}, {"split": "validation", "path": "data/trust_practice_val.csv"}, {"split": "test", "path": "data/trust_practice_test.csv"}]}, {"config_name": "geography_of_taiwan", "datafiles": [{"split": "train", "path": "data/geography_of_taiwan_dev.csv"}, {"split": "validation", "path": "data/geography_of_taiwan_val.csv"}, {"split": "test", "path": "data/geography_of_taiwan_test.csv"}]}, {"config_name": "physical_education", "datafiles": [{"split": "train", "path": "data/physical_education_dev.csv"}, {"split": "validation", "path": "data/physical_education_val.csv"}, {"split": "test", "path": "data/physical_education_test.csv"}]}, {"config_name": "auditing", "datafiles": [{"split": "train", "path": "data/auditing_dev.csv"}, {"split": "validation", "path": "data/auditing_val.csv"}, {"split": "test", "path": "data/auditing_test.csv"}]}, {"config_name": "administrative_law", "datafiles": [{"split": "train", "path": "data/administrative_law_dev.csv"}, {"split": "validation", "path": "data/administrative_law_val.csv"}, {"split": "test", "path": "data/administrative_law_test.csv"}]}, {"config_name": "education_(profession_level)", "datafiles": [{"split": "train", "path": "data/education_(profession_level)_dev.csv"}, {"split": "validation", "path": "data/education_(profession_level)_val.csv"}, {"split": "test", "path": "data/education_(profession_level)_test.csv"}]}, {"config_name": "economics", "datafiles": [{"split": "train", "path": "data/economics_dev.csv"}, {"split": "validation", "path": "data/economics_val.csv"}, {"split": "test", "path": "data/economics_test.csv"}]}, {"config_name": "veterinary_pharmacology", "datafiles": [{"split": "train", "path": "data/veterinary_pharmacology_dev.csv"}, {"split": "validation", "path": "data/veterinary_pharmacology_val.csv"}, {"split": "test", "path": "data/veterinary_pharmacology_test.csv"}]}, {"config_name": "nautical_science", "datafiles": [{"split": "train", "path": "data/nautical_science_dev.csv"}, {"split": "validation", "path": "data/nautical_science_val.csv"}, {"split": "test", "path": "data/nautical_science_test.csv"}]}, {"config_name": "occupational_therapy_for_psychological_disorders", "datafiles": [{"split": "train", "path": "data/occupational_therapy_for_psychological_disorders_dev.csv"}, {"split": "validation", "path": "data/occupational_therapy_for_psychological_disorders_val.csv"}, {"split": "test", "path": "data/occupational_therapy_for_psychological_disorders_test.csv"}]}, {"config_name": "basic_medical_science", "datafiles": [{"split": "train", "path": "data/basic_medical_science_dev.csv"}, {"split": "validation", "path": "data/basic_medical_science_val.csv"}, {"split": "test", "path": "data/basic_medical_science_test.csv"}]}, {"config_name": "macroeconomics", "datafiles": [{"split": "train", "path": "data/macroeconomics_dev.csv"}, {"split": "validation", "path": "data/macroeconomics_val.csv"}, {"split": "test", "path": "data/macroeconomics_test.csv"}]}, {"config_name": "trade", "datafiles": [{"split": "train", "path": "data/trade_dev.csv"}, {"split": "validation", "path": "data/trade_val.csv"}, {"split": "test", "path": "data/trade_test.csv"}]}, {"config_name": "chinese_language_and_literature", "datafiles": [{"split": "train", "path": "data/chinese_language_and_literature_dev.csv"}, {"split": "validation", "path": "data/chinese_language_and_literature_val.csv"}, {"split": "test", "path": "data/chinese_language_and_literature_test.csv"}]}, {"config_name": "tve_design", "datafiles": [{"split": "train", "path": "data/tve_design_dev.csv"}, {"split": "validation", "path": "data/tve_design_val.csv"}, {"split": "test", "path": "data/tve_design_test.csv"}]}, {"config_name": "junior_science_exam", "datafiles": [{"split": "train", "path": "data/junior_science_exam_dev.csv"}, {"split": "validation", "path": "data/junior_science_exam_val.csv"}, {"split": "test", "path": "data/junior_science_exam_test.csv"}]}, {"config_name": "junior_math_exam", "datafiles": [{"split": "train", "path": "data/junior_math_exam_dev.csv"}, {"split": "validation", "path": "data/junior_math_exam_val.csv"}, {"split": "test", "path": "data/junior_math_exam_test.csv"}]}, {"config_name": "junior_chinese_exam", "datafiles": [{"split": "train", "path": "data/junior_chinese_exam_dev.csv"}, {"split": "validation", "path": "data/junior_chinese_exam_val.csv"}, {"split": "test", "path": "data/junior_chinese_exam_test.csv"}]}, {"config_name": "junior_social_studies", "datafiles": [{"split": "train", "path": "data/junior_social_studies_dev.csv"}, {"split": "validation", "path": "data/junior_social_studies_val.csv"}, {"split": "test", "path": "data/junior_social_studies_test.csv"}]}, {"config_name": "tve_mathematics", "datafiles": [{"split": "train", "path": "data/tve_mathematics_dev.csv"}, {"split": "validation", "path": "data/tve_mathematics_val.csv"}, {"split": "test", "path": "data/tve_mathematics_test.csv"}]}, {"config_name": "tve_chinese_language", "datafiles": [{"split": "train", "path": "data/tve_chinese_language_dev.csv"}, {"split": "validation", "path": "data/tve_chinese_language_val.csv"}, {"split": "test", "path": "data/tve_chinese_language_test.csv"}]}, {"config_name": "tve_natural_sciences", "datafiles": [{"split": "train", "path": "data/tve_natural_sciences_dev.csv"}, {"split": "validation", "path": "data/tve_natural_sciences_val.csv"}, {"split": "test", "path": "data/tve_natural_sciences_test.csv"}]}, {"config_name": "junior_chemistry", "datafiles": [{"split": "train", "path": "data/junior_chemistry_dev.csv"}, {"split": "validation", "path": "data/junior_chemistry_val.csv"}, {"split": "test", "path": "data/junior_chemistry_test.csv"}]}, {"config_name": "music", "datafiles": [{"split": "train", "path": "data/music_dev.csv"}, {"split": "validation", "path": "data/music_val.csv"}, {"split": "test", "path": "data/music_test.csv"}]}, {"config_name": "education", "datafiles": [{"split": "train", "path": "data/education_dev.csv"}, {"split": "validation", "path": "data/education_val.csv"}, {"split": "test", "path": "data/education_test.csv"}]}, {"config_name": "three_principles_of_people", "datafiles": [{"split": "train", "path": "data/three_principles_of_people_dev.csv"}, {"split": "validation", "path": "data/three_principles_of_people_val.csv"}, {"split": "test", "path": "data/three_principles_of_people_test.csv"}]}, {"config_name": "taiwanese_hokkien", "datafiles": [{"split": "train", "path": "data/taiwanese_hokkien_dev.csv"}, {"split": "validation", "path": "data/taiwanese_hokkien_val.csv"}, {"split": "test", "path": "data/taiwanese_hokkien_test.csv"}]}, {"config_name": "linear_algebra", "datafiles": [{"split": "train", "path": "data/linear_algebra_dev.csv"}, {"split": "validation", "path": "data/linear_algebra_val.csv"}, {"split": "test", "path": "data/linear_algebra_test.csv"}]}]} | 2024-01-19T08:10:20+00:00 |
7cba2dcc3a4d9c8bb3cdd23f8184c96534f82244 | baptistecolle/mc_training_data | [
"region:us"
] | 2024-01-15T10:16:17+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 12892848.386679526, "num_examples": 31728}, {"name": "test", "num_bytes": 1432809.6133204743, "num_examples": 3526}], "download_size": 8267846, "dataset_size": 14325658.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-15T11:02:23+00:00 |
|
2ac4957a00a4d5232ea390624a679d475f71c4f8 |
# Dataset of toutetsu_yuuma (Touhou)
This is the dataset of toutetsu_yuuma (Touhou), containing 20 images and their tags.
The core tags of this character are `horns, red_eyes, ribbon, earrings, pointy_ears, short_hair, horn_ornament, red_horns, white_hair, horn_ribbon, bangs, curly_hair, sheep_horns, grey_hair, horizontal_pupils`, 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 | 20 | 44.78 MiB | [Download](https://huggingface.co/datasets/CyberHarem/toutetsu_yuuma_touhou/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 20 | 20.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/toutetsu_yuuma_touhou/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 54 | 47.08 MiB | [Download](https://huggingface.co/datasets/CyberHarem/toutetsu_yuuma_touhou/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 20 | 37.27 MiB | [Download](https://huggingface.co/datasets/CyberHarem/toutetsu_yuuma_touhou/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 54 | 74.61 MiB | [Download](https://huggingface.co/datasets/CyberHarem/toutetsu_yuuma_touhou/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/toutetsu_yuuma_touhou',
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 | 20 |  |  |  |  |  | 1girl, jewelry, solo, blue_dress, red_sleeves, sharp_teeth, looking_at_viewer, bare_shoulders, detached_sleeves, oversized_object, smile, open_mouth, spoon |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | jewelry | solo | blue_dress | red_sleeves | sharp_teeth | looking_at_viewer | bare_shoulders | detached_sleeves | oversized_object | smile | open_mouth | spoon |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:----------|:-------|:-------------|:--------------|:--------------|:--------------------|:-----------------|:-------------------|:-------------------|:--------|:-------------|:--------|
| 0 | 20 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X |
| CyberHarem/toutetsu_yuuma_touhou | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-15T10:22:07+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-15T10:29:09+00:00 |
11801b3305dafd57d68a8a7d09009f5a925fe741 | slplab/asd_syl_240115 | [
"region:us"
] | 2024-01-15T10:24:52+00:00 | {} | 2024-01-15T10:26:46+00:00 |
|
f02a094952b01741c7ba187c426b568cb6123cce | Gabbbzzz/potato_farming | [
"region:us"
] | 2024-01-15T10:29:34+00:00 | {} | 2024-01-15T12:37:51+00:00 |
|
ecb6f3cd4d08203b252f0b5ee68849176805e631 | herbievore/bbc_complete | [
"region:us"
] | 2024-01-15T10:39:45+00:00 | {} | 2024-01-15T10:40:01+00:00 |
|
7059f8e33bb37e740d7c228f5bc5ccfb51bc166b | Kamyar-zeinalipour/Protein | [
"region:us"
] | 2024-01-17T11:08:57+00:00 | {"dataset_info": {"features": [{"name": "Cluster ID", "dtype": "string"}, {"name": "Cluster Name", "dtype": "string"}, {"name": "Types", "dtype": "string"}, {"name": "Size", "dtype": "int64"}, {"name": "Organisms", "dtype": "string"}, {"name": "Length", "dtype": "int64"}, {"name": "Identity", "dtype": "float64"}, {"name": "Reference sequence", "dtype": "string"}, {"name": "Common taxon ID", "dtype": "int64"}, {"name": "Common taxon", "dtype": "string"}, {"name": "Organism IDs", "dtype": "string"}, {"name": "Cluster members", "dtype": "string"}, {"name": "Date of creation", "dtype": "string"}, {"name": "__index_level_0__", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 43805803, "num_examples": 52000}, {"name": "test", "num_bytes": 1693705, "num_examples": 1986}], "download_size": 27144249, "dataset_size": 45499508}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-17T11:09:04+00:00 |
|
73027ffcfed3121a9874efb861ea507b8a7f6e5a |
# Dataset Card for Evaluation run of sumo43/Yi-32b-x2-v2.0
<!-- Provide a quick summary of the dataset. -->
Dataset automatically created during the evaluation run of model [sumo43/Yi-32b-x2-v2.0](https://huggingface.co/sumo43/Yi-32b-x2-v2.0) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 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_sumo43__Yi-32b-x2-v2.0",
"harness_winogrande_5",
split="train")
```
## Latest results
These are the [latest results from run 2024-01-17T11:06:51.060608](https://huggingface.co/datasets/open-llm-leaderboard/details_sumo43__Yi-32b-x2-v2.0/blob/main/results_2024-01-17T11-06-51.060608.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": 0.7642971242141403,
"acc_stderr": 0.02819142505165966,
"acc_norm": 0.7688226036476489,
"acc_norm_stderr": 0.02871739914525888,
"mc1": 0.5862913096695227,
"mc1_stderr": 0.0172408618120998,
"mc2": 0.7322370420432542,
"mc2_stderr": 0.014094911817256119
},
"harness|arc:challenge|25": {
"acc": 0.7022184300341296,
"acc_stderr": 0.013363080107244482,
"acc_norm": 0.7303754266211604,
"acc_norm_stderr": 0.012968040686869155
},
"harness|hellaswag|10": {
"acc": 0.6692889862577176,
"acc_stderr": 0.004695076629884535,
"acc_norm": 0.8594901414060944,
"acc_norm_stderr": 0.003468050114923806
},
"harness|hendrycksTest-abstract_algebra|5": {
"acc": 0.5,
"acc_stderr": 0.050251890762960605,
"acc_norm": 0.5,
"acc_norm_stderr": 0.050251890762960605
},
"harness|hendrycksTest-anatomy|5": {
"acc": 0.762962962962963,
"acc_stderr": 0.03673731683969506,
"acc_norm": 0.762962962962963,
"acc_norm_stderr": 0.03673731683969506
},
"harness|hendrycksTest-astronomy|5": {
"acc": 0.875,
"acc_stderr": 0.026913523521537846,
"acc_norm": 0.875,
"acc_norm_stderr": 0.026913523521537846
},
"harness|hendrycksTest-business_ethics|5": {
"acc": 0.76,
"acc_stderr": 0.04292346959909282,
"acc_norm": 0.76,
"acc_norm_stderr": 0.04292346959909282
},
"harness|hendrycksTest-clinical_knowledge|5": {
"acc": 0.7962264150943397,
"acc_stderr": 0.02479078450177541,
"acc_norm": 0.7962264150943397,
"acc_norm_stderr": 0.02479078450177541
},
"harness|hendrycksTest-college_biology|5": {
"acc": 0.875,
"acc_stderr": 0.02765610492929436,
"acc_norm": 0.875,
"acc_norm_stderr": 0.02765610492929436
},
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}
}
```
## Dataset Details
### Dataset Description
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- **Curated by:** [More Information Needed]
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## Dataset Structure
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## Dataset Creation
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#### Data Collection and Processing
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## Dataset Card Contact
[More Information Needed] | open-llm-leaderboard/details_sumo43__Yi-32b-x2-v2.0 | [
"region:us"
] | 2024-01-17T11:09:02+00:00 | {"pretty_name": "Evaluation run of sumo43/Yi-32b-x2-v2.0", "dataset_summary": "Dataset automatically created during the evaluation run of model [sumo43/Yi-32b-x2-v2.0](https://huggingface.co/sumo43/Yi-32b-x2-v2.0) on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\nThe dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.\n\nThe dataset has been created from 1 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_sumo43__Yi-32b-x2-v2.0\",\n\t\"harness_winogrande_5\",\n\tsplit=\"train\")\n```\n\n## Latest results\n\nThese are the [latest results from run 2024-01-17T11:06:51.060608](https://huggingface.co/datasets/open-llm-leaderboard/details_sumo43__Yi-32b-x2-v2.0/blob/main/results_2024-01-17T11-06-51.060608.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\": 0.7642971242141403,\n \"acc_stderr\": 0.02819142505165966,\n \"acc_norm\": 0.7688226036476489,\n \"acc_norm_stderr\": 0.02871739914525888,\n \"mc1\": 0.5862913096695227,\n \"mc1_stderr\": 0.0172408618120998,\n \"mc2\": 0.7322370420432542,\n \"mc2_stderr\": 0.014094911817256119\n },\n \"harness|arc:challenge|25\": {\n \"acc\": 0.7022184300341296,\n \"acc_stderr\": 0.013363080107244482,\n \"acc_norm\": 0.7303754266211604,\n \"acc_norm_stderr\": 0.012968040686869155\n },\n \"harness|hellaswag|10\": {\n \"acc\": 0.6692889862577176,\n \"acc_stderr\": 0.004695076629884535,\n \"acc_norm\": 0.8594901414060944,\n \"acc_norm_stderr\": 0.003468050114923806\n },\n \"harness|hendrycksTest-abstract_algebra|5\": {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 0.5,\n \"acc_norm_stderr\": 0.050251890762960605\n },\n \"harness|hendrycksTest-anatomy|5\": {\n \"acc\": 0.762962962962963,\n \"acc_stderr\": 0.03673731683969506,\n \"acc_norm\": 0.762962962962963,\n \"acc_norm_stderr\": 0.03673731683969506\n },\n \"harness|hendrycksTest-astronomy|5\": {\n \"acc\": 0.875,\n \"acc_stderr\": 0.026913523521537846,\n \"acc_norm\": 0.875,\n \"acc_norm_stderr\": 0.026913523521537846\n },\n \"harness|hendrycksTest-business_ethics|5\": {\n \"acc\": 0.76,\n \"acc_stderr\": 0.04292346959909282,\n \"acc_norm\": 0.76,\n \"acc_norm_stderr\": 0.04292346959909282\n },\n \"harness|hendrycksTest-clinical_knowledge|5\": {\n \"acc\": 0.7962264150943397,\n \"acc_stderr\": 0.02479078450177541,\n \"acc_norm\": 0.7962264150943397,\n \"acc_norm_stderr\": 0.02479078450177541\n },\n \"harness|hendrycksTest-college_biology|5\": {\n \"acc\": 0.875,\n \"acc_stderr\": 0.02765610492929436,\n \"acc_norm\": 0.875,\n \"acc_norm_stderr\": 0.02765610492929436\n },\n \"harness|hendrycksTest-college_chemistry|5\": {\n \"acc\": 0.5,\n \"acc_stderr\": 0.050251890762960605,\n \"acc_norm\": 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"path": ["**/details_harness|hendrycksTest-moral_disputes|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_moral_scenarios_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-moral_scenarios|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_nutrition_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-nutrition|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-nutrition|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_philosophy_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-philosophy|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-philosophy|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_prehistory_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-prehistory|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-prehistory|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_professional_accounting_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-professional_accounting|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_professional_law_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-professional_law|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": 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["**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-us_foreign_policy|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_virology_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-virology|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-virology|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_hendrycksTest_world_religions_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|hendrycksTest-world_religions|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|hendrycksTest-world_religions|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_truthfulqa_mc_0", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|truthfulqa:mc|0_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|truthfulqa:mc|0_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "harness_winogrande_5", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["**/details_harness|winogrande|5_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["**/details_harness|winogrande|5_2024-01-17T11-06-51.060608.parquet"]}]}, {"config_name": "results", "data_files": [{"split": "2024_01_17T11_06_51.060608", "path": ["results_2024-01-17T11-06-51.060608.parquet"]}, {"split": "latest", "path": ["results_2024-01-17T11-06-51.060608.parquet"]}]}]} | 2024-01-17T11:09:21+00:00 |
253440f8a74dc09a331059b3a372988a819825b9 |
# **About**
This dataset is the formated version of the Isaak-Carter/Openai-function-invocations-20k-with-greetings dataset.
This dataset, uniquely structured with custom special tokens, is meticulously crafted to train language models in complex function invocation and time-contextualized interactions. Each "sample" in the dataset contains a sequence of elements: function definitions, user prompts, function calls, function responses, and the assistant's responses. These elements are separated by custom special tokens, enhancing the dataset's structure for more effective parsing and training.
Key Highlights:
- **Function Definition**: Detailed descriptions of functions, including parameters and types, enabling the model to understand and simulate API-like interactions.
- **User Prompts**: Varied user queries, encouraging the model to handle a diverse range of function-related requests.
- **Function Calls & Responses**: Simulated API call and response patterns, illustrating practical applications of function calls.
- **Time-Contextualized Assistant Responses**: The assistant's responses vary based on the time of the day, indicated by the context. This feature is pivotal in creating AI models that offer time-sensitive responses, from standard greetings to thoughtful reminders for rest during late hours.
Applications:
- **AI Assistants**: Training conversational AI that can understand and interact based on function calls and time context.
- **API Interaction Simulation**: Models that can simulate API interactions based on user requests.
- **Context-Aware Systems**: Developing systems that respond differently based on the time of interaction.
This dataset is a versatile tool for advancing AI capabilities in understanding complex queries, simulating API interactions, and providing context-aware responses. | Isaak-Carter/Formated-openai-function-invocations-20k-with-greetings | [
"task_categories:text-classification",
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:conversational",
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"region:us"
] | 2024-01-17T11:14:27+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-classification", "question-answering", "summarization", "conversational", "text-generation"], "dataset_info": {"features": [{"name": "sample", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 20270230, "num_examples": 20432}], "download_size": 6760479, "dataset_size": 20270230}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T11:36:41+00:00 |
3d4021b58c91c8c4ef6521045dd982ea5c7b0796 |
# Dataset of Wandjina/ワンジナ/旺吉娜 (Fate/Grand Order)
This is the dataset of Wandjina/ワンジナ/旺吉娜 (Fate/Grand Order), containing 22 images and their tags.
The core tags of this character are `short_hair, yellow_eyes, breasts, black_hair, dark_skin, dark-skinned_female, small_breasts, 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 | 22 | 30.91 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wandjina_fgo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 22 | 16.59 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wandjina_fgo/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 52 | 35.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wandjina_fgo/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 22 | 27.65 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wandjina_fgo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 52 | 51.38 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wandjina_fgo/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/wandjina_fgo',
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, solo, looking_at_viewer, navel, smile, clothing_cutout, open_mouth, white_background |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | looking_at_viewer | navel | smile | clothing_cutout | open_mouth | white_background |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------------------|:--------|:--------|:------------------|:-------------|:-------------------|
| 0 | 22 |  |  |  |  |  | X | X | X | X | X | X | X | X |
| CyberHarem/wandjina_fgo | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:17:38+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T11:23:26+00:00 |
ee72c58bedcb69dd81caa3d9e388d3393f9cacf5 | cjsanjay/jira_train_17012024 | [
"region:us"
] | 2024-01-17T11:18:37+00:00 | {"dataset_info": {"features": [{"name": "expand", "dtype": "string"}, {"name": "_id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "fields", "struct": [{"name": "aggregateprogress", "struct": [{"name": "percent", "dtype": "int64"}, {"name": "progress", "dtype": "int64"}, {"name": "total", "dtype": "int64"}]}, {"name": "aggregatetimeestimate", "dtype": "int64"}, {"name": "aggregatetimeoriginalestimate", "dtype": "int64"}, {"name": "aggregatetimespent", "dtype": "int64"}, {"name": "assignee", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "comments", "list": [{"name": "author", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "body", "dtype": "string"}, {"name": "created", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "updateAuthor", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "updated", "dtype": "string"}]}, {"name": "components", "list": [{"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "created", "dtype": "string"}, {"name": "creator", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "customfield_10010", "dtype": "float64"}, {"name": "customfield_10022", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "customfield_10023", "struct": [{"name": "disabled", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "customfield_10024", "list": [{"name": "disabled", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "customfield_12310191", "list": [{"name": "disabled", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "customfield_12310192", "dtype": "string"}, {"name": "customfield_12310230", "dtype": "string"}, {"name": "customfield_12310250", "list": [{"name": "disabled", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "customfield_12310290", "dtype": "null"}, {"name": "customfield_12310291", "dtype": "null"}, {"name": "customfield_12310300", "dtype": "null"}, {"name": "customfield_12310320", "list": [{"name": "archived", "dtype": "bool"}, {"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "releaseDate", "dtype": "string"}, {"name": "released", "dtype": "bool"}, {"name": "self", "dtype": "string"}]}, {"name": "customfield_12310420", "dtype": "string"}, {"name": "customfield_12310920", "dtype": "string"}, {"name": "customfield_12310921", "dtype": "null"}, {"name": "customfield_12311020", "dtype": "string"}, {"name": "customfield_12311024", "dtype": "string"}, {"name": "customfield_12311038", "dtype": "null"}, {"name": "customfield_12311120", "dtype": "null"}, {"name": "customfield_12311121", "dtype": "string"}, {"name": "customfield_12311122", "struct": [{"name": "disabled", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "value", "dtype": "string"}]}, {"name": "customfield_12311123", "dtype": "string"}, {"name": "customfield_12311820", "dtype": "string"}, {"name": "customfield_12311920", "dtype": "null"}, {"name": "customfield_12312022", "dtype": "null"}, {"name": "customfield_12312023", "dtype": "null"}, {"name": "customfield_12312024", "dtype": "null"}, {"name": "customfield_12312026", "dtype": "null"}, {"name": "customfield_12312220", "dtype": "null"}, {"name": "customfield_12312320", "dtype": "null"}, {"name": "customfield_12312321", "dtype": "null"}, {"name": "customfield_12312322", "dtype": "null"}, {"name": "customfield_12312323", "dtype": "null"}, {"name": "customfield_12312324", "dtype": "null"}, {"name": "customfield_12312325", "dtype": "null"}, {"name": "customfield_12312326", "dtype": "null"}, {"name": "customfield_12312327", "dtype": "null"}, {"name": "customfield_12312328", "dtype": "null"}, {"name": "customfield_12312329", "dtype": "null"}, {"name": "customfield_12312330", "dtype": "null"}, {"name": "customfield_12312331", "dtype": "null"}, {"name": "customfield_12312332", "dtype": "null"}, {"name": "customfield_12312333", "dtype": "null"}, {"name": "customfield_12312334", "dtype": "null"}, {"name": "customfield_12312335", "dtype": "null"}, {"name": "customfield_12312336", "dtype": "null"}, {"name": "customfield_12312337", "dtype": "null"}, {"name": "customfield_12312338", "dtype": "null"}, {"name": "customfield_12312339", "dtype": "null"}, {"name": "customfield_12312340", "dtype": "null"}, {"name": "customfield_12312341", "dtype": "null"}, {"name": "customfield_12312520", "dtype": "null"}, {"name": "customfield_12312720", "dtype": "string"}, {"name": "customfield_12312821", "list": [{"name": "archived", "dtype": "bool"}, {"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "releaseDate", "dtype": "string"}, {"name": "released", "dtype": "bool"}, {"name": "self", "dtype": "string"}]}, {"name": "customfield_12312823", "dtype": "null"}, {"name": "customfield_12312920", "dtype": "null"}, {"name": "customfield_12312921", "dtype": "null"}, {"name": "customfield_12312923", "dtype": "null"}, {"name": "customfield_12313422", "dtype": "string"}, {"name": "customfield_12313520", "dtype": "null"}, {"name": "customfield_12313820", "dtype": "null"}, {"name": "customfield_12313821", "dtype": "null"}, {"name": "customfield_12313822", "dtype": "null"}, {"name": "customfield_12313823", "dtype": "null"}, {"name": "customfield_12313825", "dtype": "null"}, {"name": "customfield_12313826", "dtype": "null"}, {"name": "customfield_12313920", "dtype": "null"}, {"name": "customfield_12313924", "dtype": "null"}, {"name": "customfield_12314020", "dtype": "string"}, {"name": "customfield_12314120", "dtype": "null"}, {"name": "customfield_12314121", "dtype": "null"}, {"name": "customfield_12314122", "dtype": "null"}, {"name": "customfield_12314123", "dtype": "null"}, {"name": "customfield_12314124", "dtype": "null"}, {"name": "customfield_12314125", "dtype": "null"}, {"name": "customfield_12314126", "list": [{"name": "archived", "dtype": "bool"}, {"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "releaseDate", "dtype": "string"}, {"name": "released", "dtype": "bool"}, {"name": "self", "dtype": "string"}]}, {"name": "customfield_12314127", "dtype": "null"}, {"name": "customfield_12314128", "dtype": "null"}, {"name": "customfield_12314129", "dtype": "null"}, {"name": "customfield_12314130", "dtype": "null"}, {"name": "customfield_12314131", "dtype": "null"}, {"name": "customfield_12314132", "dtype": "null"}, {"name": "customfield_12314134", "dtype": "null"}, {"name": "customfield_12314135", "dtype": "null"}, {"name": "customfield_12314136", "dtype": "null"}, {"name": "customfield_12314137", "dtype": "null"}, {"name": "customfield_12314138", "dtype": "null"}, {"name": "customfield_12314139", "dtype": "null"}, {"name": "customfield_12314140", "dtype": "null"}, {"name": "customfield_12314141", "dtype": "null"}, {"name": "customfield_12314143", "dtype": "null"}, {"name": "customfield_12314144", "dtype": "null"}, {"name": "customfield_12314145", "dtype": "null"}, {"name": "customfield_12314146", "dtype": "null"}, {"name": "customfield_12314420", "dtype": "null"}, {"name": "customfield_12314421", "sequence": "string"}, {"name": "customfield_12314422", "dtype": "null"}, {"name": "customfield_12314520", "dtype": "null"}, {"name": "customfield_12314521", "dtype": "null"}, {"name": "customfield_12314522", "dtype": "null"}, {"name": "customfield_12314523", "dtype": "null"}, {"name": "customfield_12314524", "dtype": "null"}, {"name": "description", "dtype": "string"}, {"name": "duedate", "dtype": "string"}, {"name": "environment", "dtype": "string"}, {"name": "fixVersions", "list": [{"name": "archived", "dtype": "bool"}, {"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "releaseDate", "dtype": "string"}, {"name": "released", "dtype": "bool"}, {"name": "self", "dtype": "string"}]}, {"name": "issuelinks", "list": [{"name": "id", "dtype": "string"}, {"name": "inwardIssue", "struct": [{"name": "fields", "struct": [{"name": "issuetype", "struct": [{"name": "avatarId", "dtype": "int64"}, {"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "subtask", "dtype": "bool"}]}, {"name": "priority", "struct": [{"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "status", "struct": [{"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "statusCategory", "struct": [{"name": "colorName", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "summary", "dtype": "string"}]}, {"name": "id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "outwardIssue", "struct": [{"name": "fields", "struct": [{"name": "issuetype", "struct": [{"name": "avatarId", "dtype": "int64"}, {"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "subtask", "dtype": "bool"}]}, {"name": "priority", "struct": [{"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "status", "struct": [{"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "statusCategory", "struct": [{"name": "colorName", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "summary", "dtype": "string"}]}, {"name": "id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "self", "dtype": "string"}, {"name": "type", "struct": [{"name": "id", "dtype": "string"}, {"name": "inward", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "outward", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "issuetype", "struct": [{"name": "avatarId", "dtype": "int64"}, {"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "subtask", "dtype": "bool"}]}, {"name": "labels", "sequence": "string"}, {"name": "lastViewed", "dtype": "null"}, {"name": "parent", "struct": [{"name": "fields", "struct": [{"name": "issuetype", "struct": [{"name": "avatarId", "dtype": "int64"}, {"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "subtask", "dtype": "bool"}]}, {"name": "priority", "struct": [{"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "status", "struct": [{"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "statusCategory", "struct": [{"name": "colorName", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "summary", "dtype": "string"}]}, {"name": "id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "priority", "struct": [{"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "progress", "struct": [{"name": "percent", "dtype": "int64"}, {"name": "progress", "dtype": "int64"}, {"name": "total", "dtype": "int64"}]}, {"name": "project", "struct": [{"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "projectCategory", "struct": [{"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "projectTypeKey", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "reporter", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "resolution", "struct": [{"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "resolutiondate", "dtype": "string"}, {"name": "status", "struct": [{"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "statusCategory", "struct": [{"name": "colorName", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "subtasks", "list": [{"name": "fields", "struct": [{"name": "issuetype", "struct": [{"name": "avatarId", "dtype": "int64"}, {"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "subtask", "dtype": "bool"}]}, {"name": "priority", "struct": [{"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "status", "struct": [{"name": "description", "dtype": "string"}, {"name": "iconUrl", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "statusCategory", "struct": [{"name": "colorName", "dtype": "string"}, {"name": "id", "dtype": "int64"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}]}]}, {"name": "summary", "dtype": "string"}]}, {"name": "id", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "self", "dtype": "string"}]}, {"name": "summary", "dtype": "string"}, {"name": "timeestimate", "dtype": "int64"}, {"name": "timeoriginalestimate", "dtype": "int64"}, {"name": "timespent", "dtype": "int64"}, {"name": "updated", "dtype": "string"}, {"name": "versions", "list": [{"name": "archived", "dtype": "bool"}, {"name": "description", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "releaseDate", "dtype": "string"}, {"name": "released", "dtype": "bool"}, {"name": "self", "dtype": "string"}]}, {"name": "votes", "struct": [{"name": "hasVoted", "dtype": "bool"}, {"name": "self", "dtype": "string"}, {"name": "votes", "dtype": "int64"}]}, {"name": "watches", "struct": [{"name": "isWatching", "dtype": "bool"}, {"name": "self", "dtype": "string"}, {"name": "watchCount", "dtype": "int64"}]}, {"name": "workratio", "dtype": "int64"}]}, {"name": "changelog", "struct": [{"name": "histories", "list": [{"name": "author", "struct": [{"name": "active", "dtype": "bool"}, {"name": "avatarUrls", "struct": [{"name": "16x16", "dtype": "string"}, {"name": "24x24", "dtype": "string"}, {"name": "32x32", "dtype": "string"}, {"name": "48x48", "dtype": "string"}]}, {"name": "displayName", "dtype": "string"}, {"name": "key", "dtype": "string"}, {"name": "name", "dtype": "string"}, {"name": "self", "dtype": "string"}, {"name": "timeZone", "dtype": "string"}]}, {"name": "created", "dtype": "string"}, {"name": "id", "dtype": "string"}, {"name": "items", "list": [{"name": "field", "dtype": "string"}, {"name": "fieldtype", "dtype": "string"}, {"name": "from", "dtype": "string"}, {"name": "fromString", "dtype": "string"}, {"name": "to", "dtype": "string"}, {"name": "toString", "dtype": "string"}]}]}, {"name": "maxResults", "dtype": "int64"}, {"name": "startAt", "dtype": "int64"}, {"name": "total", "dtype": "int64"}]}, {"name": "self", "dtype": "string"}, {"name": "is_secops", "dtype": "bool"}, {"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1011042600, "num_examples": 34598}], "download_size": 155169432, "dataset_size": 1011042600}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T11:19:07+00:00 |
|
5d5cd07bb49954d0812af0e721fbecddd42a611e |
# Dataset of Kashin Koji/果心居士 (Fate/Grand Order)
This is the dataset of Kashin Koji/果心居士 (Fate/Grand Order), containing 34 images and their tags.
The core tags of this character are `heterochromia, long_hair, multicolored_hair, red_eyes, white_hair, black_hair, bangs, grey_hair, two-tone_hair, hair_ornament, green_eyes, twintails, very_long_hair, blue_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 | 34 | 72.37 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kashin_koji_fgo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 34 | 33.63 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kashin_koji_fgo/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 83 | 73.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kashin_koji_fgo/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 34 | 58.87 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kashin_koji_fgo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 83 | 115.31 MiB | [Download](https://huggingface.co/datasets/CyberHarem/kashin_koji_fgo/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/kashin_koji_fgo',
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 | 25 |  |  |  |  |  | 1girl, solo, looking_at_viewer, parted_lips, split-color_hair, red_gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | looking_at_viewer | parted_lips | split-color_hair | red_gloves |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:--------------------|:--------------|:-------------------|:-------------|
| 0 | 25 |  |  |  |  |  | X | X | X | X | X | X |
| CyberHarem/kashin_koji_fgo | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:19:30+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T11:29:23+00:00 |
d4ff1d7811910aa78e494ebad0c65b072b8630b2 |
# Dataset of Sugitani Zenjyubou/杉谷善住坊 (Fate/Grand Order)
This is the dataset of Sugitani Zenjyubou/杉谷善住坊 (Fate/Grand Order), containing 25 images and their tags.
The core tags of this character are `brown_hair, breasts, brown_eyes, large_breasts, yellow_eyes, ahoge, ponytail`, 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 | 25 | 37.43 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sugitani_zenjubou_fgo/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 25 | 18.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sugitani_zenjubou_fgo/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 60 | 41.50 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sugitani_zenjubou_fgo/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 25 | 31.05 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sugitani_zenjubou_fgo/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 60 | 65.41 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sugitani_zenjubou_fgo/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/sugitani_zenjubou_fgo',
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 |  |  |  |  |  | necklace, solo, bandages, scarf, 1girl, prayer_beads, hat, looking_at_viewer, short_hair, smile, cleavage |
| 1 | 9 |  |  |  |  |  | 1girl, scarf, solo, bandaged_arm, sideboob, long_hair, looking_at_viewer, smile |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | necklace | solo | bandages | scarf | 1girl | prayer_beads | hat | looking_at_viewer | short_hair | smile | cleavage | bandaged_arm | sideboob | long_hair |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-----------|:-------|:-----------|:--------|:--------|:---------------|:------|:--------------------|:-------------|:--------|:-----------|:---------------|:-----------|:------------|
| 0 | 7 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | |
| 1 | 9 |  |  |  |  |  | | X | | X | X | | | X | | X | | X | X | X |
| CyberHarem/sugitani_zenjubou_fgo | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:20:06+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T11:26:05+00:00 |
7a2ceddb8d37b5cf3670b34e1cb32110b610a770 |
## Description
Weather. Channel.
## Model
SVD
## Voice
Julian
# Tags
- News
# Style
groundhog, live tv channel, weather news report, tv studio
# Music
soft breaking news intro
## Prompt
Groundhog TV is an AI tube channel generating videos to summarize the weather forecast of the day.
The channel should keep the tone light, eventually making joke depending on the weather, sun, rain etc
| jbilcke-hf/ai-tube-groundhog-tv | [
"license:cc-by-nc-4.0",
"region:us"
] | 2024-01-17T11:22:11+00:00 | {"license": "cc-by-nc-4.0", "pretty_name": "Groundhog TV"} | 2024-01-31T20:55:20+00:00 |
8ffc544fb0c3cf478a8dcbbb9859d78160ba2481 | Faeu/mathew1 | [
"license:openrail",
"region:us"
] | 2024-01-17T11:22:38+00:00 | {"license": "openrail"} | 2024-01-17T11:53:22+00:00 |
|
cae1fd6435c03dca005205b54c77ba55454cf01d |
# **Function Invocation and Time-Based Greeting Dataset**
This unique dataset is designed for advanced natural language understanding and features function-calling capabilities. Each entry includes a contextual timestamp, a function definition, user inquiries, function calls, function responses, and an assistant's response. What makes this dataset stand out is the assistant's ability to tailor its greetings based on the time of day. For example, in the morning, it greets with "Good morning," while in the evening, the greeting changes accordingly. Notably, if the time is late at night, the assistant thoughtfully reminds the user about the importance of rest but still remains responsive to commands. This dynamic interaction based on timestamps showcases potential for creating more intuitive and human-like AI assistants.
```text
"context": "Wednesday, 02.06.2038 09:51",
"functions": "{'description': 'Get report data', 'name': 'v3_media', 'parameters': {'properties': {'file_id': {'description': 'UUID of the file.', 'type': 'string'}}, 'required': ['file_id'], 'type': 'object'}}",
"user": "I'm curious about the data in this report. Can you fetch it for me?",
"function_call": "{'name': 'v3_media', 'arguments': {'file_id': '12345'}}",
"function_response": "{'file_id': '12345', 'data': {'title': 'Sales Report', 'date': '2022-01-01', 'total_sales': 50000, 'top_selling_product': 'Widget X'}}",
"assistant_response": "Good Wednesday morning. Here is the data from the report:\n\n- Title: Sales Report\n- Date: 2022-01-01\n- Total Sales: $50,000\n- Top Selling Product: Widget X"
``` | Isaak-Carter/Openai-function-invocations-20k-with-greetings | [
"task_categories:conversational",
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"region:us"
] | 2024-01-17T11:22:44+00:00 | {"language": ["en"], "license": "apache-2.0", "size_categories": ["10K<n<100K"], "task_categories": ["conversational", "text-generation"], "dataset_info": {"features": [{"name": "function_call", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "functions", "dtype": "string"}, {"name": "user", "dtype": "string"}, {"name": "assistant_response", "dtype": "string"}, {"name": "function_response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 18475155, "num_examples": 20432}], "download_size": 7342675, "dataset_size": 18475155}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T11:33:50+00:00 |
33bc987e8d70b56af2bc4e3c5a3a30cb3587c7f2 | A2m94/headline-emotional-word | [
"size_categories:1K<n<10K",
"language:fr",
"art",
"region:us"
] | 2024-01-17T11:24:43+00:00 | {"language": ["fr"], "size_categories": ["1K<n<10K"], "tags": ["art"]} | 2024-01-17T11:27:56+00:00 |
|
d0b3910af57de6fadb5baca27b43b7fef011ea01 |
# Dataset of lyn/リンディス (Fire Emblem)
This is the dataset of lyn/リンディス (Fire Emblem), containing 500 images and their tags.
The core tags of this character are `green_hair, long_hair, ponytail, green_eyes, breasts, earrings, large_breasts, bangs, very_long_hair, high_ponytail`, 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 | 687.67 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lyn_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 392.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lyn_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1200 | 816.51 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lyn_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 611.12 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lyn_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1200 | 1.14 GiB | [Download](https://huggingface.co/datasets/CyberHarem/lyn_fireemblem/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/lyn_fireemblem',
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, blush, hair_flower, jewelry, official_alternate_costume, solo, bare_shoulders, blue_bikini, looking_at_viewer, choker, cleavage, collarbone, smile, simple_background, closed_mouth, strapless_bikini, white_background, navel |
| 1 | 11 |  |  |  |  |  | 1girl, hair_flower, jewelry, official_alternate_costume, outdoors, blue_bikini, day, solo, blue_sky, cleavage, cloud, looking_at_viewer, ocean, beach, smile, navel, bare_shoulders, blush, open_mouth, one_eye_closed, strapless_bikini, thighs, water |
| 2 | 6 |  |  |  |  |  | 1girl, fingerless_gloves, jewelry, looking_at_viewer, sword, open_mouth, solo, blue_dress, simple_background, smile, side_slit |
| 3 | 13 |  |  |  |  |  | 1girl, fingerless_gloves, holding_sword, thighs, jewelry, pelvic_curtain, solo, blue_dress, katana, looking_at_viewer, short_sleeves, side_slit, sheath, black_gloves, boots, simple_background, medium_breasts, smile, white_background, full_body, open_mouth, sash |
| 4 | 6 |  |  |  |  |  | 1girl, dress, jewelry, solo, arrow_(projectile), fingerless_gloves, holding_bow_(weapon), looking_at_viewer, quiver, simple_background, smile, white_background, feathers, armor, boots, pelvic_curtain, thighs |
| 5 | 5 |  |  |  |  |  | 1girl, arrow_(projectile), dress, elbow_gloves, feathers, fingerless_gloves, full_body, hair_ornament, holding_bow_(weapon), jewelry, knee_boots, medium_breasts, short_sleeves, solo, brown_footwear, fur_trim, shoulder_armor, simple_background, belt, fur_cape, pelvic_curtain, quiver, sheath, standing, white_background, grey_background, looking_away, parted_lips, side_slit, sword, thighs, torn_clothes |
| 6 | 6 |  |  |  |  |  | cleavage, japanese_clothes, jewelry, ninja, pelvic_curtain, sword, 1girl, bare_shoulders, fingerless_gloves, scarf, shuriken, solo, elbow_gloves, holding_weapon, medium_breasts, official_alternate_costume, thighs, looking_at_viewer, simple_background, smile |
| 7 | 8 |  |  |  |  |  | 1boy, 1girl, blush, hetero, jewelry, penis, solo_focus, open_mouth, paizuri, bar_censor, fingerless_gloves, nipples, cum_on_breasts, breasts_squeezed_together, male_pubic_hair, black_gloves, blue_dress, breasts_out, clothes_lift, ejaculation, facial, smile, sweatdrop, white_background |
| 8 | 5 |  |  |  |  |  | 1girl, bare_shoulders, bride, hair_flower, necklace, wedding_dress, white_dress, bouquet, cleavage, official_alternate_costume, open_mouth, solo, strapless_dress, blush, detached_sleeves, holding, looking_at_viewer, simple_background, white_background, bridal_veil, medium_breasts, petals, smile, sweatdrop |
| 9 | 6 |  |  |  |  |  | 1boy, 1girl, blush, hetero, open_mouth, sex, solo_focus, mosaic_censoring, penis, vaginal, closed_eyes, nipples, spread_legs, cum_in_pussy, rape, tears |
| 10 | 12 |  |  |  |  |  | 1girl, hetero, nipples, sex, 1boy, sweat, blush, solo_focus, vaginal, completely_nude, girl_on_top, penis, mosaic_censoring, jewelry, medium_breasts, cowgirl_position, cum, looking_at_viewer, pubic_hair |
| 11 | 5 |  |  |  |  |  | 1girl, bandages, bandeau, blue_shirt, blue_skirt, chest_sarashi, full_body, holding_polearm, mask_on_head, midriff, navel, official_alternate_costume, paper_lantern, single_bare_shoulder, single_sleeve, solo, spear, stomach, tube_top, white_background, cleavage, simple_background, thighs, looking_at_viewer, short_sleeves, standing, :d, collarbone, fire, grin, jewelry, lips, open_mouth, teeth |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | blush | hair_flower | jewelry | official_alternate_costume | solo | bare_shoulders | blue_bikini | looking_at_viewer | choker | cleavage | collarbone | smile | simple_background | closed_mouth | strapless_bikini | white_background | navel | outdoors | day | blue_sky | cloud | ocean | beach | open_mouth | one_eye_closed | thighs | water | fingerless_gloves | sword | blue_dress | side_slit | holding_sword | pelvic_curtain | katana | short_sleeves | sheath | black_gloves | boots | medium_breasts | full_body | sash | dress | arrow_(projectile) | holding_bow_(weapon) | quiver | feathers | armor | elbow_gloves | hair_ornament | knee_boots | brown_footwear | fur_trim | shoulder_armor | belt | fur_cape | standing | grey_background | looking_away | parted_lips | torn_clothes | japanese_clothes | ninja | scarf | shuriken | holding_weapon | 1boy | hetero | penis | solo_focus | paizuri | bar_censor | nipples | cum_on_breasts | breasts_squeezed_together | male_pubic_hair | breasts_out | clothes_lift | ejaculation | facial | sweatdrop | bride | necklace | wedding_dress | white_dress | bouquet | strapless_dress | detached_sleeves | holding | bridal_veil | petals | sex | mosaic_censoring | vaginal | closed_eyes | spread_legs | cum_in_pussy | rape | tears | sweat | completely_nude | girl_on_top | cowgirl_position | cum | pubic_hair | bandages | bandeau | blue_shirt | blue_skirt | chest_sarashi | holding_polearm | mask_on_head | midriff | paper_lantern | single_bare_shoulder | single_sleeve | spear | stomach | tube_top | :d | fire | grin | lips | teeth |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------|:--------------|:----------|:-----------------------------|:-------|:-----------------|:--------------|:--------------------|:---------|:-----------|:-------------|:--------|:--------------------|:---------------|:-------------------|:-------------------|:--------|:-----------|:------|:-----------|:--------|:--------|:--------|:-------------|:-----------------|:---------|:--------|:--------------------|:--------|:-------------|:------------|:----------------|:-----------------|:---------|:----------------|:---------|:---------------|:--------|:-----------------|:------------|:-------|:--------|:---------------------|:-----------------------|:---------|:-----------|:--------|:---------------|:----------------|:-------------|:-----------------|:-----------|:-----------------|:-------|:-----------|:-----------|:------------------|:---------------|:--------------|:---------------|:-------------------|:--------|:--------|:-----------|:-----------------|:-------|:---------|:--------|:-------------|:----------|:-------------|:----------|:-----------------|:----------------------------|:------------------|:--------------|:---------------|:--------------|:---------|:------------|:--------|:-----------|:----------------|:--------------|:----------|:------------------|:-------------------|:----------|:--------------|:---------|:------|:-------------------|:----------|:--------------|:--------------|:---------------|:-------|:--------|:--------|:------------------|:--------------|:-------------------|:------|:-------------|:-----------|:----------|:-------------|:-------------|:----------------|:------------------|:---------------|:----------|:----------------|:-----------------------|:----------------|:--------|:----------|:-----------|:-----|:-------|:-------|:-------|:--------|
| 0 | 9 |  |  |  |  |  | X | X | X | X | 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 | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 13 |  |  |  |  |  | X | | | X | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | X | | | X | X | 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 | 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 | 6 |  |  |  |  |  | X | X | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | | | X | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 12 |  |  |  |  |  | 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 | X | X | X | X | X | X | X | X | X |
| CyberHarem/lyn_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:25:15+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:07:25+00:00 |
c2372ae32a48f94542b58fa664e1275729c4ffe5 |
# Dataset of sakura/サクラ (Fire Emblem)
This is the dataset of sakura/サクラ (Fire Emblem), containing 362 images and their tags.
The core tags of this character are `short_hair, pink_hair, hairband, pink_eyes, breasts, 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 | 362 | 369.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakura_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 362 | 239.24 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakura_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 769 | 463.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakura_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 362 | 339.16 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakura_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 769 | 611.37 MiB | [Download](https://huggingface.co/datasets/CyberHarem/sakura_fireemblem/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/sakura_fireemblem',
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 |  |  |  |  |  | 1boy, 1girl, hetero, blush, nipples, sex, open_mouth, solo_focus, penis, sweat, vaginal, pussy, mosaic_censoring, medium_breasts, spread_legs, navel, red_hair, small_breasts, thighhighs, completely_nude |
| 1 | 5 |  |  |  |  |  | 1girl, gloves, japanese_clothes, simple_background, smile, solo, white_background, capelet, looking_at_viewer |
| 2 | 6 |  |  |  |  |  | 1girl, japanese_clothes, smile, solo, capelet, gloves, blush, open_mouth, thighhighs |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1boy | 1girl | hetero | blush | nipples | sex | open_mouth | solo_focus | penis | sweat | vaginal | pussy | mosaic_censoring | medium_breasts | spread_legs | navel | red_hair | small_breasts | thighhighs | completely_nude | gloves | japanese_clothes | simple_background | smile | solo | white_background | capelet | looking_at_viewer |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:-------|:--------|:---------|:--------|:----------|:------|:-------------|:-------------|:--------|:--------|:----------|:--------|:-------------------|:-----------------|:--------------|:--------|:-----------|:----------------|:-------------|:------------------|:---------|:-------------------|:--------------------|:--------|:-------|:-------------------|:----------|:--------------------|
| 0 | 21 |  |  |  |  |  | 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 |
| 2 | 6 |  |  |  |  |  | | X | | X | | | X | | | | | | | | | | | | X | | X | X | | X | X | | X | |
| CyberHarem/sakura_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:26:46+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:16:55+00:00 |
345016b2cdd07bd75ce7fbdaee94e1d5e4cc1350 | # Dataset Card for "filtered_wikibook"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | ashish23/filtered_wikibook | [
"region:us"
] | 2024-01-17T11:31:17+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2567855206.0077558, "num_examples": 8433293}, {"name": "test", "num_bytes": 7727048.207960854, "num_examples": 25377}], "download_size": 11760058784, "dataset_size": 2575582254.215717}} | 2024-01-17T11:49:42+00:00 |
bea123f296f3c915365aeeb244f7f5065b4c75fb |
# Dataset of katua/カチュア/카츄아 (Fire Emblem)
This is the dataset of katua/カチュア/카츄아 (Fire Emblem), containing 270 images and their tags.
The core tags of this character are `blue_hair, short_hair, blue_eyes, headband, breasts, 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 | 270 | 245.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/katua_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 270 | 165.30 MiB | [Download](https://huggingface.co/datasets/CyberHarem/katua_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 534 | 304.91 MiB | [Download](https://huggingface.co/datasets/CyberHarem/katua_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 270 | 227.04 MiB | [Download](https://huggingface.co/datasets/CyberHarem/katua_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 534 | 387.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/katua_fireemblem/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/katua_fireemblem',
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, elbow_gloves, full_body, solo, thigh_boots, thighhighs, breastplate, fingerless_gloves, looking_at_viewer, short_dress, side_slit, simple_background, spear, white_background, holding_weapon, standing, sword, pegasus_knight_uniform_(fire_emblem), sheath, shoulder_armor, smile, zettai_ryouiki |
| 1 | 22 |  |  |  |  |  | 1girl, solo, elbow_gloves, fingerless_gloves, pegasus_knight_uniform_(fire_emblem), thighhighs, spear, breastplate, smile, boots, simple_background, zettai_ryouiki |
| 2 | 26 |  |  |  |  |  | 1girl, solo, nipples, blush, nude, large_breasts, pussy, open_mouth |
| 3 | 15 |  |  |  |  |  | 1girl, white_dress, bare_shoulders, smile, solo, wedding_dress, simple_background, bangs, detached_collar, strapless_dress, hair_flower, white_background, full_body, feather_trim, official_alternate_costume, skirt_hold, white_footwear, closed_mouth, detached_sleeves, holding, looking_at_viewer |
| 4 | 14 |  |  |  |  |  | fake_animal_ears, rabbit_ears, rabbit_tail, 1girl, pegasus_knight_uniform_(fire_emblem), solo, elbow_gloves, thighhighs, blush, playboy_bunny, hair_flower, looking_at_viewer, simple_background, white_gloves, cleavage, egg, detached_collar, open_mouth, white_background |
| 5 | 7 |  |  |  |  |  | 1boy, hetero, nipples, open_mouth, 1girl, blush, sex, solo_focus, sweat, vaginal, pussy, spread_legs, closed_eyes, completely_nude, female_pubic_hair, girl_on_top, mosaic_censoring, navel, penis, cowgirl_position |
| 6 | 5 |  |  |  |  |  | 1boy, 1girl, hetero, nipples, sex, solo_focus, open_mouth, penis, thighhighs, vaginal, white_headband, blush, censored, cum_in_pussy, fingerless_gloves, spread_legs, sweat, arm_grab, armor, ass, breasts_out, closed_eyes, on_back |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | elbow_gloves | full_body | solo | thigh_boots | thighhighs | breastplate | fingerless_gloves | looking_at_viewer | short_dress | side_slit | simple_background | spear | white_background | holding_weapon | standing | sword | pegasus_knight_uniform_(fire_emblem) | sheath | shoulder_armor | smile | zettai_ryouiki | boots | nipples | blush | nude | large_breasts | pussy | open_mouth | white_dress | bare_shoulders | wedding_dress | bangs | detached_collar | strapless_dress | hair_flower | feather_trim | official_alternate_costume | skirt_hold | white_footwear | closed_mouth | detached_sleeves | holding | fake_animal_ears | rabbit_ears | rabbit_tail | playboy_bunny | white_gloves | cleavage | egg | 1boy | hetero | sex | solo_focus | sweat | vaginal | spread_legs | closed_eyes | completely_nude | female_pubic_hair | girl_on_top | mosaic_censoring | navel | penis | cowgirl_position | white_headband | censored | cum_in_pussy | arm_grab | armor | ass | breasts_out | on_back |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:---------------|:------------|:-------|:--------------|:-------------|:--------------|:--------------------|:--------------------|:--------------|:------------|:--------------------|:--------|:-------------------|:-----------------|:-----------|:--------|:---------------------------------------|:---------|:-----------------|:--------|:-----------------|:--------|:----------|:--------|:-------|:----------------|:--------|:-------------|:--------------|:-----------------|:----------------|:--------|:------------------|:------------------|:--------------|:---------------|:-----------------------------|:-------------|:-----------------|:---------------|:-------------------|:----------|:-------------------|:--------------|:--------------|:----------------|:---------------|:-----------|:------|:-------|:---------|:------|:-------------|:--------|:----------|:--------------|:--------------|:------------------|:--------------------|:--------------|:-------------------|:--------|:--------|:-------------------|:-----------------|:-----------|:---------------|:-----------|:--------|:------|:--------------|:----------|
| 0 | 6 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 22 |  |  |  |  |  | X | X | | X | | X | X | X | | | | X | X | | | | | X | | | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 26 |  |  |  |  |  | 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 | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 4 | 14 |  |  |  |  |  | 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 | | | | | | | | |
| 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 |
| CyberHarem/katua_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:35:07+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T12:32:06+00:00 |
8c33020dcdc2e20305cf14f42cbff0dfbb017542 |
# Dataset of elise/エリーゼ (Fire Emblem)
This is the dataset of elise/エリーゼ (Fire Emblem), containing 335 images and their tags.
The core tags of this character are `blonde_hair, long_hair, twintails, purple_eyes, bow, hair_bow, ribbon, drill_hair, purple_hair, hair_ribbon, 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 | 335 | 313.25 MiB | [Download](https://huggingface.co/datasets/CyberHarem/elise_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 335 | 213.70 MiB | [Download](https://huggingface.co/datasets/CyberHarem/elise_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 676 | 400.02 MiB | [Download](https://huggingface.co/datasets/CyberHarem/elise_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 335 | 288.13 MiB | [Download](https://huggingface.co/datasets/CyberHarem/elise_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 676 | 505.66 MiB | [Download](https://huggingface.co/datasets/CyberHarem/elise_fireemblem/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/elise_fireemblem',
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 | 45 |  |  |  |  |  | 1girl, solo, gloves, smile, dress, open_mouth, staff, thighhighs, armor, thigh_boots |
| 1 | 11 |  |  |  |  |  | 1girl, black_bow, open_mouth, bangs, white_background, white_rose, simple_background, solo, :d, black_dress, blush, looking_at_viewer, very_long_hair, black_gloves, earrings, two-tone_hair, upper_body, black_capelet, holding_staff, long_sleeves, pink_bowtie |
| 2 | 5 |  |  |  |  |  | 1girl, ninja, official_alternate_costume, open_mouth, red_scarf, bangs, looking_at_viewer, obi, :d, bare_shoulders, black_gloves, blush, fingerless_gloves, multicolored_hair, solo, 2girls, earrings, holding, scroll, shuriken, sidelocks, simple_background, sleeveless_kimono, upper_body, very_long_hair |
| 3 | 7 |  |  |  |  |  | 1girl, navel, solo, blush, nipples, medium_breasts, open_mouth, completely_nude, looking_at_viewer, one_eye_closed, smile |
| 4 | 8 |  |  |  |  |  | 1girl, hetero, nipples, solo_focus, 1boy, completely_nude, open_mouth, pussy, sex, navel, penis, blush, girl_on_top, small_breasts, smile, spread_legs, vaginal, cowgirl_position, medium_breasts, uncensored |
| 5 | 6 |  |  |  |  |  | 1boy, 1girl, hetero, sex, solo_focus, vaginal, cum_in_pussy, gloves, nipples, penis, open_mouth, small_breasts, thighhighs, blush, mosaic_censoring |
| 6 | 7 |  |  |  |  |  | open_mouth, smile, black_bow, blush, multicolored_hair, flower_necklace, small_breasts, very_long_hair, 1girl, 2girls, bikini, black_one-piece_swimsuit, blue_sky, casual_one-piece_swimsuit, closed_eyes, cloud, day, outdoors, water |
| 7 | 6 |  |  |  |  |  | 1girl, bondage, solo, arms_behind_back, gagged, rope, shibari, improvised_gag, thighhighs |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | gloves | smile | dress | open_mouth | staff | thighhighs | armor | thigh_boots | black_bow | bangs | white_background | white_rose | simple_background | :d | black_dress | blush | looking_at_viewer | very_long_hair | black_gloves | earrings | two-tone_hair | upper_body | black_capelet | holding_staff | long_sleeves | pink_bowtie | ninja | official_alternate_costume | red_scarf | obi | bare_shoulders | fingerless_gloves | multicolored_hair | 2girls | holding | scroll | shuriken | sidelocks | sleeveless_kimono | navel | nipples | medium_breasts | completely_nude | one_eye_closed | hetero | solo_focus | 1boy | pussy | sex | penis | girl_on_top | small_breasts | spread_legs | vaginal | cowgirl_position | uncensored | cum_in_pussy | mosaic_censoring | flower_necklace | bikini | black_one-piece_swimsuit | blue_sky | casual_one-piece_swimsuit | closed_eyes | cloud | day | outdoors | water | bondage | arms_behind_back | gagged | rope | shibari | improvised_gag |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:---------|:--------|:--------|:-------------|:--------|:-------------|:--------|:--------------|:------------|:--------|:-------------------|:-------------|:--------------------|:-----|:--------------|:--------|:--------------------|:-----------------|:---------------|:-----------|:----------------|:-------------|:----------------|:----------------|:---------------|:--------------|:--------|:-----------------------------|:------------|:------|:-----------------|:--------------------|:--------------------|:---------|:----------|:---------|:-----------|:------------|:--------------------|:--------|:----------|:-----------------|:------------------|:-----------------|:---------|:-------------|:-------|:--------|:------|:--------|:--------------|:----------------|:--------------|:----------|:-------------------|:-------------|:---------------|:-------------------|:------------------|:---------|:---------------------------|:-----------|:----------------------------|:--------------|:--------|:------|:-----------|:--------|:----------|:-------------------|:---------|:-------|:----------|:-----------------|
| 0 | 45 |  |  |  |  |  | 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 | 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 | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 7 |  |  |  |  |  | X | X | | X | | 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 | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | 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 | 6 |  |  |  |  |  | X | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | X |
| CyberHarem/elise_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:35:16+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T12:56:30+00:00 |
40056ec4725839d3a4e765f374b40158ff7773aa |
# Dataset of wayu/ワユ (Fire Emblem)
This is the dataset of wayu/ワユ (Fire Emblem), containing 500 images and their tags.
The core tags of this character are `long_hair, green_eyes, blue_hair, hairband, white_hairband, breasts, ahoge, purple_hair, headband`, 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 | 620.79 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wayu_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 370.40 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wayu_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1194 | 781.07 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wayu_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 558.48 MiB | [Download](https://huggingface.co/datasets/CyberHarem/wayu_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1194 | 1.05 GiB | [Download](https://huggingface.co/datasets/CyberHarem/wayu_fireemblem/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/wayu_fireemblem',
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, fingerless_gloves, holding_sword, looking_at_viewer, smile, solo, detached_sleeves, armor, belt, simple_background, thighhighs, closed_mouth |
| 1 | 13 |  |  |  |  |  | 1girl, smile, solo, fingerless_gloves, sword, simple_background, thighhighs, belt, detached_sleeves, bare_shoulders, white_background, open_mouth, zettai_ryouiki |
| 2 | 5 |  |  |  |  |  | 1girl, detached_sleeves, fingerless_gloves, holding_sword, navel, official_alternate_costume, smile, solo, thighhighs, cape, looking_at_viewer, open_mouth, short_shorts, midriff, sheathed, white_shorts, bare_shoulders, belt, medium_breasts, simple_background, white_background, white_gloves |
| 3 | 9 |  |  |  |  |  | 1girl, belt, halloween_costume, navel_cutout, solo, white_headband, witch_hat, detached_sleeves, fingerless_gloves, open_mouth, black_gloves, garter_straps, broom_riding, thighhighs |
| 4 | 8 |  |  |  |  |  | 1girl, blue_sky, day, hair_flower, orange_bikini, solo, cloud, navel, cleavage, looking_at_viewer, grin, armpits, holding, large_breasts, open_mouth, thigh_strap, wristband |
| 5 | 13 |  |  |  |  |  | hair_flower, orange_bikini, 1girl, smile, solo, medium_breasts, simple_background, cleavage, looking_at_viewer, navel, white_background, open_mouth, wristband, official_alternate_costume, orange_flower, thigh_strap, holding |
| 6 | 9 |  |  |  |  |  | 1girl, blush, hair_flower, hetero, orange_bikini, penis, sex, solo_focus, vaginal, nipples, open_mouth, 1boy, cum_in_pussy, spread_legs, thigh_strap, breasts_out, day, large_breasts, mosaic_censoring, navel, orange_flower, outdoors, clothes_lift, ejaculation, wristband, bangs, blue_sky, clothing_aside, cloud, stomach |
| 7 | 7 |  |  |  |  |  | 1girl, cum_in_pussy, gangbang, hetero, multiple_penises, nipples, solo_focus, thighhighs, vaginal, 3boys, blush, ejaculation, spread_legs, clothed_female_nude_male, cum_on_breasts, large_breasts, open_mouth, breast_grab, breasts_out, clothed_sex, detached_sleeves, facial, fingerless_gloves, grabbing, testicles, bar_censor, belt, gloved_handjob, mosaic_censoring, rape |
| 8 | 6 |  |  |  |  |  | 1boy, 1girl, blush, hetero, nipples, open_mouth, penis, solo_focus, thighhighs, vaginal, breasts_out, clothed_female_nude_male, clothed_sex, fingerless_gloves, medium_breasts, mosaic_censoring, spread_legs, belt, cum_in_pussy, elbow_gloves, lying, black_gloves, detached_sleeves, large_breasts, tears |
| 9 | 6 |  |  |  |  |  | 1girl, navel, nipples, smile, solo, pussy, blush, looking_at_viewer, medium_breasts, simple_background, bar_censor, completely_nude, large_breasts, white_background |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | fingerless_gloves | holding_sword | looking_at_viewer | smile | solo | detached_sleeves | armor | belt | simple_background | thighhighs | closed_mouth | sword | bare_shoulders | white_background | open_mouth | zettai_ryouiki | navel | official_alternate_costume | cape | short_shorts | midriff | sheathed | white_shorts | medium_breasts | white_gloves | halloween_costume | navel_cutout | white_headband | witch_hat | black_gloves | garter_straps | broom_riding | blue_sky | day | hair_flower | orange_bikini | cloud | cleavage | grin | armpits | holding | large_breasts | thigh_strap | wristband | orange_flower | blush | hetero | penis | sex | solo_focus | vaginal | nipples | 1boy | cum_in_pussy | spread_legs | breasts_out | mosaic_censoring | outdoors | clothes_lift | ejaculation | bangs | clothing_aside | stomach | gangbang | multiple_penises | 3boys | clothed_female_nude_male | cum_on_breasts | breast_grab | clothed_sex | facial | grabbing | testicles | bar_censor | gloved_handjob | rape | elbow_gloves | lying | tears | pussy | completely_nude |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:----------------|:--------------------|:--------|:-------|:-------------------|:--------|:-------|:--------------------|:-------------|:---------------|:--------|:-----------------|:-------------------|:-------------|:-----------------|:--------|:-----------------------------|:-------|:---------------|:----------|:-----------|:---------------|:-----------------|:---------------|:--------------------|:---------------|:-----------------|:------------|:---------------|:----------------|:---------------|:-----------|:------|:--------------|:----------------|:--------|:-----------|:-------|:----------|:----------|:----------------|:--------------|:------------|:----------------|:--------|:---------|:--------|:------|:-------------|:----------|:----------|:-------|:---------------|:--------------|:--------------|:-------------------|:-----------|:---------------|:--------------|:--------|:-----------------|:----------|:-----------|:-------------------|:--------|:---------------------------|:-----------------|:--------------|:--------------|:---------|:-----------|:------------|:-------------|:-----------------|:-------|:---------------|:--------|:--------|:--------|:------------------|
| 0 | 7 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 13 |  |  |  |  |  | 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 | 9 |  |  |  |  |  | X | X | | | | X | X | | X | | X | | | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 13 |  |  |  |  |  | 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 | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | |
| 7 | 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 | X | X | X | X | X | X | | | | | |
| 8 | 6 |  |  |  |  |  | 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 | | |
| 9 | 6 |  |  |  |  |  | X | | | X | X | X | | | | X | | | | | X | | | X | | | | | | | X | | | | | | | | | | | | | | | | | | X | | | | X | | | | | | X | | | | | | | | | | | | | | | | | | | | | | X | | | | | | X | X |
| CyberHarem/wayu_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:35:24+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:17:09+00:00 |
f9b83e1776ed4d269129750ef6f7e7f9e22bccc9 |
# Dataset of eirik/エイリーク (Fire Emblem)
This is the dataset of eirik/エイリーク (Fire Emblem), containing 500 images and their tags.
The core tags of this character are `long_hair, blue_eyes, aqua_hair, blue_hair, bangs, breasts, aqua_eyes, sidelocks`, 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 | 718.41 MiB | [Download](https://huggingface.co/datasets/CyberHarem/eirik_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 409.08 MiB | [Download](https://huggingface.co/datasets/CyberHarem/eirik_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1192 | 846.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/eirik_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 639.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/eirik_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1192 | 1.16 GiB | [Download](https://huggingface.co/datasets/CyberHarem/eirik_fireemblem/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/eirik_fireemblem',
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, breastplate, closed_mouth, red_shirt, solo, upper_body, looking_at_viewer, pauldrons, simple_background, smile, short_sleeves, cape, earrings, hair_between_eyes, white_background |
| 1 | 14 |  |  |  |  |  | 1girl, breastplate, cape, holding_sword, miniskirt, red_gloves, thigh_boots, white_skirt, zettai_ryouiki, fingerless_gloves, solo, looking_at_viewer, short_sleeves, shoulder_armor, red_footwear, red_shirt, earrings, full_body, closed_mouth, rapier, red_thighhighs, hair_between_eyes, standing, simple_background, smile, white_background |
| 2 | 5 |  |  |  |  |  | 1girl, armor, cape, rapier, skirt, solo, thighhighs, earrings, thigh_boots, zettai_ryouiki, white_background, fingerless_gloves |
| 3 | 6 |  |  |  |  |  | 1girl, breastplate, cape, looking_at_viewer, red_gloves, shoulder_armor, solo, shirt, white_skirt, fingerless_gloves, hair_between_eyes, short_sleeves, holding_sword, smile |
| 4 | 6 |  |  |  |  |  | 1girl, breastplate, fingerless_gloves, looking_at_viewer, red_gloves, shoulder_armor, solo, upper_body, earrings, open_mouth, red_shirt, cape, simple_background, smile, blush, hair_between_eyes, shiny_hair |
| 5 | 6 |  |  |  |  |  | 1girl, alternate_hairstyle, breastplate, cosplay, ponytail, solo, upper_body, cape, closed_mouth, looking_at_viewer, official_alternate_costume, simple_background, smile, earrings, white_background |
| 6 | 25 |  |  |  |  |  | 1girl, solo, breastplate, cape, looking_at_viewer, ponytail, cosplay, holding_polearm, official_alternate_costume, spear, earrings, brown_gloves, thighhighs, skirt, smile, alternate_hairstyle, belt, shoulder_armor, boots, hair_ornament, simple_background |
| 7 | 11 |  |  |  |  |  | 1girl, christmas, fur_trim, santa_costume, santa_hat, smile, cape, looking_at_viewer, red_gloves, solo, dress, official_alternate_costume, open_mouth, red_headwear, blush, holding_staff, skirt |
| 8 | 9 |  |  |  |  |  | 1girl, hair_flower, smile, solo, earrings, looking_at_viewer, simple_background, white_background, bare_shoulders, closed_mouth, wedding_dress, white_dress |
| 9 | 17 |  |  |  |  |  | 1girl, hair_flower, official_alternate_costume, smile, yellow_bikini, solo, navel, cleavage, off-shoulder_bikini, bare_shoulders, looking_at_viewer, bracelet, hibiscus, necklace, two-tone_bikini, open_mouth, blush, layered_bikini, bikini_skirt, innertube, medium_breasts, simple_background, white_background |
| 10 | 11 |  |  |  |  |  | 1girl, black_bikini, cleavage, hair_flower, large_breasts, official_alternate_costume, solo, looking_at_viewer, smile, cloud, navel, ocean, outdoors, blue_sky, dagger, day, beach, hair_between_eyes, hibiscus, water, closed_mouth, holding, parted_lips, sheathed, black_capelet, collarbone, cowboy_shot, red_flower, sitting |
| 11 | 8 |  |  |  |  |  | 1girl, looking_at_viewer, nipples, blush, solo, barefoot, completely_nude, smile, ass, full_body, large_breasts, medium_breasts, navel, dakimakura_(medium), on_back |
| 12 | 10 |  |  |  |  |  | 1boy, 1girl, hetero, nipples, penis, blush, large_breasts, open_mouth, vaginal, solo_focus, thighhighs, cum_in_pussy, mosaic_censoring, spread_legs, straddling, breasts_out, clothed_sex, girl_on_top, navel, panties |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | breastplate | closed_mouth | red_shirt | solo | upper_body | looking_at_viewer | pauldrons | simple_background | smile | short_sleeves | cape | earrings | hair_between_eyes | white_background | holding_sword | miniskirt | red_gloves | thigh_boots | white_skirt | zettai_ryouiki | fingerless_gloves | shoulder_armor | red_footwear | full_body | rapier | red_thighhighs | standing | armor | skirt | thighhighs | shirt | open_mouth | blush | shiny_hair | alternate_hairstyle | cosplay | ponytail | official_alternate_costume | holding_polearm | spear | brown_gloves | belt | boots | hair_ornament | christmas | fur_trim | santa_costume | santa_hat | dress | red_headwear | holding_staff | hair_flower | bare_shoulders | wedding_dress | white_dress | yellow_bikini | navel | cleavage | off-shoulder_bikini | bracelet | hibiscus | necklace | two-tone_bikini | layered_bikini | bikini_skirt | innertube | medium_breasts | black_bikini | large_breasts | cloud | ocean | outdoors | blue_sky | dagger | day | beach | water | holding | parted_lips | sheathed | black_capelet | collarbone | cowboy_shot | red_flower | sitting | nipples | barefoot | completely_nude | ass | dakimakura_(medium) | on_back | 1boy | hetero | penis | vaginal | solo_focus | cum_in_pussy | mosaic_censoring | spread_legs | straddling | breasts_out | clothed_sex | girl_on_top | panties |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:--------------|:---------------|:------------|:-------|:-------------|:--------------------|:------------|:--------------------|:--------|:----------------|:-------|:-----------|:--------------------|:-------------------|:----------------|:------------|:-------------|:--------------|:--------------|:-----------------|:--------------------|:-----------------|:---------------|:------------|:---------|:-----------------|:-----------|:--------|:--------|:-------------|:--------|:-------------|:--------|:-------------|:----------------------|:----------|:-----------|:-----------------------------|:------------------|:--------|:---------------|:-------|:--------|:----------------|:------------|:-----------|:----------------|:------------|:--------|:---------------|:----------------|:--------------|:-----------------|:----------------|:--------------|:----------------|:--------|:-----------|:----------------------|:-----------|:-----------|:-----------|:------------------|:-----------------|:---------------|:------------|:-----------------|:---------------|:----------------|:--------|:--------|:-----------|:-----------|:---------|:------|:--------|:--------|:----------|:--------------|:-----------|:----------------|:-------------|:--------------|:-------------|:----------|:----------|:-----------|:------------------|:------|:----------------------|:----------|:-------|:---------|:--------|:----------|:-------------|:---------------|:-------------------|:--------------|:-------------|:--------------|:--------------|:--------------|:----------|
| 0 | 5 |  |  |  |  |  | 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 | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 6 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 6 |  |  |  |  |  | X | X | X | | X | X | X | | X | X | | X | X | | X | | | | | | | | | | | | | | | | | | | | | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 25 |  |  |  |  |  | X | X | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 8 | 9 |  |  |  |  |  | X | | 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 | 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 | X | | | | | | | | | | | | | | | | | | | |
| 11 | 8 |  |  |  |  |  | X | | | | X | | X | | | X | | | | | | | | | | | | | | | X | | | | | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | X | | X | | | | | | | | | | | | | | | | | X | X | X | X | X | X | | | | | | | | | | | | | |
| 12 | 10 |  |  |  |  |  | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | | X | X | | | | | | | | | | | | | | | | | | | | | | | | X | | | | | | | | | | | | X | | | | | | | | | | | | | | | | | X | | | | | | X | X | X | X | X | X | X | X | X | X | X | X | X |
| CyberHarem/eirik_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:35:47+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:34:22+00:00 |
5f6037055dc9cc31e821ef69a97394087300cbfc | AnzaniAI/ner_data | [
"license:mit",
"region:us"
] | 2024-01-17T11:37:05+00:00 | {"license": "mit"} | 2024-01-18T03:14:56+00:00 |
|
68c66948a91b29250fb7eb4ec2cb93a5b3e15f33 | Aneeth/job_description_7k | [
"region:us"
] | 2024-01-17T11:42:40+00:00 | {"dataset_info": {"features": [{"name": "Unnamed: 0", "dtype": "int64"}, {"name": "index", "dtype": "int64"}, {"name": "user_prompt", "dtype": "string"}, {"name": "model_response", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 12754354, "num_examples": 7000}, {"name": "validation", "num_bytes": 910258, "num_examples": 500}], "download_size": 3473642, "dataset_size": 13664612}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "validation", "path": "data/validation-*"}]}]} | 2024-01-17T11:46:35+00:00 |
|
f0a4329cf9f9027b095be7743a6db068fa425e5f |
This is a cleaned version from the Quora dataset that solves a single problem with the original dataset - sentences can have multiple ids. We also removed 2 rows from the original dataset that contained an empty string - this causes problem when trying to run an embedding because a empty string cannot... be embedded by OpenAI and has no valid representation?
Created to minimise data leakage from your train, test and validation sets by allowing you to segregate and split by ID. | 567-labs/cleaned-quora-dataset | [
"language:en",
"license:mit",
"region:us"
] | 2024-01-17T11:44:18+00:00 | {"language": ["en"], "license": "mit", "dataset_info": {"features": [{"name": "questions", "struct": [{"name": "id", "sequence": "int64"}, {"name": "text", "sequence": "string"}]}, {"name": "is_duplicate", "dtype": "bool"}], "splits": [{"name": "train", "num_bytes": 61389323, "num_examples": 404288}], "download_size": 36181628, "dataset_size": 61389323}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-29T14:31:06+00:00 |
29b6a8283f0060ca608994d2d1972e129ee68449 | Kamyar-zeinalipour/Protein-less-than-500 | [
"region:us"
] | 2024-01-17T11:49:04+00:00 | {"dataset_info": {"features": [{"name": "Cluster ID", "dtype": "string"}, {"name": "Cluster Name", "dtype": "string"}, {"name": "Types", "dtype": "string"}, {"name": "Size", "dtype": "int64"}, {"name": "Organisms", "dtype": "string"}, {"name": "Length", "dtype": "int64"}, {"name": "Identity", "dtype": "float64"}, {"name": "Reference_sequence", "dtype": "string"}, {"name": "Common taxon ID", "dtype": "int64"}, {"name": "Common taxon", "dtype": "string"}, {"name": "Organism IDs", "dtype": "string"}, {"name": "Cluster members", "dtype": "string"}, {"name": "Date of creation", "dtype": "string"}, {"name": "Reference sequence len", "dtype": "int64"}, {"name": "__index_level_0__", "dtype": "int64"}], "splits": [{"name": "train", "num_bytes": 27537377, "num_examples": 42000}, {"name": "test", "num_bytes": 973422, "num_examples": 1484}], "download_size": 14859478, "dataset_size": 28510799}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}, {"split": "test", "path": "data/test-*"}]}]} | 2024-01-17T17:26:02+00:00 |
|
943afd821c0f96ad9e0b6472ee60c10b668f81ae |
# Dataset of felicia/フェリシア (Fire Emblem)
This is the dataset of felicia/フェリシア (Fire Emblem), containing 258 images and their tags.
The core tags of this character are `long_hair, pink_hair, blue_eyes, maid_headdress, ponytail, breasts, bangs`, 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 | 258 | 288.01 MiB | [Download](https://huggingface.co/datasets/CyberHarem/felicia_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 258 | 175.99 MiB | [Download](https://huggingface.co/datasets/CyberHarem/felicia_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 572 | 350.61 MiB | [Download](https://huggingface.co/datasets/CyberHarem/felicia_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 258 | 259.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/felicia_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 572 | 480.32 MiB | [Download](https://huggingface.co/datasets/CyberHarem/felicia_fireemblem/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/felicia_fireemblem',
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, solo, long_sleeves, maid, smile, looking_at_viewer, puffy_sleeves, simple_background, open_mouth, white_background, apron, upper_body |
| 1 | 8 |  |  |  |  |  | 1girl, solo, knife, maid_apron, simple_background, weapon, black_thighhighs, holding, white_background, long_sleeves, open_mouth, smile, full_body, looking_at_viewer, puffy_sleeves, zettai_ryouiki, bridal_gauntlets, gem |
| 2 | 6 |  |  |  |  |  | 1boy, 1girl, blush, completely_nude, hetero, large_breasts, solo_focus, nipples, open_mouth, tongue_out, ahegao, heart-shaped_pupils, sweat, blunt_bangs, collarbone, doggystyle, saliva, sex_from_behind, simple_background, smile |
| 3 | 8 |  |  |  |  |  | 1boy, 1girl, hetero, open_mouth, sex, thighhighs, blush, maid, solo_focus, vaginal, large_breasts, nipples, penis, breasts_out, cum_in_pussy, spread_legs, uncensored, bar_censor, girl_on_top, heart-shaped_pupils, long_sleeves, lying, straddling |
| 4 | 6 |  |  |  |  |  | 1boy, blush, completely_nude, hetero, medium_breasts, navel, nipples, open_mouth, penis, sex, vaginal, 1girl, sweat, blunt_bangs, solo_focus, uncensored, cum_in_pussy |
| 5 | 5 |  |  |  |  |  | 1boy, 1girl, blush, hetero, penis, solo_focus, nipples, blunt_bangs, cum_in_mouth, large_breasts, looking_at_viewer, nude, pov, maid, mosaic_censoring, open_mouth, oral, paizuri, smile, tongue_out |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | solo | long_sleeves | maid | smile | looking_at_viewer | puffy_sleeves | simple_background | open_mouth | white_background | apron | upper_body | knife | maid_apron | weapon | black_thighhighs | holding | full_body | zettai_ryouiki | bridal_gauntlets | gem | 1boy | blush | completely_nude | hetero | large_breasts | solo_focus | nipples | tongue_out | ahegao | heart-shaped_pupils | sweat | blunt_bangs | collarbone | doggystyle | saliva | sex_from_behind | sex | thighhighs | vaginal | penis | breasts_out | cum_in_pussy | spread_legs | uncensored | bar_censor | girl_on_top | lying | straddling | medium_breasts | navel | cum_in_mouth | nude | pov | mosaic_censoring | oral | paizuri |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:---------------|:-------|:--------|:--------------------|:----------------|:--------------------|:-------------|:-------------------|:--------|:-------------|:--------|:-------------|:---------|:-------------------|:----------|:------------|:-----------------|:-------------------|:------|:-------|:--------|:------------------|:---------|:----------------|:-------------|:----------|:-------------|:---------|:----------------------|:--------|:--------------|:-------------|:-------------|:---------|:------------------|:------|:-------------|:----------|:--------|:--------------|:---------------|:--------------|:-------------|:-------------|:--------------|:--------|:-------------|:-----------------|:--------|:---------------|:-------|:------|:-------------------|:-------|:----------|
| 0 | 12 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | |
| 3 | 8 |  |  |  |  |  | X | | X | X | | | | | 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 | | | | | | |
| 5 | 5 |  |  |  |  |  | X | | | X | X | X | | | X | | | | | | | | | | | | | X | X | | X | X | X | X | X | | | | X | | | | | | | | X | | | | | | | | | | | X | X | X | X | X | X |
| CyberHarem/felicia_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:49:58+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T12:51:37+00:00 |
ed43c565e4d2a8d9d9db4e05ee6591b6f7061d99 |
# Dataset of olivia/オリヴィエ (Fire Emblem)
This is the dataset of olivia/オリヴィエ (Fire Emblem), containing 397 images and their tags.
The core tags of this character are `long_hair, pink_hair, braid, ponytail, twin_braids, hairband, breasts, pink_eyes, side_braid, 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 | 397 | 465.32 MiB | [Download](https://huggingface.co/datasets/CyberHarem/olivia_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 397 | 270.82 MiB | [Download](https://huggingface.co/datasets/CyberHarem/olivia_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 881 | 552.00 MiB | [Download](https://huggingface.co/datasets/CyberHarem/olivia_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 397 | 411.85 MiB | [Download](https://huggingface.co/datasets/CyberHarem/olivia_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 881 | 766.22 MiB | [Download](https://huggingface.co/datasets/CyberHarem/olivia_fireemblem/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/olivia_fireemblem',
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, simple_background, solo, bare_shoulders, closed_mouth, midriff, navel, blush, detached_sleeves, looking_at_viewer, o-ring, smile, twitter_username, upper_body, white_background, dancer, cleavage, grey_background |
| 1 | 7 |  |  |  |  |  | 1girl, bare_shoulders, looking_at_viewer, navel, simple_background, smile, solo, dancer, midriff, bridal_gauntlets, full_body, sandals, thighhighs, white_background |
| 2 | 10 |  |  |  |  |  | 1girl, ass, bare_shoulders, looking_at_viewer, smile, solo, see-through, simple_background, dancer, looking_back, from_behind, full_body |
| 3 | 5 |  |  |  |  |  | 1girl, ass, blush, from_behind, looking_at_viewer, looking_back, simple_background, solo, white_background, bare_shoulders, dancer, black_panties, bridal_gauntlets, thighhighs |
| 4 | 5 |  |  |  |  |  | 1girl, cleavage, fake_animal_ears, playboy_bunny, rabbit_ears, solo, alternate_costume, black_pantyhose, detached_collar, strapless_leotard, wrist_cuffs, bare_shoulders, full_body, high_heels, looking_at_viewer, open_mouth, simple_background, white_background, black_leotard, blush, bowtie, covered_navel, necktie, smile, white_leotard |
| 5 | 7 |  |  |  |  |  | 1boy, 1girl, blush, cum_in_pussy, hetero, penis, sex, vaginal, nipples, solo_focus, large_breasts, open_mouth, spread_legs, mosaic_censoring, nude, purple_eyes, thighhighs |
| 6 | 9 |  |  |  |  |  | 1boy, 1girl, blush, hetero, panties_aside, penis, sex, solo_focus, vaginal, nipples, open_mouth, pussy, spread_legs, thighhighs, white_panties, censored, large_breasts, navel, purple_eyes, sweat |
| 7 | 8 |  |  |  |  |  | 1boy, 1girl, blush, hetero, faceless_male, heart, simple_background, sweat, tongue_out, kiss, open_mouth, bare_shoulders, cleavage, armpits, bald, bridal_gauntlets, licking_armpit, midriff, navel, nude, upper_body |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | simple_background | solo | bare_shoulders | closed_mouth | midriff | navel | blush | detached_sleeves | looking_at_viewer | o-ring | smile | twitter_username | upper_body | white_background | dancer | cleavage | grey_background | bridal_gauntlets | full_body | sandals | thighhighs | ass | see-through | looking_back | from_behind | black_panties | fake_animal_ears | playboy_bunny | rabbit_ears | alternate_costume | black_pantyhose | detached_collar | strapless_leotard | wrist_cuffs | high_heels | open_mouth | black_leotard | bowtie | covered_navel | necktie | white_leotard | 1boy | cum_in_pussy | hetero | penis | sex | vaginal | nipples | solo_focus | large_breasts | spread_legs | mosaic_censoring | nude | purple_eyes | panties_aside | pussy | white_panties | censored | sweat | faceless_male | heart | tongue_out | kiss | armpits | bald | licking_armpit |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:--------------------|:-------|:-----------------|:---------------|:----------|:--------|:--------|:-------------------|:--------------------|:---------|:--------|:-------------------|:-------------|:-------------------|:---------|:-----------|:------------------|:-------------------|:------------|:----------|:-------------|:------|:--------------|:---------------|:--------------|:----------------|:-------------------|:----------------|:--------------|:--------------------|:------------------|:------------------|:--------------------|:--------------|:-------------|:-------------|:----------------|:---------|:----------------|:----------|:----------------|:-------|:---------------|:---------|:--------|:------|:----------|:----------|:-------------|:----------------|:--------------|:-------------------|:-------|:--------------|:----------------|:--------|:----------------|:-----------|:--------|:----------------|:--------|:-------------|:-------|:----------|:-------|:-----------------|
| 0 | 10 |  |  |  |  |  | X | X | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 2 | 10 |  |  |  |  |  | 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 | 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 | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 7 |  |  |  |  |  | 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 | | | 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 | X | X | X |
| CyberHarem/olivia_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:50:02+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:17:33+00:00 |
dfcc9898ac587e21245e006751ed4583e027163f |
# Dataset of paola/パオラ (Fire Emblem)
This is the dataset of paola/パオラ (Fire Emblem), containing 466 images and their tags.
The core tags of this character are `green_hair, long_hair, green_eyes, breasts, headband, 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 | 466 | 520.12 MiB | [Download](https://huggingface.co/datasets/CyberHarem/paola_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 466 | 320.94 MiB | [Download](https://huggingface.co/datasets/CyberHarem/paola_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1059 | 648.77 MiB | [Download](https://huggingface.co/datasets/CyberHarem/paola_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 466 | 474.15 MiB | [Download](https://huggingface.co/datasets/CyberHarem/paola_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1059 | 872.81 MiB | [Download](https://huggingface.co/datasets/CyberHarem/paola_fireemblem/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/paola_fireemblem',
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, elbow_gloves, green_footwear, solo, pegasus_knight_uniform_(fire_emblem), thigh_boots, green_skirt, dress, green_thighhighs, sitting, smile |
| 1 | 18 |  |  |  |  |  | 1girl, smile, solo, breastplate, looking_at_viewer, upper_body, simple_background, shoulder_armor, white_background, blush, elbow_gloves, closed_mouth |
| 2 | 11 |  |  |  |  |  | 1girl, dress, elbow_gloves, solo, thighhighs, green_gloves, side_slit, bare_shoulders, blush, simple_background, white_background, looking_at_viewer, polearm, sleeveless |
| 3 | 5 |  |  |  |  |  | 1girl, bangs, belt, breastplate, capelet, elbow_gloves, full_body, open_mouth, pelvic_curtain, shoulder_armor, solo, thigh_boots, thighhighs, thighs, white_footwear, white_gloves, gold_trim, shiny_hair, sleeveless, white_dress, holding_sword, medium_breasts, simple_background, white_background, hand_on_own_chest, hand_up, high_heel_boots, looking_at_viewer, sheathed, short_dress, smile, standing, transparent_background |
| 4 | 11 |  |  |  |  |  | 1girl, nipples, nude, smile, solo, looking_at_viewer, blush, navel |
| 5 | 6 |  |  |  |  |  | 1girl, blush, completely_nude, navel, nipples, spread_legs, bangs, female_pubic_hair, mosaic_censoring, on_back, open_mouth, solo, looking_at_viewer, pillow, smile, spread_pussy |
| 6 | 5 |  |  |  |  |  | 1girl, blush, navel, nipples, open_mouth, solo, sweat, armpits, arms_behind_head, arms_up, bangs, completely_nude, female_pubic_hair, looking_at_viewer, cowboy_shot, very_long_hair, white_headband |
| 7 | 14 |  |  |  |  |  | 1boy, 1girl, hetero, solo_focus, nipples, penis, thighhighs, vaginal, blush, cum_in_pussy, elbow_gloves, open_mouth, female_pubic_hair, mosaic_censoring, girl_on_top, spread_legs, torn_clothes, breasts_out, clothed_sex, cowgirl_position, medium_breasts, tears, rape |
| 8 | 8 |  |  |  |  |  | 1girl, navel, solo, cleavage, looking_at_viewer, collarbone, simple_background, smile, white_background, bangs, bare_shoulders, blush, green_bikini, stomach, armpits, thigh_gap |
| 9 | 5 |  |  |  |  |  | 1girl, bare_shoulders, smile, solo, blush, elbow_gloves, hair_flower, looking_at_viewer, simple_background, white_background, white_gloves, bangs, official_alternate_costume, green_dress, green_footwear, medium_breasts, open_mouth, skirt, sleeveless_dress, thigh_boots, thighhighs, upper_body |
| 10 | 36 |  |  |  |  |  | fake_animal_ears, rabbit_ears, 1girl, solo, cleavage, playboy_bunny, smile, pantyhose, white_gloves, choker, hair_flower, rabbit_tail, leotard, simple_background, looking_at_viewer, blush, open_mouth, see-through, white_background |
| 11 | 7 |  |  |  |  |  | 1boy, 1girl, hetero, solo_focus, nude, open_mouth, blush, censored, licking_penis, tongue_out, bangs, cum, sweat |
| 12 | 5 |  |  |  |  |  | 1girl, anus, blush, elbow_gloves, female_pubic_hair, outdoors, pussy, thighhighs, bar_censor, looking_at_viewer, no_panties, open_mouth, solo, squatting, thigh_boots, white_headband, day, peeing, sky, ass, bare_shoulders, brown_gloves, bush, dress, green_footwear, green_gloves, looking_back, sleeveless, spread_legs |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | elbow_gloves | green_footwear | solo | pegasus_knight_uniform_(fire_emblem) | thigh_boots | green_skirt | dress | green_thighhighs | sitting | smile | breastplate | looking_at_viewer | upper_body | simple_background | shoulder_armor | white_background | blush | closed_mouth | thighhighs | green_gloves | side_slit | bare_shoulders | polearm | sleeveless | bangs | belt | capelet | full_body | open_mouth | pelvic_curtain | thighs | white_footwear | white_gloves | gold_trim | shiny_hair | white_dress | holding_sword | medium_breasts | hand_on_own_chest | hand_up | high_heel_boots | sheathed | short_dress | standing | transparent_background | nipples | nude | navel | completely_nude | spread_legs | female_pubic_hair | mosaic_censoring | on_back | pillow | spread_pussy | sweat | armpits | arms_behind_head | arms_up | cowboy_shot | very_long_hair | white_headband | 1boy | hetero | solo_focus | penis | vaginal | cum_in_pussy | girl_on_top | torn_clothes | breasts_out | clothed_sex | cowgirl_position | tears | rape | cleavage | collarbone | green_bikini | stomach | thigh_gap | hair_flower | official_alternate_costume | green_dress | skirt | sleeveless_dress | fake_animal_ears | rabbit_ears | playboy_bunny | pantyhose | choker | rabbit_tail | leotard | see-through | censored | licking_penis | tongue_out | cum | anus | outdoors | pussy | bar_censor | no_panties | squatting | day | peeing | sky | ass | brown_gloves | bush | looking_back |
|----:|----------:|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:----------------------------------|:--------|:---------------|:-----------------|:-------|:---------------------------------------|:--------------|:--------------|:--------|:-------------------|:----------|:--------|:--------------|:--------------------|:-------------|:--------------------|:-----------------|:-------------------|:--------|:---------------|:-------------|:---------------|:------------|:-----------------|:----------|:-------------|:--------|:-------|:----------|:------------|:-------------|:-----------------|:---------|:-----------------|:---------------|:------------|:-------------|:--------------|:----------------|:-----------------|:--------------------|:----------|:------------------|:-----------|:--------------|:-----------|:-------------------------|:----------|:-------|:--------|:------------------|:--------------|:--------------------|:-------------------|:----------|:---------|:---------------|:--------|:----------|:-------------------|:----------|:--------------|:-----------------|:-----------------|:-------|:---------|:-------------|:--------|:----------|:---------------|:--------------|:---------------|:--------------|:--------------|:-------------------|:--------|:-------|:-----------|:-------------|:---------------|:----------|:------------|:--------------|:-----------------------------|:--------------|:--------|:-------------------|:-------------------|:--------------|:----------------|:------------|:---------|:--------------|:----------|:--------------|:-----------|:----------------|:-------------|:------|:-------|:-----------|:--------|:-------------|:-------------|:------------|:------|:---------|:------|:------|:---------------|:-------|:---------------|
| 0 | 5 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 18 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 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 | 11 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 5 |  |  |  |  |  | X | | | X | | | | | | | | | X | | | | | X | | | | | | | | X | | | | X | | | | | | | | | | | | | | | | | X | | X | X | | X | | | | | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 7 | 14 |  |  |  |  |  | X | X | | | | | | | | | | | | | | | | X | | X | | | | | | | | | | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 9 | 5 |  |  |  |  |  | X | X | X | X | | X | | | | | X | | X | X | X | | X | X | | X | | | X | | | X | | | | X | | | | X | | | | | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | |
| 10 | 36 |  |  |  |  |  | X | | | X | | | | | | | X | | X | | X | | X | 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 | | | | | | | | | | | | | |
| 12 | 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 |
| CyberHarem/paola_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:50:10+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:24:34+00:00 |
d2623048d49ddb62a45217bb0edb7e0e72c552d0 |
# Dataset of lucina/#ルキナ (Fire Emblem)
This is the dataset of lucina/#ルキナ (Fire Emblem), containing 500 images and their tags.
The core tags of this character are `blue_hair, blue_eyes, long_hair, hair_between_eyes, breasts, bangs`, 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 | 655.53 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lucina_fireemblem/resolve/main/dataset-raw.zip) | Waifuc-Raw | Raw data with meta information (min edge aligned to 1400 if larger). |
| 800 | 500 | 371.92 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lucina_fireemblem/resolve/main/dataset-800.zip) | IMG+TXT | dataset with the shorter side not exceeding 800 pixels. |
| stage3-p480-800 | 1138 | 759.97 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lucina_fireemblem/resolve/main/dataset-stage3-p480-800.zip) | IMG+TXT | 3-stage cropped dataset with the area not less than 480x480 pixels. |
| 1200 | 500 | 577.49 MiB | [Download](https://huggingface.co/datasets/CyberHarem/lucina_fireemblem/resolve/main/dataset-1200.zip) | IMG+TXT | dataset with the shorter side not exceeding 1200 pixels. |
| stage3-p480-1200 | 1138 | 1.05 GiB | [Download](https://huggingface.co/datasets/CyberHarem/lucina_fireemblem/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/lucina_fireemblem',
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 | 27 |  |  |  |  |  | 1girl, cape, falchion_(fire_emblem), solo, sword, tiara, fingerless_gloves, armor, looking_at_viewer, smile |
| 1 | 11 |  |  |  |  |  | 1girl, cape, falchion_(fire_emblem), solo, tiara, armor, fingerless_gloves, looking_at_viewer, holding_sword, simple_background, belt |
| 2 | 5 |  |  |  |  |  | 1girl, cape, simple_background, solo, tiara, white_background, looking_at_viewer, polearm, shield, armored_boots, full_body, holding_weapon, official_alternate_costume, shoulder_armor, smile |
| 3 | 7 |  |  |  |  |  | 1girl, bare_shoulders, hair_flower, looking_at_viewer, official_alternate_costume, solo, white_dress, cleavage, sleeveless_dress, smile, blush, closed_mouth, collarbone, symbol-shaped_pupils, armlet, small_breasts |
| 4 | 5 |  |  |  |  |  | 1girl, crop_top, looking_at_viewer, midriff, navel, short_shorts, solo, tiara, bare_shoulders, blush, official_alternate_costume, small_breasts, open_mouth, simple_background, sleeveless, thighs, white_background, :d, arm_up, armpits, belt, bikini, blue_shorts, innertube |
| 5 | 7 |  |  |  |  |  | 1girl, day, navel, smile, solo, tiara, blue_bikini, crop_top, looking_at_viewer, midriff, outdoors, armpits, bare_shoulders, cloud, ocean, short_shorts, small_breasts, water, alternate_costume, arm_up, beach, belt, blue_sky, blush, closed_mouth, cowboy_shot, innertube, sleeveless, thighs, tree, wet |
| 6 | 6 |  |  |  |  |  | 1girl, alternate_breast_size, large_breasts, smile, solo, looking_at_viewer, navel, tiara, blue_bikini, patreon_username |
| 7 | 11 |  |  |  |  |  | 1girl, tiara, 1boy, hetero, nipples, penis, solo_focus, blush, navel, pussy, uncensored, completely_nude, spread_legs, looking_at_viewer, open_mouth, sex, vaginal, cum, pubic_hair, small_breasts, clitoris, lying, pov, sweat |
| 8 | 18 |  |  |  |  |  | 1girl, looking_at_viewer, solo, alternate_costume, orange_shorts, short_shorts, tiara, waitress, beer_mug, smile, cleavage, employee_uniform, blush, medium_breasts, open_mouth, white_tank_top, chicken_(food), holding_plate, navel, tray |
| 9 | 12 |  |  |  |  |  | 1girl, looking_at_viewer, playboy_bunny, rabbit_ears, solo, fake_animal_ears, official_alternate_costume, smile, leotard, white_pantyhose, rabbit_tail, blush, cleavage, egg, open_mouth, simple_background, frills, small_breasts, choker, puffy_short_sleeves, white_background, white_gloves |
### Table Version
| # | Samples | Img-1 | Img-2 | Img-3 | Img-4 | Img-5 | 1girl | cape | falchion_(fire_emblem) | solo | sword | tiara | fingerless_gloves | armor | looking_at_viewer | smile | holding_sword | simple_background | belt | white_background | polearm | shield | armored_boots | full_body | holding_weapon | official_alternate_costume | shoulder_armor | bare_shoulders | hair_flower | white_dress | cleavage | sleeveless_dress | blush | closed_mouth | collarbone | symbol-shaped_pupils | armlet | small_breasts | crop_top | midriff | navel | short_shorts | open_mouth | sleeveless | thighs | :d | arm_up | armpits | bikini | blue_shorts | innertube | day | blue_bikini | outdoors | cloud | ocean | water | alternate_costume | beach | blue_sky | cowboy_shot | tree | wet | alternate_breast_size | large_breasts | patreon_username | 1boy | hetero | nipples | penis | solo_focus | pussy | uncensored | completely_nude | spread_legs | sex | vaginal | cum | pubic_hair | clitoris | lying | pov | sweat | orange_shorts | waitress | beer_mug | employee_uniform | medium_breasts | white_tank_top | chicken_(food) | holding_plate | tray | playboy_bunny | rabbit_ears | fake_animal_ears | leotard | white_pantyhose | rabbit_tail | egg | frills | choker | puffy_short_sleeves | white_gloves |
|----:|----------:|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------------------------------|:--------|:-------|:-------------------------|:-------|:--------|:--------|:--------------------|:--------|:--------------------|:--------|:----------------|:--------------------|:-------|:-------------------|:----------|:---------|:----------------|:------------|:-----------------|:-----------------------------|:-----------------|:-----------------|:--------------|:--------------|:-----------|:-------------------|:--------|:---------------|:-------------|:-----------------------|:---------|:----------------|:-----------|:----------|:--------|:---------------|:-------------|:-------------|:---------|:-----|:---------|:----------|:---------|:--------------|:------------|:------|:--------------|:-----------|:--------|:--------|:--------|:--------------------|:--------|:-----------|:--------------|:-------|:------|:------------------------|:----------------|:-------------------|:-------|:---------|:----------|:--------|:-------------|:--------|:-------------|:------------------|:--------------|:------|:----------|:------|:-------------|:-----------|:--------|:------|:--------|:----------------|:-----------|:-----------|:-------------------|:-----------------|:-----------------|:-----------------|:----------------|:-------|:----------------|:--------------|:-------------------|:----------|:------------------|:--------------|:------|:---------|:---------|:----------------------|:---------------|
| 0 | 27 |  |  |  |  |  | X | X | X | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 1 | 11 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 3 | 7 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 5 | 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 | X | X | X | X | X | X | X | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| 6 | 6 |  |  |  |  |  | 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 | | | | | | | | | | | | | | | | | | | | |
| 8 | 18 |  |  |  |  |  | X | | | X | | X | | | X | X | | | | | | | | | | | | | | | X | | 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 | X | X | X | X | X | X | X | X | X |
| CyberHarem/lucina_fireemblem | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | 2024-01-17T11:50:26+00:00 | {"license": "mit", "size_categories": ["n<1K"], "task_categories": ["text-to-image"], "tags": ["art", "not-for-all-audiences"]} | 2024-01-17T13:39:21+00:00 |
b9823848cfa321c2408f38bc08501a3e03379474 | VitinDJ/VozesBR | [
"license:unknown",
"region:us"
] | 2024-01-17T11:52:03+00:00 | {"license": "unknown"} | 2024-01-17T12:25:39+00:00 |
|
9fb64fa5af6e3d4a2d0ebf3906980754f9e4dc6d |
We collect a 2.5B training dataset from various domains for long-context continual pre-training. The composition of this dataset is as follows (partially inspired by [Long-Data-Collection](https://huggingface.co/datasets/togethercomputer/Long-Data-Collections)):
| Domain | Proportion | Source |
| ------------- | ---------- | ------ |
| Book | 40% | [Redpajama-Book](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) |
| Arxiv | 20% | [Redpajama-Arxiv](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) |
| General | 20% | [Redpajama](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) |
| Code | 10% | [LCC-Python](https://huggingface.co/datasets/microsoft/LCC_python) |
| QA | 5% | [Natural Questions](https://ai.google.com/research/NaturalQuestions/) |
| Summarization | 5% | [BookSum](https://github.com/salesforce/booksum) |
We have also curated a test dataset comprising 250 million tokens, mirroring the same composition. The selection criteria ensured that the average n-gram similarity (for n=2, 3, 4) with the training set is below 10%. This threshold effectively excludes all QA and Summarization data, resulting in a test corpus where the distribution of tokens across Book, Arxiv, General, and Code categories follows a ratio of 4:2:2:1, respectively. | DAMO-NLP-SG/LongCorpus-2.5B | [
"task_categories:text-generation",
"license:mit",
"region:us"
] | 2024-01-17T11:56:31+00:00 | {"license": "mit", "task_categories": ["text-generation"], "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train_*"}, {"split": "test", "path": "data/test_*"}]}]} | 2024-01-19T18:15:18+00:00 |
844aa403486950f583e399578cb11f89fa05f87f |
# Forecasting Future World Events with Neural Networks
This is an (unofficial) repository for "[Forecasting Future World Events with Neural Networks](http://arxiv.org/abs/2206.15474)"
by [Andy Zou](https://andyzoujm.github.io/), [Tristan Xiao](https://www.linkedin.com/in/tristan-xiao/), [Ryan Jia](https://www.linkedin.com/in/ryanjia/), [Joe Kwon](joekwon.io), [Mantas Mazeika](https://www.linkedin.com/in/mmazeika/), [Richard Li](https://www.linkedin.com/in/lirichard23/), [Dawn Song](https://people.eecs.berkeley.edu/~dawnsong/), [Jacob Steinhardt](https://www.stat.berkeley.edu/~jsteinhardt/), [Owain Evans](https://owainevans.github.io/), and [Dan Hendrycks](https://danhendrycks.com/).
<img align="center" src="assets/splash.png" width="750">
## Introduction
Forecasting future world events is a challenging but valuable task. Forecasts of climate, geopolitical conflict, pandemics and economic indicators help shape policy and decision making. In these domains, the judgment of expert humans contributes to the best forecasts. Given advances in language modeling, can these forecasts be automated? To this end, we introduce Autocast, a dataset containing thousands of forecasting questions and an accompanying news corpus. Questions are taken from forecasting tournaments, ensuring high quality, real-world importance, and diversity. The news corpus is organized by date, allowing us to precisely simulate the conditions under which humans made past forecasts (avoiding leakage from the future). We test language models on our forecasting task and find that performance is far below a human expert baseline. However, performance improves with increased model size and incorporation of relevant information from the news corpus. In sum, Autocast poses a novel challenge for large language models and improved performance could bring large practical benefits.
## Autocast Dataset
The original version of the [Autocast dataset can be downloaded here](https://people.eecs.berkeley.edu/~hendrycks/autocast.tar.gz). For more details on how to use the Autocast dataset and news articles, please refer to our short demonstration in `usage.ipynb`.
Each question has the following fields:
```json
{
"id": "unique identifier (str)",
"question": "question body (str)",
"background": "question context/details (str)",
"qtype": "question type (str)",
"status": "question status (str)",
"choices": "choices or possible ranges (List or Dict)",
"answer": "question resolution (str or float)",
"crowd": "human crowd forecasts over time (List)",
"publish_time": "publish timestamp (str)",
"close_time": "close timestamp (str)",
"prediction_count": "number of crowd predictions (int)",
"forecaster_count": "number of crowd forecasters (int)",
"tags": "question category (List)",
"source_links": "source links from comments (List)"
}
```
The authors obtained permission from [Metaculus](https://www.metaculus.com/) to host the dataset on GitHub for research purposes only.
## IntervalQA Dataset
Motivated by the difficulty of forecasting numbers across orders of magnitude (e.g. global cases of COVID-19 in 2022), we also curate IntervalQA, a dataset of numerical questions and metrics for calibration.
[Download the IntervalQA dataset here](https://people.eecs.berkeley.edu/~hendrycks/intervalqa.tar.gz).
## Citation
If you find this useful in your research, please consider citing:
@article{zouforecasting2022,
title={Forecasting Future World Events with Neural Networks},
author={Andy Zou and Tristan Xiao and Ryan Jia and Joe Kwon and Mantas Mazeika and Richard Li and Dawn Song and Jacob Steinhardt and Owain Evans and Dan Hendrycks},
journal={NeurIPS},
year={2022}
} | AlgoveraAI/autocast | [
"task_categories:time-series-forecasting",
"arxiv:2206.15474",
"region:us"
] | 2024-01-17T12:05:02+00:00 | {"task_categories": ["time-series-forecasting"]} | 2024-01-23T11:34:41+00:00 |
5f21c760463aa605b3952bde9f472e39c8a17eac | reza-alipour/muse-landmark-0 | [
"region:us"
] | 2024-01-17T12:05:23+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "caption", "dtype": "string"}, {"name": "caption_fre", "dtype": "string"}, {"name": "caption_deu", "dtype": "string"}, {"name": "caption_ita", "dtype": "string"}, {"name": "caption_spa", "dtype": "string"}, {"name": "generated_mask", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 578425461.5, "num_examples": 1500}], "download_size": 230627940, "dataset_size": 578425461.5}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T14:23:48+00:00 |
|
5ef2c5b8df689c7eb2cad93b9f0edb68aac3eda8 | # Dataset Card for "20000-50000-ultrafeedback-binarized-preferences-cleaned-ita"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | giux78/20000-50000-ultrafeedback-binarized-preferences-cleaned-ita | [
"region:us"
] | 2024-01-17T12:12:21+00:00 | {"dataset_info": {"features": [{"name": "source", "dtype": "string"}, {"name": "prompt", "dtype": "string"}, {"name": "chosen", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "chosen-rating", "dtype": "float64"}, {"name": "chosen-model", "dtype": "string"}, {"name": "rejected", "list": [{"name": "content", "dtype": "string"}, {"name": "role", "dtype": "string"}]}, {"name": "rejected-rating", "dtype": "float64"}, {"name": "rejected-model", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 197228907, "num_examples": 30000}], "download_size": 87134816, "dataset_size": 197228907}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T12:12:28+00:00 |
38a0b0594135a3e018458ccadb5a972e764f4d04 | elissilva/sheldon | [
"license:openrail",
"region:us"
] | 2024-01-17T12:24:11+00:00 | {"license": "openrail"} | 2024-01-17T12:36:18+00:00 |
|
5bbd59a5492d377df916a2d712aa40078c9a32d6 | trooaditya/image_data_set | [
"region:us"
] | 2024-01-17T12:37:04+00:00 | {"dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 193266.0, "num_examples": 10}], "download_size": 97794, "dataset_size": 193266.0}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T12:37:05+00:00 |
|
159620e7bfe560252ecd1d68aa4f78ed23f339b5 | marcones/marconesofertas | [
"license:openrail",
"region:us"
] | 2024-01-17T12:39:15+00:00 | {"license": "openrail"} | 2024-01-17T12:39:41+00:00 |
|
34dd6ba200632b59b97f93bcd05b953d77842cdb | zjsfxpm1/1231231 | [
"license:mit",
"region:us"
] | 2024-01-17T12:39:40+00:00 | {"license": "mit"} | 2024-01-17T12:39:40+00:00 |
|
348b5298c715ae7a38883de2a59fb3aaf4e6842d | MBassNoBeat/japaozinvoz | [
"license:openrail",
"region:us"
] | 2024-01-17T12:51:26+00:00 | {"license": "openrail"} | 2024-01-17T12:52:36+00:00 |
|
3ef2a4a8880bd74c0517eb2ba4b17137ad33115e | reza-alipour/m-landmark-generated | [
"region:us"
] | 2024-01-17T13:02:13+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "caption", "dtype": "string"}, {"name": "caption_fre", "dtype": "string"}, {"name": "caption_deu", "dtype": "string"}, {"name": "caption_ita", "dtype": "string"}, {"name": "caption_spa", "dtype": "string"}, {"name": "generated_mask", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 1148441048.756, "num_examples": 2998}], "download_size": 779602659, "dataset_size": 1148441048.756}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T15:36:11+00:00 |
|
d244355319e9eda251e3adce4ebb4ea2f3e4751e | reza-alipour/m-mask-generated | [
"region:us"
] | 2024-01-17T13:03:01+00:00 | {"dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "image", "dtype": "image"}, {"name": "mask", "dtype": "image"}, {"name": "caption", "dtype": "string"}, {"name": "caption_fre", "dtype": "string"}, {"name": "caption_deu", "dtype": "string"}, {"name": "caption_ita", "dtype": "string"}, {"name": "caption_spa", "dtype": "string"}, {"name": "generated_mask", "dtype": "image"}], "splits": [{"name": "train", "num_bytes": 1188331922.75, "num_examples": 2998}], "download_size": 819495595, "dataset_size": 1188331922.75}, "configs": [{"config_name": "default", "data_files": [{"split": "train", "path": "data/train-*"}]}]} | 2024-01-17T13:03:40+00:00 |
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