id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
kye/lucidrains-python-3-8192-mistral-7b | 2023-10-05T18:10:47.000Z | [
"region:us"
] | kye | null | null | 0 | 0 | 2023-10-05T18:10:27 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
splits:
- name: train
num_bytes: 167436216
num_examples: 4087
download_size: 38766555
dataset_size: 167436216
---
# Dataset Card for "lucidrains-python-3-8192-mistral-7b"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 433 | [
[
-0.019073486328125,
-0.005641937255859375,
0.012298583984375,
0.027862548828125,
-0.018280029296875,
-0.02752685546875,
0.0174713134765625,
-0.0132293701171875,
0.04876708984375,
0.037261962890625,
-0.03692626953125,
-0.032989501953125,
-0.028167724609375,
0... |
JoSw-14/chem-5000-10000 | 2023-10-05T19:06:07.000Z | [
"region:us"
] | JoSw-14 | null | null | 0 | 0 | 2023-10-05T19:06:07 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
BangumiBase/tatenoyuushanonariagari | 2023-10-05T22:00:17.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T19:20:42 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Tate No Yuusha No Nariagari
This is the image base of bangumi Tate no Yuusha no Nariagari, we detected 50 characters, 4925 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 264 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 62 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 18 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 52 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 16 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 93 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 1176 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 89 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 29 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 111 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 33 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 47 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 35 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 33 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 42 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 24 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 13 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 170 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 244 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 82 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 17 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 87 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 19 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 21 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 9 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 746 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 113 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 192 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 66 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 105 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 23 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 13 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 11 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 17 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 53 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 9 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 13 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 17 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 49 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 13 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 12 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 8 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 170 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 6 | [Download](43/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 44 | 13 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 13 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 7 | [Download](46/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 47 | 5 | [Download](47/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 48 | 46 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 419 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 16,935 | [
[
-0.042388916015625,
-0.009552001953125,
0.008941650390625,
0.01093292236328125,
-0.01506805419921875,
-0.00583648681640625,
-0.0021038055419921875,
-0.0239410400390625,
0.040008544921875,
0.02996826171875,
-0.059539794921875,
-0.053466796875,
-0.04083251953125,
... |
BangumiBase/shinmaimaounotestament | 2023-10-05T21:15:54.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T19:20:56 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Shinmai Maou No Testament
This is the image base of bangumi Shinmai Maou no Testament, we detected 35 characters, 3166 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 811 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 58 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 67 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 24 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 49 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 14 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 19 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 6 | [Download](7/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 8 | 9 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 11 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 31 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 58 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 120 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 97 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 22 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 11 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 43 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 27 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 14 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 541 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 12 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 11 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 9 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 20 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 9 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 6 | [Download](25/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 26 | 7 | [Download](26/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 27 | 348 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 26 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 43 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 11 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 40 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 15 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 12 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 565 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 12,221 | [
[
-0.041290283203125,
-0.0083770751953125,
0.0108489990234375,
0.0146026611328125,
-0.016845703125,
-0.005954742431640625,
-0.0009946823120117188,
-0.0226898193359375,
0.039520263671875,
0.031463623046875,
-0.057708740234375,
-0.05511474609375,
-0.042633056640625,... |
BangumiBase/godeater | 2023-10-05T20:37:58.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T19:21:12 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of God Eater
This is the image base of bangumi GOD EATER, we detected 23 characters, 1589 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 31 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 6 | [Download](1/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 2 | 176 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 22 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 49 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 527 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 32 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 28 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 15 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 17 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 50 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 124 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 26 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 24 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 10 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 9 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 24 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 61 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 121 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 131 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 16 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 6 | [Download](21/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 84 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 8,421 | [
[
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0.00972747802734375,
0.010345458984375,
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0.00322723388671875,
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0.043212890625,
0.0306243896484375,
-0.056549072265625,
-0.051055908203125,
-0.044189453125,
... |
vijayvaidya832/patient-survival | 2023-10-05T19:35:36.000Z | [
"region:us"
] | vijayvaidya832 | null | null | 0 | 0 | 2023-10-05T19:35:36 | Entry not found | 15 | [
[
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0.052490234375,
0.00507354736328125,
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0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
autoevaluate/autoeval-eval-squad-plain_text-5877ef-93263145810 | 2023-10-05T20:17:21.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T20:17:17 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
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0.0379... |
autoevaluate/autoeval-eval-squad-plain_text-7a9df8-93264145811 | 2023-10-05T20:17:24.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T20:17:20 | Entry not found | 15 | [
[
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-0.01494598388671875,
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0.03790... |
autoevaluate/autoeval-eval-squad-plain_text-7a9df8-93264145812 | 2023-10-05T20:17:30.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T20:17:26 | Entry not found | 15 | [
[
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0.01702880859375,
-0.052093505859375,
-0.01494598388671875,
-0.06036376953125,
0.03790... |
autoevaluate/autoeval-eval-squad-plain_text-7a9df8-93264145813 | 2023-10-05T20:17:37.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T20:17:34 | Entry not found | 15 | [
[
-0.021392822265625,
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0.01702880859375,
-0.052093505859375,
-0.01494598388671875,
-0.06036376953125,
0.03790... |
autoevaluate/autoeval-eval-squad-plain_text-7a9df8-93264145814 | 2023-10-05T20:17:44.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T20:17:40 | Entry not found | 15 | [
[
-0.021392822265625,
-0.01494598388671875,
0.05718994140625,
0.028839111328125,
-0.0350341796875,
0.046539306640625,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.01702880859375,
-0.052093505859375,
-0.01494598388671875,
-0.06036376953125,
0.03790... |
acozma/fill50k | 2023-10-05T21:31:15.000Z | [
"region:us"
] | acozma | null | null | 0 | 0 | 2023-10-05T20:22:49 | ---
dataset_info:
features:
- name: image
dtype: image
- name: conditioning_image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 451820630.0
num_examples: 50000
download_size: 323967497
dataset_size: 451820630.0
---
# Dataset Card for "fill50k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 439 | [
[
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0.033935546875,
-0.06500244140625,
-0.04559326171875,
-0.032623291015625,
-0.... |
TheBossLevel123/minillama | 2023-10-05T20:40:11.000Z | [
"region:us"
] | TheBossLevel123 | null | null | 0 | 0 | 2023-10-05T20:39:29 | Entry not found | 15 | [
[
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0.028839111328125,
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0.01702880859375,
-0.052093505859375,
-0.01494598388671875,
-0.06036376953125,
0.03790... |
BangumiBase/sangatsunolion | 2023-10-05T23:19:37.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T20:54:08 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Sangatsu No Lion
This is the image base of bangumi Sangatsu no Lion, we detected 33 characters, 3830 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 1087 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 167 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 205 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 49 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 126 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 39 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 179 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 96 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 264 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 111 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 29 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 34 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 19 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 44 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 56 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 27 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 28 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 405 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 203 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 13 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 16 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 142 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 20 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 8 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 23 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 23 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 46 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 55 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 9 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 8 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 39 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 9 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 251 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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Arodrigo/llamadas_celular_voz_es | 2023-10-05T21:06:08.000Z | [
"region:us"
] | Arodrigo | null | null | 0 | 0 | 2023-10-05T21:04:49 | Entry not found | 15 | [
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BangumiBase/mahoutsukainoyome | 2023-10-05T22:27:53.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T21:09:24 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Mahou Tsukai No Yome
This is the image base of bangumi Mahou Tsukai no Yome, we detected 28 characters, 1731 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 899 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 20 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 11 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 44 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 39 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 19 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 19 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 17 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 20 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 37 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 20 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 15 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 13 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 14 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 85 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 34 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 60 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 58 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 5 | [Download](19/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 20 | 19 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 13 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 18 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 12 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 16 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 7 | [Download](25/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 26 | 21 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 182 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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ddfff6677/f | 2023-10-31T23:26:50.000Z | [
"region:us"
] | ddfff6677 | null | null | 0 | 0 | 2023-10-05T22:26:23 | Entry not found | 15 | [
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bslota/yay | 2023-10-05T22:30:47.000Z | [
"region:us"
] | bslota | null | null | 0 | 0 | 2023-10-05T22:30:47 | Entry not found | 15 | [
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feynman-integrals-nn/t331ZZZM-s12_24 | 2023-10-17T17:20:44.000Z | [
"license:cc-by-4.0",
"region:us"
] | feynman-integrals-nn | null | null | 0 | 0 | 2023-10-05T22:31:36 | ---
license: cc-by-4.0
---
# t331ZZZM
* [data](https://huggingface.co/datasets/feynman-integrals-nn/t331ZZZM-s12_24)
* [model](https://huggingface.co/feynman-integrals-nn/t331ZZZM-dimensionless)
* [source](https://gitlab.com/feynman-integrals-nn/feynman-integrals-nn/-/tree/main/t331ZZZM)
Warning: deprecated dataset
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feynman-integrals-nn/heavycrossbox | 2023-10-05T23:30:41.000Z | [
"license:cc-by-4.0",
"region:us"
] | feynman-integrals-nn | null | null | 0 | 0 | 2023-10-05T22:54:33 | ---
license: cc-by-4.0
---
# heavycrossbox
* [data](https://huggingface.co/datasets/feynman-integrals-nn/heavycrossbox)
* [source](https://gitlab.com/feynman-integrals-nn/feynman-integrals-nn/-/tree/main/heavycrossbox)
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feynman-integrals-nn/topbox | 2023-10-05T23:30:47.000Z | [
"license:cc-by-4.0",
"region:us"
] | feynman-integrals-nn | null | null | 0 | 0 | 2023-10-05T22:54:49 | ---
license: cc-by-4.0
---
# topbox
* [data](https://huggingface.co/datasets/feynman-integrals-nn/topbox)
* [source](https://gitlab.com/feynman-integrals-nn/feynman-integrals-nn/-/tree/main/topbox)
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alessisheinman/hi | 2023-10-05T22:56:00.000Z | [
"region:us"
] | alessisheinman | null | null | 0 | 0 | 2023-10-05T22:56:00 | Entry not found | 15 | [
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feynman-integrals-nn/box1m | 2023-10-06T10:12:45.000Z | [
"license:cc-by-4.0",
"region:us"
] | feynman-integrals-nn | null | null | 0 | 0 | 2023-10-05T23:02:24 | ---
license: cc-by-4.0
---
# box1m
* [data](https://huggingface.co/datasets/feynman-integrals-nn/box1m)
* [source](https://gitlab.com/feynman-integrals-nn/feynman-integrals-nn/-/tree/main/box1m)
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JeremiahZ/mbxp_llvm_wasm | 2023-10-05T23:22:33.000Z | [
"region:us"
] | JeremiahZ | null | null | 0 | 0 | 2023-10-05T23:22:30 | ---
dataset_info:
features:
- name: task_id
dtype: string
- name: language
dtype: string
- name: prompt
dtype: string
- name: description
dtype: string
- name: test
dtype: string
- name: entry_point
dtype: string
- name: canonical_solution
dtype: string
- name: llvm_ir
dtype: string
- name: wat
dtype: string
splits:
- name: test
num_bytes: 13548211
num_examples: 773
download_size: 2857975
dataset_size: 13548211
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# Dataset Card for "hmbxp_llvm_wasm"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 744 | [
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AIRES-PUCRS/chest_xray | 2023-10-05T23:43:05.000Z | [
"region:us"
] | AIRES-PUCRS | null | null | 0 | 0 | 2023-10-05T23:40:18 | Entry not found | 15 | [
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Reza8848/MUFFIN_68k | 2023-10-17T20:56:55.000Z | [
"size_categories:10K<n<100K",
"language:en",
"region:us"
] | Reza8848 | null | null | 1 | 0 | 2023-10-05T23:41:51 | ---
language:
- en
size_categories:
- 10K<n<100K
---
<img src="https://cdn-uploads.huggingface.co/production/uploads/6434a6e8ea46c009904c617e/J_4FHXmtM6TuRnN3aL06y.png" width="38" height="38">
This is the training dataset of **MUFFIN** (**Mu**lti-**F**aceted **In**structions).
Please refer to our project website for more details: [Website](https://renzelou.github.io/Muffin/)
## JSON Format
The download data can be read as a Python list.
In this list, each elemental Python dictionary has one input text.
This input text has multiple task instructions and the corresponding outputs.
```json
[
{
"input": "XXX",
"instances": [
{ "instruction": "III", "output": "YYY" },
{ "instruction": "III", "output": "YYY" }
]
}
,
{
"input": "XXX",
"instances": [
{ "instruction": "III", "output": "YYY" }
]
}
]
```
## Data Statistics
There are a total of 1,463 input texts, where each input is equipped with multiple task instructions (~46.48 instructions per input), resulting in **68,014** training instances in total.
The detailed statistics are shown below:
<div style="text-align:center"><img src="https://cdn-uploads.huggingface.co/production/uploads/6434a6e8ea46c009904c617e/hcQjRr1TqX08C4tMnEQaZ.png" alt="statistics.png" width="500"/></div>
## 🥳 Citation
Please kindly cite our paper if you use our dataset:
```
TODO
```
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joey234/tweet_eval_affix_pos | 2023-10-23T02:30:18.000Z | [
"region:us"
] | joey234 | null | null | 0 | 0 | 2023-10-05T23:43:59 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': negative
'1': neutral
'2': positive
- name: words_with_affixes
sequence: string
splits:
- name: test
num_bytes: 76536
num_examples: 609
download_size: 49267
dataset_size: 76536
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# Dataset Card for "tweet_eval_affix_pos"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 620 | [
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nian0448/data | 2023-10-16T14:05:34.000Z | [
"region:us"
] | nian0448 | null | null | 0 | 0 | 2023-10-06T00:42:44 | Entry not found | 15 | [
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Kaludi/BDA594-fake-news-classification | 2023-10-06T01:59:55.000Z | [
"task_categories:text-classification",
"region:us"
] | Kaludi | null | null | 0 | 0 | 2023-10-06T01:25:31 | ---
task_categories:
- text-classification
---
# AutoTrain Dataset for project: test13
## Dataset Description
This dataset has been processed for project BDA594-fake-news-classification model.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"text": "MOSCOW\u2014Warning President Volodymyr Zelensky think carefully repercussions changing country\u2019s college football conference alignment, Russian president Vladimir Putin reportedly vowed retaliation Friday Ukraine ever become member Big Ten. \u201cThere absolutely reason Ukraine needs join Big Ten outside provoking Russia, move apply membership met harshest consequences,\u201d said Putin, pointing Ukraine\u2019s position neutral firewall countries long served geographical buffer Russia Big Ten members like Indiana University Rutgers. \u201cAny move even increase number games Ukraine Big Ten schools considered act aggression Russian state met proportionate force. universities stoking hostility Russia decades, caution Ukraine indulge thirst power. Frankly, Zelensky\u2019s good. know University Michigan cofounded Big Ten years ago vehicle nefarious interests NCAA Division sports, urge Ukraine become puppet [University Michigan athletic director] Alan Haller prolonged proxy season Big Ten schools Russia.\u201d press time, tensions rising Russia pulled ambassador Penn State. Watch Biden Asks Americans Come Sit Keep Company End CC Share Subtitles English Share Video Facebook Twitter Email Reddit Link view video Biden Asks Americans Come Sit Keep Company End Week's Viral News: September 22, 2023 Friday 2:58PM Study Finds LSD Highly Effective Ruining Nephew\u2019s Baptism Thursday 10:44AM",
"target": 0
},
{
"text": "Coast Guard searching 35yearold man fell overboard Carnival cruise ship near Florida Monday, according statement . man passenger Carnival Magic cruise ship, 186 miles east Jacksonville fell water. Security footage shows leaned railing room balcony fell water around 4:10 a.m. Monday, cruise corporation said statement. reported missing companion late Monday afternoon. Officials released identifying information man age. cruise ship released Coast Guard search rescue efforts continue way Norfolk, Virginia, scheduled arrive Tuesday. \"The Carnival Care Team providing support guest\u2019s companion traveling party board,\" Carnival said. Coast Guard using air water assets search passenger.",
"target": 1
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(names=['fake', 'real'], id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 508 |
| valid | 128 |
| 2,919 | [
[
-0.036041259765625,
-0.0304718017578125,
0.01953125,
0.0229644775390625,
-0.029632568359375,
-0.0053558349609375,
0.0015583038330078125,
-0.028656005859375,
0.0272064208984375,
0.0175323486328125,
-0.0306243896484375,
-0.03839111328125,
-0.032562255859375,
0... |
abeiler/Numeric_and_Alpha_Instruct_Arithmetic | 2023-10-06T01:37:22.000Z | [
"region:us"
] | abeiler | null | null | 0 | 0 | 2023-10-06T01:36:42 | Entry not found | 15 | [
[
-0.02142333984375,
-0.014984130859375,
0.057220458984375,
0.0288238525390625,
-0.03509521484375,
0.04656982421875,
0.052520751953125,
0.00506591796875,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060455322265625,
0.03793334... |
dread1900/Anarchist-CSGO | 2023-10-06T01:40:08.000Z | [
"region:us"
] | dread1900 | null | null | 0 | 0 | 2023-10-06T01:39:01 | Entry not found | 15 | [
[
-0.02142333984375,
-0.014984130859375,
0.057220458984375,
0.0288238525390625,
-0.03509521484375,
0.04656982421875,
0.052520751953125,
0.00506591796875,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060455322265625,
0.03793334... |
daytoy-models/coronary-artery | 2023-10-23T07:33:43.000Z | [
"task_categories:text-classification",
"task_categories:table-question-answering",
"task_categories:zero-shot-classification",
"task_categories:summarization",
"task_categories:sentence-similarity",
"task_categories:text-to-audio",
"size_categories:1B<n<10B",
"size_categories:1K",
"language:en",
"... | daytoy-models | null | null | 0 | 0 | 2023-10-06T02:11:55 | ---
license: lgpl-lr
language:
- en
tags:
- chemistry
- biology
size_categories:
- 1B<n<10B
- 1K
task_categories:
- text-classification
- table-question-answering
- zero-shot-classification
- summarization
- sentence-similarity
- text-to-audio
pretty_name: abc
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
### Dataset Sources [optional]
<!-- Provide the basic links for the dataset. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
[More Information Needed]
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
[More Information Needed]
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
[More Information Needed]
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
[More Information Needed]
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
[More Information Needed]
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Annotation process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
[More Information Needed]
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
[More Information Needed]
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Citation [optional]
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
**APA:**
[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Dataset Card Authors [optional]
[More Information Needed]
## Dataset Card Contact
[More Information Needed] | 4,625 | [
[
-0.04034423828125,
-0.0419921875,
0.00977325439453125,
0.0178070068359375,
-0.0300445556640625,
-0.00891876220703125,
-0.0026874542236328125,
-0.048431396484375,
0.043212890625,
0.059478759765625,
-0.05938720703125,
-0.069580078125,
-0.042205810546875,
0.009... |
ZhaoweiWang/COPES | 2023-10-06T03:02:33.000Z | [
"region:us"
] | ZhaoweiWang | null | null | 0 | 0 | 2023-10-06T03:02:06 | All commonsense causal data is in COPES.json.
The data is recorded in the format of json records with three fileds:
1. story: the story of 5 sentences sampled from RocStories.
2. cause_idx: the events that have a causal relation with the last event (indices start from 0).
3. res_idx: the result, just the last event.
The split_idx.json provide the indices for validation and testing data, indexing from 0.
| 408 | [
[
-0.01561737060546875,
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0.055572509765625,
0.00664520263671875,
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0.032257080078125,
0.052093505859375,
-0.051605224609375,
-0.03668212890625,
-0.0262756347... |
dummyuser/gene | 2023-10-06T03:03:26.000Z | [
"region:us"
] | dummyuser | null | null | 0 | 0 | 2023-10-06T03:03:26 | Entry not found | 15 | [
[
-0.02142333984375,
-0.014984130859375,
0.057220458984375,
0.0288238525390625,
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0.052520751953125,
0.00506591796875,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060455322265625,
0.03793334... |
dummyuser/genAI | 2023-10-06T03:17:54.000Z | [
"region:us"
] | dummyuser | null | null | 0 | 0 | 2023-10-06T03:17:54 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
-0.035064697265625,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
mariamjamal001/kws_bg | 2023-10-06T03:55:50.000Z | [
"region:us"
] | mariamjamal001 | null | null | 0 | 0 | 2023-10-06T03:37:22 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
-0.035064697265625,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
BangumiBase/maoujoudeoyasumi | 2023-10-06T05:15:32.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T04:14:03 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Maoujou De Oyasumi
This is the image base of bangumi Maoujou de Oyasumi, we detected 21 characters, 1076 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 9 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 12 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 17 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 22 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 195 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 21 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 46 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 8 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 36 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 9 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 72 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 69 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 15 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 15 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 10 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 10 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 12 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 396 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 21 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 21 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 60 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,811 | [
[
-0.042083740234375,
-0.009613037109375,
0.0087127685546875,
0.01381683349609375,
-0.015777587890625,
-0.005893707275390625,
-0.003875732421875,
-0.0237579345703125,
0.03839111328125,
0.03314208984375,
-0.05792236328125,
-0.052978515625,
-0.04180908203125,
0.... |
BangumiBase/punchline | 2023-10-06T05:17:13.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T04:14:19 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Punch Line
This is the image base of bangumi Punch Line, we detected 17 characters, 1203 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 104 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 12 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 134 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 47 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 135 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 16 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 11 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 14 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 14 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 21 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 18 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 40 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 150 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 324 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 14 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 9 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 140 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 6,539 | [
[
-0.04315185546875,
-0.01241302490234375,
0.00820159912109375,
0.01505279541015625,
-0.0180206298828125,
-0.00616455078125,
0.0003402233123779297,
-0.0238037109375,
0.038604736328125,
0.03466796875,
-0.05810546875,
-0.05194091796875,
-0.04150390625,
0.0301818... |
BangumiBase/suzumiyaharuhinoyuuutsu | 2023-10-06T07:11:00.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T04:31:09 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Suzumiya Haruhi No Yuuutsu
This is the image base of bangumi Suzumiya Haruhi no Yuuutsu, we detected 22 characters, 4994 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 1639 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 563 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 606 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 72 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 27 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 103 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 796 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 23 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 22 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 453 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 124 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 67 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 19 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 49 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 13 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 34 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 48 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 12 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 44 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 57 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 5 | [Download](20/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 218 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 8,141 | [
[
-0.0433349609375,
-0.01050567626953125,
0.0088653564453125,
0.01222991943359375,
-0.0169219970703125,
-0.006046295166015625,
-0.0025196075439453125,
-0.022613525390625,
0.04132080078125,
0.032318115234375,
-0.059722900390625,
-0.05224609375,
-0.04052734375,
... |
frank-chieng/python_datamining | 2023-10-11T03:55:49.000Z | [
"region:us"
] | frank-chieng | null | null | 0 | 0 | 2023-10-06T04:41:37 | Entry not found | 15 | [
[
-0.0214080810546875,
-0.01496124267578125,
0.057159423828125,
0.02880859375,
-0.0350341796875,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.05206298828125,
-0.01497650146484375,
-0.060302734375,
0.0379638... |
phongmt184172/python_code_version2 | 2023-10-06T04:46:06.000Z | [
"region:us"
] | phongmt184172 | null | null | 0 | 0 | 2023-10-06T04:44:12 | Entry not found | 15 | [
[
-0.0214080810546875,
-0.01496124267578125,
0.057159423828125,
0.02880859375,
-0.0350341796875,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.05206298828125,
-0.01497650146484375,
-0.060302734375,
0.0379638... |
BangumiBase/fireforce | 2023-10-06T08:11:49.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T04:46:39 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Fire Force
This is the image base of bangumi Fire Force, we detected 60 characters, 5217 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 1278 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 231 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 55 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 65 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 89 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 30 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 73 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 140 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 47 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 56 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 264 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 25 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 41 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 173 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 73 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 35 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 23 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 70 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 23 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 26 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 57 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 34 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 156 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 29 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 218 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 34 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 67 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 20 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 42 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 33 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 69 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 34 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 41 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 177 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 36 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 299 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 52 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 135 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 26 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 26 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 5 | [Download](40/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 41 | 25 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 15 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 12 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 22 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 17 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 85 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 12 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 85 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 33 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 37 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 17 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 122 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
| 53 | 25 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 60 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 13 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 6 | [Download](56/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 57 | 5 | [Download](57/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 58 | 10 | [Download](58/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 209 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 20,041 | [
[
-0.042205810546875,
-0.00780487060546875,
0.007305145263671875,
0.01328277587890625,
-0.01528167724609375,
-0.0026760101318359375,
-0.0010080337524414062,
-0.0199737548828125,
0.039306640625,
0.030853271484375,
-0.058807373046875,
-0.053466796875,
-0.04235839843... |
BangumiBase/zetsuennotempest | 2023-10-06T06:18:35.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T04:46:59 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Zetsuen No Tempest
This is the image base of bangumi Zetsuen no Tempest, we detected 16 characters, 2070 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 75 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 405 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 19 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 435 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 15 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 35 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 40 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 124 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 10 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 28 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 402 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 88 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 55 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 40 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 175 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 124 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 6,241 | [
[
-0.04644775390625,
-0.00911712646484375,
0.01153564453125,
0.01568603515625,
-0.016876220703125,
-0.00644683837890625,
-0.0008645057678222656,
-0.0240325927734375,
0.039520263671875,
0.035247802734375,
-0.0599365234375,
-0.05523681640625,
-0.040069580078125,
... |
BangumiBase/violetevergarden | 2023-10-06T08:00:10.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T05:43:11 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Violet Evergarden
This is the image base of bangumi Violet Evergarden, we detected 72 characters, 4728 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 32 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 166 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 16 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 23 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 160 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 66 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 17 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 13 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 23 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 15 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 38 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 30 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 31 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 23 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 15 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 34 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 104 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 23 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 103 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 75 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 32 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 27 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 21 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 25 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 19 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 13 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 22 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 180 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 39 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 156 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 21 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 70 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 23 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 180 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 12 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 39 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 58 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 108 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 27 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 38 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 32 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 335 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 84 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 16 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 94 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 19 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 67 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 20 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 79 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 17 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 9 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 6 | [Download](52/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 53 | 34 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 12 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 31 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 33 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 17 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 24 | [Download](58/dataset.zip) |  |  |  |  |  |  |  |  |
| 59 | 1282 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 20 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 10 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 8 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 20 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| 64 | 12 | [Download](64/dataset.zip) |  |  |  |  |  |  |  |  |
| 65 | 14 | [Download](65/dataset.zip) |  |  |  |  |  |  |  |  |
| 66 | 80 | [Download](66/dataset.zip) |  |  |  |  |  |  |  |  |
| 67 | 9 | [Download](67/dataset.zip) |  |  |  |  |  |  |  |  |
| 68 | 14 | [Download](68/dataset.zip) |  |  |  |  |  |  |  |  |
| 69 | 10 | [Download](69/dataset.zip) |  |  |  |  |  |  |  |  |
| 70 | 9 | [Download](70/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 178 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 23,823 | [
[
-0.038665771484375,
-0.00774383544921875,
0.007659912109375,
0.0155487060546875,
-0.015655517578125,
-0.006458282470703125,
0.0006909370422363281,
-0.0220184326171875,
0.037200927734375,
0.031890869140625,
-0.05865478515625,
-0.0552978515625,
-0.04010009765625,
... |
BirdL/DONOTUSEDATA-SideB | 2023-10-07T21:46:48.000Z | [
"not-for-all-audiences",
"region:us"
] | BirdL | null | null | 0 | 0 | 2023-10-06T06:14:16 | ---
dataset_info:
features:
- name: text
dtype: string
- name: sexual
dtype: float64
- name: hate
dtype: float64
- name: violence
dtype: float64
- name: self-harm
dtype: float64
- name: sexual/minors
dtype: float64
- name: hate/threatening
dtype: float64
- name: violence/graphic
dtype: float64
splits:
- name: train
num_bytes: 6855523
num_examples: 30002
download_size: 5665789
dataset_size: 6855523
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- not-for-all-audiences
---
# Dataset Card for "DONOTUSEDATA-SideB"
Studying the effects of harmful data on LLMs. Side B.
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 814 | [
[
-0.0214691162109375,
-0.03997802734375,
0.020233154296875,
0.0133209228515625,
-0.0266265869140625,
-0.01299285888671875,
0.03204345703125,
-0.0084686279296875,
0.0640869140625,
0.060272216796875,
-0.056427001953125,
-0.049560546875,
-0.0380859375,
-0.019363... |
skbose-fold/wizmap-datasets | 2023-10-30T13:22:45.000Z | [
"region:us"
] | skbose-fold | null | null | 0 | 0 | 2023-10-06T06:40:43 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
-0.035064697265625,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
HotDaddy/hdv2 | 2023-10-06T06:46:30.000Z | [
"region:us"
] | HotDaddy | null | null | 0 | 0 | 2023-10-06T06:44:30 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
-0.035064697265625,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
ai4ce/EgoPAT3Dv2 | 2023-10-30T05:55:27.000Z | [
"language:en",
"robotics",
"region:us"
] | ai4ce | null | null | 0 | 0 | 2023-10-06T07:15:55 | ---
language:
- en
tags:
- robotics
---
There are 11 scenes contained in the dataset from folder 1 to folder 11. Each scene folder contains several video folders represent each recorded videos under that scene. Each video folder contains a RGB folder, a depth folder, a point cloud folder and a ground truth folder. If you want to use this EgoPAT3Dv2 dataset's RGB modality as we do, you need to generate HDF5 file on your own with the script we provided(about 500GB since huggingface doesn't support that large file):
1. Download all of these scene folders. Extract each video folder from video zip files in the scene folder using unzip command and delete all useless files inside.
2. To use RGB modality, you need to create a new separate folder which has the same hierarchy as the scene-video-rgb structure. Put the previously extracted RGB folders for each scene each video into the same place as the original one. For example, color folder in ***"1/1.1/color"*** should be put into ***"RGB_file/1/1.1"*** as ***"RGB_file/1/1.1/color"***.
3. Run script make_RGB_dataset.py.
Then you can use the provided RGBDataset tool to load dataset and create the dataloader. | 1,172 | [
[
-0.060394287109375,
-0.036163330078125,
0.007251739501953125,
0.03179931640625,
-0.01074981689453125,
-0.0245819091796875,
0.028350830078125,
-0.012359619140625,
0.01030731201171875,
0.04595947265625,
-0.0787353515625,
-0.0159759521484375,
-0.0235595703125,
... |
minh21/COVID-QA-question-answering-biencoder-data-75_25 | 2023-10-06T07:38:59.000Z | [
"region:us"
] | minh21 | null | null | 0 | 0 | 2023-10-06T07:38:55 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context_chunks
sequence: string
- name: document_id
dtype: int64
- name: id
dtype: int64
splits:
- name: train
num_bytes: 59010693
num_examples: 1348
- name: validation
num_bytes: 4567041
num_examples: 158
download_size: 13833996
dataset_size: 63577734
---
# Dataset Card for "COVID-QA-question-answering-biencoder-data-75_25"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 749 | [
[
-0.043121337890625,
-0.0228271484375,
0.007305145263671875,
0.01001739501953125,
-0.0119781494140625,
-0.002132415771484375,
0.03338623046875,
-0.0017910003662109375,
0.04168701171875,
0.019287109375,
-0.056427001953125,
-0.04852294921875,
-0.02703857421875,
... |
minh21/COVID-QA-testset-biencoder-data-65_25_10 | 2023-10-06T07:47:57.000Z | [
"region:us"
] | minh21 | null | null | 0 | 0 | 2023-10-06T07:47:56 | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context_chunks
sequence: string
- name: document_id
dtype: int64
- name: id
dtype: int64
- name: context
dtype: string
splits:
- name: train
num_bytes: 16708455
num_examples: 201
download_size: 442083
dataset_size: 16708455
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "COVID-QA-testset-biencoder-data-65_25_10"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 658 | [
[
-0.03253173828125,
-0.00824737548828125,
-0.00450897216796875,
0.01523590087890625,
-0.0164794921875,
-0.00640106201171875,
0.030059814453125,
-0.004657745361328125,
0.04351806640625,
0.005260467529296875,
-0.0474853515625,
-0.051055908203125,
-0.030014038085937... |
minh21/COVID-QA-question-answering-biencoder-data-65_25_10 | 2023-10-06T07:48:19.000Z | [
"region:us"
] | minh21 | null | null | 0 | 0 | 2023-10-06T07:48:16 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context_chunks
sequence: string
- name: document_id
dtype: int64
- name: id
dtype: int64
splits:
- name: train
num_bytes: 55383294
num_examples: 1170
- name: validation
num_bytes: 5172033
num_examples: 140
download_size: 16954453
dataset_size: 60555327
---
# Dataset Card for "COVID-QA-question-answering-biencoder-data-65_25_10"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 752 | [
[
-0.041046142578125,
-0.022552490234375,
0.004772186279296875,
0.01139068603515625,
-0.0107574462890625,
-0.0062255859375,
0.033233642578125,
-0.0054168701171875,
0.041290283203125,
0.01482391357421875,
-0.054351806640625,
-0.0460205078125,
-0.0280609130859375,
... |
flozi00/single-queries-german | 2023-10-27T09:26:52.000Z | [
"task_categories:text2text-generation",
"task_categories:text-generation",
"language:de",
"license:apache-2.0",
"region:us"
] | flozi00 | null | null | 0 | 0 | 2023-10-06T07:56:58 | ---
language:
- de
license: apache-2.0
task_categories:
- text2text-generation
- text-generation
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 17678
num_examples: 57
download_size: 0
dataset_size: 17678
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "single-queries-german"
[Converted from here](https://github.com/flozi00/atra/blob/main/_selfquery.txt) | 514 | [
[
-0.034942626953125,
-0.0406494140625,
0.0165252685546875,
0.0095672607421875,
-0.04290771484375,
-0.0158538818359375,
0.002033233642578125,
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0.042083740234375,
0.060089111328125,
-0.05859375,
-0.071533203125,
-0.005336761474609375,
-0.... |
metral/ranobe_sample | 2023-10-06T08:25:32.000Z | [
"language:ja",
"license:apache-2.0",
"region:us"
] | metral | null | null | 1 | 0 | 2023-10-06T08:05:28 | ---
license: apache-2.0
language:
- ja
---
# What is this?
This is the text of my novel. It has approximately 240,000 words.
The genre is fantasy light novel.
# What is the licence?
The licence type is Apache 2.0.
# How can I use it?
I want you to use this novel as a sample of Japanese writing.
After that, you are free to use it within the scope of the licence.
You can send me fan letters :)
# Are there any precautions I should be aware of?
This text is still available on Kakuyom. The unique format for its publication has been retained. Please note that some of the formatting, such as ruby and highlighted characters, are not found in normal Japanese texts.
* https://kakuyomu.jp/help/entry/notation
# Others.
If you have any questions, please feel free to contact the HuggingFace community. | 802 | [
[
-0.02734375,
-0.047607421875,
0.023712158203125,
0.061553955078125,
-0.0491943359375,
-0.019195556640625,
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0.0694580078125,
-0.0413818359375,
-0.0177001953125,
-0.038238525390625,
0.037872314453125,
-... |
minh21/COVID-QA-testset-biencoder-data-45_45_10 | 2023-10-06T08:08:08.000Z | [
"region:us"
] | minh21 | null | null | 0 | 0 | 2023-10-06T08:08:06 | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context_chunks
sequence: string
- name: document_id
dtype: int64
- name: id
dtype: int64
- name: context
dtype: string
splits:
- name: train
num_bytes: 16708455
num_examples: 201
download_size: 442083
dataset_size: 16708455
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "COVID-QA-testset-biencoder-data-45_45_10"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 658 | [
[
-0.036285400390625,
-0.005596160888671875,
-0.005130767822265625,
0.0188140869140625,
-0.0181884765625,
-0.0017499923706054688,
0.0292205810546875,
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0.044586181640625,
0.004459381103515625,
-0.0511474609375,
-0.049591064453125,
-0.0324707031... |
minh21/COVID-QA-question-answering-biencoder-data-45_45_10 | 2023-10-06T08:08:24.000Z | [
"region:us"
] | minh21 | null | null | 0 | 0 | 2023-10-06T08:08:22 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: context_chunks
sequence: string
- name: document_id
dtype: int64
- name: id
dtype: int64
splits:
- name: train
num_bytes: 40708361
num_examples: 814
- name: validation
num_bytes: 5112241
num_examples: 94
download_size: 12639574
dataset_size: 45820602
---
# Dataset Card for "COVID-QA-question-answering-biencoder-data-45_45_10"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 750 | [
[
-0.044647216796875,
-0.020477294921875,
0.004150390625,
0.014923095703125,
-0.0122528076171875,
-0.0011777877807617188,
0.03265380859375,
-0.003719329833984375,
0.042266845703125,
0.01447296142578125,
-0.0582275390625,
-0.044464111328125,
-0.0301055908203125,
... |
Iceclear/StableSR-TestSets | 2023-10-06T08:46:40.000Z | [
"task_categories:image-to-image",
"license:other",
"arxiv:2305.07015",
"region:us"
] | Iceclear | null | null | 1 | 0 | 2023-10-06T08:24:37 | ---
license: other
license_name: ntu-slab-license
license_link: https://github.com/IceClear/StableSR/blob/main/LICENSE.txt
task_categories:
- image-to-image
---
# StableSR TestSets Card
These test sets are used associated with the StableSR, available [here](https://github.com/IceClear/StableSR).
## Data Details
- **Developed by:** Jianyi Wang
- **Data type:** Synthetic and real-world test sets for image super-resolution
- **License:** [S-Lab License 1.0](https://github.com/IceClear/StableSR/blob/main/LICENSE.txt)
- **Data Description:** The test sets are used to reproduce the metric results shown in [Paper](https://arxiv.org/abs/2305.07015).
- **Resources for more information:** [GitHub Repository](https://github.com/IceClear/StableSR).
- **Cite as:**
@InProceedings{wang2023exploiting,
author = {Wang, Jianyi and Yue, Zongsheng and Zhou, Shangchen and Chan, Kelvin CK and Loy, Chen Change},
title = {Exploiting Diffusion Prior for Real-World Image Super-Resolution},
booktitle = {arXiv preprint arXiv:2305.07015},
year = {2023},
}
# Uses
Please refer to [S-Lab License 1.0](https://github.com/IceClear/StableSR/blob/main/LICENSE.txt)
We currently provide the following test sets:
- DIV2K_Val: 3000 synthetic data pairs on the validation of [DIV2K](https://data.vision.ee.ethz.ch/cvl/DIV2K/) generated used the same degradation used for training StableSR.
- RealSR Val: Center-cropped data pairs on [RealSRv3](https://github.com/csjcai/RealSR).
- DRealSR Val: Center-cropped data pairs on [DRealSR](https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution).
- DPED Val: Center-cropped LQ-only data on [DPED](https://github.com/aiff22/DPED).
## Evaluation Results
See [Paper](https://arxiv.org/abs/2305.07015) for details. | 1,839 | [
[
-0.04168701171875,
-0.032867431640625,
0.0012722015380859375,
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-0.0382080078125,
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0.0261688232421875,
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0.01300811767578125,
0.01470947265625,
-0.035736083984375,
-0.026947021484375,
-0.02984619140625,... |
gillkabir/expanded_dataset2 | 2023-10-06T08:29:24.000Z | [
"region:us"
] | gillkabir | null | null | 0 | 0 | 2023-10-06T08:28:56 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
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0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
pphuc25/data_trigger | 2023-10-06T08:43:55.000Z | [
"region:us"
] | pphuc25 | null | null | 0 | 0 | 2023-10-06T08:43:52 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': '0'
'1': '1'
splits:
- name: train
num_bytes: 469024
num_examples: 3400
- name: test
num_bytes: 77263
num_examples: 600
download_size: 316166
dataset_size: 546287
---
# Dataset Card for "data_trigger"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 508 | [
[
-0.039825439453125,
-0.0189666748046875,
0.00434112548828125,
0.00881195068359375,
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0.016021728515625,
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0.04986572265625,
0.0177154541015625,
-0.06561279296875,
-0.05169677734375,
-0.042266845703125,
-... |
johannes-garstenauer/embeddings_from_distilbert_class_heaps_and_eval_part0_test | 2023-10-06T09:08:02.000Z | [
"region:us"
] | johannes-garstenauer | null | null | 0 | 0 | 2023-10-06T09:07:53 | ---
dataset_info:
features:
- name: struct
dtype: string
- name: label
dtype: int64
- name: pred
dtype: int64
- name: cls_layer_6
sequence: float32
- name: cls_layer_5
sequence: float32
- name: cls_layer_4
sequence: float32
splits:
- name: train
num_bytes: 13428556
num_examples: 1408
download_size: 16665816
dataset_size: 13428556
---
# Dataset Card for "embeddings_from_distilbert_class_heaps_and_eval_part0_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 602 | [
[
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0.0325927734375,
0.0169677734375,
0.04876708984375,
0.0102081298828125,
-0.031646728515625,
-0.05621337890625,
-0.043212890625,
-0.01817321777... |
johannes-garstenauer/embeddings_from_distilbert_class_heaps_and_eval_part1_test | 2023-10-06T09:08:19.000Z | [
"region:us"
] | johannes-garstenauer | null | null | 0 | 0 | 2023-10-06T09:08:12 | ---
dataset_info:
features:
- name: struct
dtype: string
- name: label
dtype: int64
- name: pred
dtype: int64
- name: cls_layer_6
sequence: float32
- name: cls_layer_5
sequence: float32
- name: cls_layer_4
sequence: float32
splits:
- name: train
num_bytes: 12230881
num_examples: 1283
download_size: 14966255
dataset_size: 12230881
---
# Dataset Card for "embeddings_from_distilbert_class_heaps_and_eval_part1_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 602 | [
[
-0.037872314453125,
-0.0465087890625,
0.0176544189453125,
0.0214996337890625,
-0.012359619140625,
0.00531768798828125,
0.034881591796875,
0.019287109375,
0.0496826171875,
0.0118560791015625,
-0.035675048828125,
-0.0576171875,
-0.0450439453125,
-0.02075195312... |
BangumiBase/angelsofdeath | 2023-10-06T10:20:16.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T09:10:12 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Angels Of Death
This is the image base of bangumi Angels of Death, we detected 8 characters, 1201 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 621 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 243 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 80 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 15 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 92 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 84 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 8 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 58 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 3,722 | [
[
-0.043182373046875,
-0.014190673828125,
0.016845703125,
0.021514892578125,
-0.0205535888671875,
-0.0014171600341796875,
0.01395416259765625,
-0.0224456787109375,
0.033966064453125,
0.047515869140625,
-0.06005859375,
-0.06298828125,
-0.04486083984375,
0.02667... |
BangumiBase/littlewitchacademia | 2023-10-06T10:59:11.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T09:10:35 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Little Witch Academia
This is the image base of bangumi Little Witch Academia, we detected 41 characters, 3200 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 803 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 62 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 61 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 26 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 12 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 106 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 63 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 35 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 16 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 21 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 181 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 28 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 21 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 61 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 26 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 11 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 40 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 115 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 27 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 11 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 41 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 16 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 189 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 8 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 21 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 31 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 27 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 111 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 265 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 30 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 21 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 29 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 66 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 35 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 20 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 41 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 38 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 30 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 11 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 8 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 436 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 14,097 | [
[
-0.042266845703125,
-0.0110321044921875,
0.01023101806640625,
0.0113525390625,
-0.01496124267578125,
-0.004520416259765625,
-0.001636505126953125,
-0.0252227783203125,
0.039398193359375,
0.03076171875,
-0.057342529296875,
-0.053619384765625,
-0.043701171875,
... |
BangumiBase/nichijou | 2023-10-06T10:48:11.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T09:11:08 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Nichijou
This is the image base of bangumi Nichijou, we detected 33 characters, 2652 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 346 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 16 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 51 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 449 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 105 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 10 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 75 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 91 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 73 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 16 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 479 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 33 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 72 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 75 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 79 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 19 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 17 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 80 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 30 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 181 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 16 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 15 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 36 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 100 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 13 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 33 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 14 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 7 | [Download](27/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 28 | 9 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 14 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 12 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 22 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 64 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 11,559 | [
[
-0.042755126953125,
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Falah/mosque_forest_image_prompts | 2023-10-06T09:35:08.000Z | [
"region:us"
] | Falah | null | null | 0 | 0 | 2023-10-06T09:35:07 | ---
dataset_info:
features:
- name: prompts
dtype: string
splits:
- name: train
num_bytes: 3517254
num_examples: 10000
download_size: 150520
dataset_size: 3517254
---
# Dataset Card for "mosque_forest_image_prompts"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 372 | [
[
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BangumiBase/eizoukenniwateodasuna | 2023-10-06T10:40:16.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T09:55:51 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Eizouken Ni Wa Te O Dasu Na!
This is the image base of bangumi Eizouken ni wa Te o Dasu na!, we detected 17 characters, 1057 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 235 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 290 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 225 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 16 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 28 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 38 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 30 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 23 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 12 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 13 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 12 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 10 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 12 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 8 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 42 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 10 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 53 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 6,575 | [
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DGurgurov/maltese_data | 2023-10-07T13:20:05.000Z | [
"region:us"
] | DGurgurov | null | null | 0 | 0 | 2023-10-06T10:00:15 | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc/guide: https://huggingface.co/docs/hub/datasets-cards
{}
---
### Dataset Summary
This repository comprises two distinct datasets focusing on Maltese:
1. **Maltese Words and Their Relationships from ConceptNet**
This dataset includes Maltese words and their respective relationships, sourced from ConceptNet.
2. **Maltese Words and Their English Glosses from Gabra**
Dataset containing Maltese words and their corresponding English glosses, extracted from the Gabra database.
### Languages
- Maltese
## Dataset Creation
- The data was extracted from ConceptNet and Gabra for further use in training PPMI embeddings.
### Contributors
- Daniil Gurgurov
| 802 | [
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DGurgurov/maltese_embeddings | 2023-10-07T13:16:44.000Z | [
"region:us"
] | DGurgurov | null | null | 0 | 0 | 2023-10-06T10:08:51 | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc/guide: https://huggingface.co/docs/hub/datasets-cards
{}
---
### Dataset Summary
This repository contains three distinct datasets focusing on Maltese word embeddings:
1. **GloVe Maltese Word Embeddings**
Embeddings generated using GloVe on the "korpus_malti" dataset, the largest Maltese corpus available.
2. **Word2Vec Maltese Word Embeddings**
Word embeddings for Maltese obtained using Word2Vec trained on the "korpus_malti" dataset.
3. **PPMI Maltese Word Embeddings**
Pointwise Mutual Information (PPMI) based word embeddings generated from ConceptNet data via SVD on the co-occurrence matrix.
### Languages
- Maltese
## Dataset Creation
- GloVe and Word2Vec embeddings were trained using the largest Maltese dataset, "korpus_malti".
- Details of the training parameters for both GloVe and Word2Vec models can be found in the provided scripts.
- PPMI embeddings were trained using ConceptNet data and applying SVD on the co-occurrence matrix.
### Contributors
- Daniil Gurgurov
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BangumiBase/popteamepic | 2023-10-06T11:24:35.000Z | [
"size_categories:n<1K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T10:53:12 | ---
license: mit
tags:
- art
size_categories:
- n<1K
---
# Bangumi Image Base of Pop Team Epic
This is the image base of bangumi POP TEAM EPIC, we detected 15 characters, 353 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 35 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 13 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 9 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 6 | [Download](3/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 4 | 13 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 15 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 48 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 15 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 77 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 14 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 10 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 8 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 13 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 11 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 66 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 5,912 | [
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shijli/enwik8 | 2023-10-06T11:13:00.000Z | [
"region:us"
] | shijli | null | null | 0 | 0 | 2023-10-06T11:13:00 | Entry not found | 15 | [
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CyberHarem/erza_scarlet_fairytail | 2023-10-06T11:40:12.000Z | [
"task_categories:text-to-image",
"size_categories:n<1K",
"license:mit",
"art",
"not-for-all-audiences",
"region:us"
] | CyberHarem | null | null | 0 | 0 | 2023-10-06T11:40:04 | ---
license: mit
task_categories:
- text-to-image
tags:
- art
- not-for-all-audiences
size_categories:
- n<1K
---
# Dataset of erza_scarlet_fairytail
This is the dataset of erza_scarlet_fairytail, containing 200 images and their tags.
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)).
| Name | Images | Download | Description |
|:----------------|---------:|:----------------------------------------|:-----------------------------------------------------------------------------------------|
| raw | 200 | [Download](dataset-raw.zip) | Raw data with meta information. |
| raw-stage3 | 427 | [Download](dataset-raw-stage3.zip) | 3-stage cropped raw data with meta information. |
| raw-stage3-eyes | 434 | [Download](dataset-raw-stage3-eyes.zip) | 3-stage cropped (with eye-focus) raw data with meta information. |
| 384x512 | 200 | [Download](dataset-384x512.zip) | 384x512 aligned dataset. |
| 512x704 | 200 | [Download](dataset-512x704.zip) | 512x704 aligned dataset. |
| 640x880 | 200 | [Download](dataset-640x880.zip) | 640x880 aligned dataset. |
| stage3-640 | 427 | [Download](dataset-stage3-640.zip) | 3-stage cropped dataset with the shorter side not exceeding 640 pixels. |
| stage3-800 | 427 | [Download](dataset-stage3-800.zip) | 3-stage cropped dataset with the shorter side not exceeding 800 pixels. |
| stage3-p512-640 | 166 | [Download](dataset-stage3-p512-640.zip) | 3-stage cropped dataset with the area not less than 512x512 pixels. |
| stage3-eyes-640 | 434 | [Download](dataset-stage3-eyes-640.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 640 pixels. |
| stage3-eyes-800 | 434 | [Download](dataset-stage3-eyes-800.zip) | 3-stage cropped (with eye-focus) dataset with the shorter side not exceeding 800 pixels. |
| 2,588 | [
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stephaniecs/clean_dataset | 2023-10-06T11:40:44.000Z | [
"region:us"
] | stephaniecs | null | null | 0 | 0 | 2023-10-06T11:40:44 | Entry not found | 15 | [
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stephaniecs/demo_dataset | 2023-10-06T11:43:23.000Z | [
"region:us"
] | stephaniecs | null | null | 0 | 0 | 2023-10-06T11:43:23 | Entry not found | 15 | [
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cointegrated/nli-rus-translated-v2021 | 2023-10-06T14:51:23.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"size_categories:1M<n<10M",
"language:ru",
"region:us"
] | cointegrated | null | null | 0 | 0 | 2023-10-06T11:47:22 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: dev
path: data/dev-*
- split: test
path: data/test-*
dataset_info:
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype: string
- name: source
dtype: string
- name: split
dtype: string
- name: premise_ru
dtype: string
- name: hypothesis_ru
dtype: string
- name: reverse_entailment_score
dtype: float64
- name: len_ratio
dtype: float64
- name: idx
dtype: int64
splits:
- name: train
num_bytes: 1156491691
num_examples: 1756548
- name: dev
num_bytes: 78632908
num_examples: 106557
- name: test
num_bytes: 30464486
num_examples: 34615
download_size: 504709758
dataset_size: 1265589085
task_categories:
- text-classification
task_ids:
- natural-language-inference
language:
- ru
size_categories:
- 1M<n<10M
---
# Dataset Card for "nli-rus-translated-v2021"
This dataset was introduced in the Habr post
["Нейросети для Natural Language Inference (NLI): логические умозаключения на русском языке"](https://habr.com/ru/articles/582620/).
It is composed from various English NLI datasets automatically translated into Russian.
Here are the sizes of the source datasets included into different splits:
| source | train | dev | test |
|:------------|--------:|------:|-------:|
| add_one_rte | 4991 | 387 | 0 |
| anli_r1 | 16946 | 1000 | 1000 |
| anli_r2 | 45460 | 1000 | 1000 |
| anli_r3 | 100459 | 1200 | 1200 |
| copa | 800 | 200 | 0 |
| fever | 162330 | 20478 | 20343 |
| help | 29347 | 3355 | 3189 |
| iie | 281643 | 31232 | 0 |
| imppres | 10179 | 7661 | 7660 |
| joci | 8412 | 939 | 0 |
| mnli | 392662 | 19647 | 0 |
| monli | 2186 | 269 | 223 |
| mpe | 9000 | 1000 | 0 |
| qnli | 108436 | 5732 | 0 |
| scitail | 24900 | 2126 | 0 |
| sick | 9500 | 500 | 0 |
| snli | 549297 | 9831 | 0 |
Most of the original data were taken from the repository [felipessalvatore/NLI_datasets](https://github.com/felipessalvatore/NLI_datasets).
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 2,439 | [
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ahmetalper/test | 2023-10-06T12:10:43.000Z | [
"region:us"
] | ahmetalper | null | null | 0 | 0 | 2023-10-06T12:00:27 | Entry not found | 15 | [
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julia-neugarten/FSNNA2023 | 2023-10-06T12:02:05.000Z | [
"region:us"
] | julia-neugarten | null | null | 0 | 0 | 2023-10-06T12:02:05 | Entry not found | 15 | [
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HamdanXI/difference_analysis | 2023-10-06T12:10:59.000Z | [
"region:us"
] | HamdanXI | null | null | 0 | 0 | 2023-10-06T12:10:56 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: en_toxic_comment
dtype: string
- name: en_neutral_comment
dtype: string
- name: edit_ops
list:
- name: content
dtype: string
- name: operation
dtype: string
- name: position
dtype: int64
- name: replacement_content
dtype: string
splits:
- name: train
num_bytes: 4067122
num_examples: 19744
download_size: 1959427
dataset_size: 4067122
---
# Dataset Card for "difference_analysis"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 710 | [
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flozi00/qa-tasks-german | 2023-10-27T09:26:54.000Z | [
"task_categories:text2text-generation",
"task_categories:text-generation",
"task_categories:question-answering",
"language:de",
"region:us"
] | flozi00 | null | null | 0 | 0 | 2023-10-06T12:22:27 | ---
language:
- de
task_categories:
- text2text-generation
- text-generation
- question-answering
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 105078
num_examples: 12
download_size: 0
dataset_size: 105078
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "qa-tasks-german"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 563 | [
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baebee/test_questions_self_instruct | 2023-10-06T12:37:58.000Z | [
"region:us"
] | baebee | null | null | 0 | 0 | 2023-10-06T12:34:38 | Entry not found | 15 | [
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asoria/copy-BRAD | 2023-10-06T12:39:29.000Z | [
"region:us"
] | asoria | null | null | 0 | 0 | 2023-10-06T12:37:41 | ---
dataset_info:
features:
- name: id
dtype: string
- name: first_sentence
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- name: second_sentence
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- name: label
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0: 0
1: 1
splits:
- name: train
num_bytes: 1420233
num_examples: 10000
- name: validation
num_bytes: 133986
num_examples: 1000
download_size: 837486
dataset_size: 1554219
---
# Dataset Card for "Commonsense_Validation"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 606 | [
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BangumiBase/nouminkanrennoskillbakkaagetetaranazekatsuyokunatta | 2023-10-06T13:38:28.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T12:40:56 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Noumin Kanren No Skill Bakka Agetetara Naze Ka Tsuyoku Natta
This is the image base of bangumi Noumin Kanren no Skill Bakka Agetetara Naze ka Tsuyoku Natta, we detected 32 characters, 1564 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 22 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 102 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 21 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 15 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 41 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 543 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 29 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 24 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 21 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 128 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 22 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 32 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 15 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 10 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 34 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 11 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 19 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 14 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 10 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 13 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 19 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 24 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 22 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 41 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 15 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 103 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 30 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 22 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 6 | [Download](29/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 30 | 5 | [Download](30/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 137 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 11,349 | [
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Vojtab42/guanaco-llama2-1k | 2023-10-06T12:43:59.000Z | [
"region:us"
] | Vojtab42 | null | null | 0 | 0 | 2023-10-06T12:43:57 | ---
dataset_info:
features:
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num_examples: 1000
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dataset_size: 1654448
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "guanaco-llama2-1k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 444 | [
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carnival13/massive_5_lang_DA3_tokenized | 2023-10-06T12:49:41.000Z | [
"region:us"
] | carnival13 | null | null | 0 | 0 | 2023-10-06T12:49:21 | ---
dataset_info:
features:
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dtype: int64
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sequence: int32
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sequence: int8
splits:
- name: train
num_bytes: 419259395
num_examples: 552890
download_size: 127212717
dataset_size: 419259395
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "massive_5_lang_DA3_tokenized"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 553 | [
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TottiPick/repo_name | 2023-10-06T13:10:36.000Z | [
"region:us"
] | TottiPick | null | null | 0 | 0 | 2023-10-06T13:10:36 | Entry not found | 15 | [
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TottiPick/melody_extraction | 2023-10-06T13:11:05.000Z | [
"region:us"
] | TottiPick | null | null | 0 | 0 | 2023-10-06T13:11:05 | Entry not found | 15 | [
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TottiPick/melody_extraction_huggingface | 2023-10-06T13:22:34.000Z | [
"region:us"
] | TottiPick | null | null | 0 | 0 | 2023-10-06T13:13:06 | Entry not found | 15 | [
[
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ebony59/chai_feedback | 2023-10-06T13:13:48.000Z | [
"region:us"
] | ebony59 | null | null | 0 | 0 | 2023-10-06T13:13:47 | ---
dataset_info:
features: []
splits:
- name: train
download_size: 324
dataset_size: 0
---
# Dataset Card for "chai_feedback"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 269 | [
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ebony59/chai_guanaco_feedback | 2023-10-06T15:45:55.000Z | [
"region:us"
] | ebony59 | null | null | 0 | 0 | 2023-10-06T13:14:25 | ---
dataset_info:
features:
- name: character
dtype: string
- name: conversations
list:
- name: content
dtype: string
- name: role
dtype: string
splits:
- name: train
num_bytes: 4081747
num_examples: 1979
download_size: 0
dataset_size: 4081747
---
# Dataset Card for "chai_guanaco_feedback"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 473 | [
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TomerMassas/melody_dataset | 2023-10-31T11:57:30.000Z | [
"region:us"
] | TomerMassas | null | null | 0 | 0 | 2023-10-06T13:28:08 | Entry not found | 15 | [
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lunarflu/Developing_LLMs_Open_Closed_or_Democratic | 2023-10-06T13:28:18.000Z | [
"region:us"
] | lunarflu | null | null | 0 | 0 | 2023-10-06T13:28:11 | https://x.com/natolambert/status/1710285440803344688?s=20 | 57 | [
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lissadesu/codeqa_v2 | 2023-10-06T13:38:30.000Z | [
"region:us"
] | lissadesu | null | null | 0 | 0 | 2023-10-06T13:38:08 | ---
dataset_info:
features:
- name: labNo
dtype: float64
- name: taskNo
dtype: float64
- name: questioner
dtype: string
- name: question
dtype: string
- name: code
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splits:
- name: train
num_bytes: 46842820
num_examples: 35360
download_size: 17749500
dataset_size: 46842820
---
# Dataset Card for "codeqa_v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 908 | [
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asoria/test_s3 | 2023-10-06T13:50:57.000Z | [
"task_categories:image-classification",
"annotations_creators:machine-generated",
"size_categories:10K<n<100K",
"source_datasets:extended|mnist",
"language:en",
"license:cc-by-sa-3.0",
"arxiv:2207.10495",
"region:us"
] | asoria | The images were created such that they have an unclear ground truth,
i.e., such that they are similar to multiple - but not all - of the datasets classes.
Robust and uncertainty-aware models should be able to detect and flag these ambiguous images.
As such, the dataset should be merged / mixed with the original dataset and we
provide such 'mixed' splits for convenience. Please refer to the dataset card for details. | @misc{https://doi.org/10.48550/arxiv.2207.10495,
doi = {10.48550/ARXIV.2207.10495},
url = {https://arxiv.org/abs/2207.10495},
author = {Weiss, Michael and Gómez, André García and Tonella, Paolo},
title = {A Forgotten Danger in DNN Supervision Testing: Generating and Detecting True Ambiguity},
publisher = {arXiv},
year = {2022}
} | 0 | 0 | 2023-10-06T13:48:53 | ---
license: cc-by-sa-3.0
task_categories:
- image-classification
language:
- en
pretty_name: mnist_ambigous
size_categories:
- 10K<n<100K
source_datasets:
- extended|mnist
annotations_creators:
- machine-generated
---
# Mnist-Ambiguous
This dataset contains mnist-like images, but with an unclear ground truth. For each image, there are two classes which could be considered true.
Robust and uncertainty-aware DNNs should thus detect and flag these issues.
### Features
Same as mnist, the supervised dataset has an `image` (28x28 int array) and a `label` (int).
Additionally, the following features are exposed for your convenience:
- `text_label` (str): A textual representation of the probabilistic label, e.g. `p(0)=0.54, p(5)=0.46`
- `p_label` (list of floats): Ground-Truth probabilities for each class (two nonzero values for our ambiguous images)
- `is_ambiguous` (bool): Flag indicating if this is one of our ambiguous images (see 'splits' below)
### Splits
We provide four splits:
- `test`: 10'000 ambiguous images
- `train`: 10'000 ambiguous images - adding ambiguous images to the training set makes sure test-time ambiguous images are in-distribution.
- `test_mixed`: 20'000 images, consisting of the (shuffled) concatenation of our ambiguous `test` set and the nominal mnist test set by LeCun et. al.,
- `train_mixed`: 70'000 images, consisting of the (shuffled) concatenation of our ambiguous `training` and the nominal training set.
Note that the ambiguous test images are highly ambiguous (i.e., the two classes have very similar ground truth likelihoods),
the training set images allow for more unbalanced ambiguity.
This is to make the training set more closely connected to the nominal data, while still keeping the test set clearly ambiguous.
For research targeting explicitly aleatoric uncertainty, we recommend training the model using `train_mixed`.
Otherwise, our `test` set will lead to both epistemic and aleatoric uncertainty.
In related literature, such 'mixed' splits are sometimes denoted as *dirty* splits.
### Assessment and Validity
For a brief discussion of the strength and weaknesses of this dataset,
including a quantitative comparison to the (only) other ambiguous datasets available in the literature, we refer to our paper.
### Paper
Pre-print here: [https://arxiv.org/abs/2207.10495](https://arxiv.org/abs/2207.10495)
Citation:
```
@misc{https://doi.org/10.48550/arxiv.2207.10495,
doi = {10.48550/ARXIV.2207.10495},
url = {https://arxiv.org/abs/2207.10495},
author = {Weiss, Michael and Gómez, André García and Tonella, Paolo},
title = {A Forgotten Danger in DNN Supervision Testing: Generating and Detecting True Ambiguity},
publisher = {arXiv},
year = {2022}
}
```
### License
As this is a derivative work of mnist, which is CC-BY-SA 3.0 licensed, our dataset is released using the same license.
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lissadesu/codeqa_v3 | 2023-10-06T13:53:22.000Z | [
"region:us"
] | lissadesu | null | null | 0 | 0 | 2023-10-06T13:52:09 | ---
dataset_info:
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splits:
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num_bytes: 46848295
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download_size: 17749500
dataset_size: 46848295
---
# Dataset Card for "codeqa_v3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 908 | [
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BangumiBase/beasttamer | 2023-10-06T15:03:07.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T13:52:45 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Beast Tamer
This is the image base of bangumi Beast Tamer, we detected 25 characters, 1727 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 46 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 24 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 15 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 411 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 13 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 8 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 12 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 17 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 8 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 201 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 25 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 41 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 21 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 17 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 317 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 10 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 231 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 10 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 14 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 50 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 22 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 37 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 14 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 38 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 125 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 9,053 | [
[
-0.04473876953125,
-0.00948333740234375,
0.006336212158203125,
0.01470184326171875,
-0.016571044921875,
-0.004306793212890625,
-0.00021398067474365234,
-0.0243072509765625,
0.038360595703125,
0.0305633544921875,
-0.058868408203125,
-0.052032470703125,
-0.0418395... |
BangumiBase/justbecause | 2023-10-06T14:49:54.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T13:52:59 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Just Because!
This is the image base of bangumi Just Because!, we detected 20 characters, 1430 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 218 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 14 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 15 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 28 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 99 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 21 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 43 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 228 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 65 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 14 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 21 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 15 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 12 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 106 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 21 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 357 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 7 | [Download](16/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 17 | 23 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 23 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 100 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,487 | [
[
-0.044342041015625,
-0.00977325439453125,
0.01290130615234375,
0.01424407958984375,
-0.016693115234375,
-0.00720977783203125,
-0.002960205078125,
-0.0224609375,
0.0389404296875,
0.032623291015625,
-0.06011962890625,
-0.0548095703125,
-0.04241943359375,
0.032... |
BangumiBase/unlimitedfafnir | 2023-10-06T14:46:23.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T13:53:41 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Unlimited Fafnir
This is the image base of bangumi Unlimited Fafnir, we detected 17 characters, 1386 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 31 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 135 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 28 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 417 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 74 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 59 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 45 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 38 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 125 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 56 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 151 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 119 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 13 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 9 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 45 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 18 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 23 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 6,551 | [
[
-0.043792724609375,
-0.00991058349609375,
0.00891876220703125,
0.018310546875,
-0.01494598388671875,
-0.007389068603515625,
0.0017023086547851562,
-0.0232696533203125,
0.03668212890625,
0.033782958984375,
-0.05999755859375,
-0.053253173828125,
-0.0426025390625,
... |
lissadesu/codeqa_reduced | 2023-10-06T13:54:14.000Z | [
"region:us"
] | lissadesu | null | null | 0 | 0 | 2023-10-06T13:53:43 | ---
dataset_info:
features:
- name: labNo
dtype: float64
- name: taskNo
dtype: float64
- name: questioner
dtype: string
- name: question
dtype: string
- name: code
dtype: string
- name: startLine
dtype: float64
- name: endLine
dtype: float64
- name: questionType
dtype: string
- name: answer
dtype: string
- name: src
dtype: string
- name: code_processed
dtype: string
- name: id
dtype: string
- name: raw_code
dtype: string
- name: raw_comment
dtype: string
- name: comment
dtype: string
- name: q_code
dtype: string
splits:
- name: train
num_bytes: 39821050.75
num_examples: 30056
- name: test
num_bytes: 7027244.25
num_examples: 5304
download_size: 23830741
dataset_size: 46848295.0
---
# Dataset Card for "codeqa_final"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 980 | [
[
-0.045257568359375,
-0.00970458984375,
0.0177001953125,
0.0009584426879882812,
-0.0091552734375,
0.01287078857421875,
0.01493072509765625,
0.0006084442138671875,
0.046112060546875,
0.043304443359375,
-0.050018310546875,
-0.060791015625,
-0.024078369140625,
-... |
BangumiBase/idolish7 | 2023-10-06T15:53:59.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-06T14:20:23 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Idolish7
This is the image base of bangumi IDOLiSH7, we detected 27 characters, 3443 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability).
Here is the characters' preview:
| # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 |
|:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|
| 0 | 307 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 58 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 281 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 323 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 116 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 23 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 88 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 289 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 91 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 329 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 379 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 70 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 21 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 17 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 17 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 293 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 439 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 12 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 8 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 18 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 6 | [Download](20/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 21 | 9 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 14 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 7 | [Download](23/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 24 | 10 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 6 | [Download](25/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 212 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 9,675 | [
[
-0.04302978515625,
-0.00881195068359375,
0.007381439208984375,
0.01279449462890625,
-0.0173797607421875,
-0.0055084228515625,
-0.00348663330078125,
-0.0234375,
0.040618896484375,
0.034088134765625,
-0.05792236328125,
-0.05377197265625,
-0.0426025390625,
0.03... |
Xenova/cmu-arctic-xvectors-extracted | 2023-10-06T14:59:01.000Z | [
"region:us"
] | Xenova | null | null | 1 | 0 | 2023-10-06T14:49:55 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
asdfaasdfs/outlier | 2023-10-06T15:04:13.000Z | [
"region:us"
] | asdfaasdfs | null | null | 0 | 0 | 2023-10-06T15:04:13 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
Ekiel/monDataSet | 2023-10-06T15:23:32.000Z | [
"region:us"
] | Ekiel | null | null | 0 | 0 | 2023-10-06T15:23:32 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
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