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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
asgaardlab/GamePhysics-FullResolution | 2023-10-08T01:54:35.000Z | [
"task_categories:video-classification",
"size_categories:10K<n<100K",
"language:en",
"license:creativeml-openrail-m",
"video-game",
"game",
"video-understanding",
"ood",
"vidoe-ood",
"arxiv:2203.11096",
"region:us"
] | asgaardlab | null | null | 1 | 0 | 2023-10-05T01:10:33 | ---
dataset_info:
features:
- name: id
dtype: string
- name: game
dtype: string
- name: filepath
dtype: string
- name: filename
dtype: string
- name: archive
dtype: string
- name: reddit_url
dtype: string
splits:
- name: validation
num_bytes: 3692759
num_examples: 26954
download_size: 1232477
dataset_size: 3692759
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
license: creativeml-openrail-m
task_categories:
- video-classification
language:
- en
tags:
- video-game
- game
- video-understanding
- ood
- vidoe-ood
pretty_name: GamePhysics
size_categories:
- 10K<n<100K
---
# GamePhysics Dataset
[](https://asgaardlab.github.io/CLIPxGamePhysics/)
[](https://arxiv.org/abs/2203.11096)
[](https://huggingface.co/spaces/taesiri/CLIPxGamePhysics)
The GamePhysics dataset is a collection of gameplay bug videos sourced from the [GamePhysics subreddit](https://www.reddit.com/r/GamePhysics/).
## Sample videos
<video src="https://asgaardlab.github.io/CLIPxGamePhysics/static/videos/9rqabp.mp4" controls="controls" muted="muted" playsinline="playsinline" width=480></video>
<video src="https://asgaardlab.github.io/CLIPxGamePhysics/static/videos/g5pm35.mp4" controls="controls" muted="muted" playsinline="playsinline" width=480></video>
<video src="https://asgaardlab.github.io/CLIPxGamePhysics/static/videos/6xplqg.mp4" controls="controls" muted="muted" playsinline="playsinline" width=480></video>
<video src="https://asgaardlab.github.io/CLIPxGamePhysics/static/videos/4jirzj.mp4" controls="controls" muted="muted" playsinline="playsinline" width=480></video> | 1,881 | [
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0.01568603515625,
-0.08270263671875,
-0.05242919921875,
-0.040435791015625,
-0.0... |
xhwangHY/foo | 2023-10-05T01:15:25.000Z | [
"region:us"
] | xhwangHY | null | null | 0 | 0 | 2023-10-05T01:15:25 | Entry not found | 15 | [
[
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0.051361083984375,
0.0170135498046875,
-0.05206298828125,
-0.0149993896484375,
-0.06036376953125,
0.0379028320... |
djaekim/mutation_dataset | 2023-10-05T01:34:05.000Z | [
"region:us"
] | djaekim | null | null | 0 | 0 | 2023-10-05T01:34:05 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
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0.046539306640625,
0.052520751953125,
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0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
autoevaluate/autoeval-eval-squad_v2-squad_v2-e8e9fa-93073145746 | 2023-10-05T02:23:34.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T02:23:29 | Entry not found | 15 | [
[
-0.02142333984375,
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0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
kkboy1/le_audio | 2023-10-05T02:50:32.000Z | [
"region:us"
] | kkboy1 | null | null | 0 | 0 | 2023-10-05T02:50:07 | 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/lordelmelloiiiseinojikenborailzeppelin | 2023-10-05T05:01:02.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T03:27:53 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Lord El-melloi Ii-sei No Jikenbo Rail Zeppelin
This is the image base of bangumi Lord El-Melloi II-sei no Jikenbo Rail Zeppelin, we detected 43 characters, 2376 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 | 483 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 98 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 22 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 33 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 19 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 18 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 23 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 26 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 67 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 50 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 62 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 15 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 18 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 30 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 149 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 14 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 42 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 17 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 47 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 9 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 44 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 10 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 32 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 240 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 34 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 33 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 93 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 18 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 12 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 12 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 52 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 74 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 22 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 101 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 11 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 17 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 10 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 15 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 5 | [Download](40/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 41 | 50 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 219 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 14,775 | [
[
-0.0440673828125,
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0.04083251953125,
0.031890869140625,
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... |
BangumiBase/inoubattlewithineverydaylife | 2023-10-05T04:50:11.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T03:47:20 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Inou Battle Within Everyday Life
This is the image base of bangumi Inou Battle Within Everyday Life, we detected 19 characters, 1588 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 | 150 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 19 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 41 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 495 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 17 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 9 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 78 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 9 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 182 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 40 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 25 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 213 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 6 | [Download](12/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 13 | 141 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 12 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 7 | [Download](15/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 16 | 5 | [Download](16/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 17 | 12 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 127 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,211 | [
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-0.04168701171875,
0... |
tinhpx2911/vnz_raw_html | 2023-10-05T03:54:28.000Z | [
"region:us"
] | tinhpx2911 | null | null | 0 | 0 | 2023-10-05T03:52:43 | Entry not found | 15 | [
[
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0.0379... |
BangumiBase/tenseishitarakendeshita | 2023-10-05T04:49:29.000Z | [
"size_categories:n<1K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T03:55:11 | ---
license: mit
tags:
- art
size_categories:
- n<1K
---
# Bangumi Image Base of Tensei Shitara Ken Deshita
This is the image base of bangumi Tensei Shitara Ken Deshita, we detected 20 characters, 895 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 | 277 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 110 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 22 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 49 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 32 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 19 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 25 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 7 | [Download](7/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 8 | 10 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 9 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 14 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 99 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 9 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 24 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 34 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 13 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 9 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 5 | [Download](18/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 114 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,508 | [
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tinhpx2911/hocmai_raw_html | 2023-10-05T03:55:20.000Z | [
"region:us"
] | tinhpx2911 | null | null | 0 | 0 | 2023-10-05T03:55:20 | Entry not found | 15 | [
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0.0379028... |
tinhpx2911/kenhsinhvien_raw_html | 2023-10-05T04:06:35.000Z | [
"region:us"
] | tinhpx2911 | null | null | 0 | 0 | 2023-10-05T04:03:21 | Entry not found | 15 | [
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-0.0604248046875,
0.0379028... |
AqwamMalik/Assistant | 2023-10-05T04:18:07.000Z | [
"region:us"
] | AqwamMalik | null | null | 0 | 0 | 2023-10-05T04:18:07 | Entry not found | 15 | [
[
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0.052490234375,
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0.0170135498046875,
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0.0379028... |
DynamicSuperb/example_dataset | 2023-10-05T04:29:53.000Z | [
"region:us"
] | DynamicSuperb | null | null | 0 | 0 | 2023-10-05T04:29:38 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
dtype: audio
- name: file
dtype: string
- name: instruction
dtype: string
- name: label
dtype: string
splits:
- name: test
num_bytes: 358052.0
num_examples: 3
download_size: 360407
dataset_size: 358052.0
---
# Dataset Card for "example_dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 545 | [
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zkdeng/inatSpiders | 2023-10-05T09:36:13.000Z | [
"region:us"
] | zkdeng | null | null | 0 | 0 | 2023-10-05T04:45:34 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Abba_transversa
'1': Acacesia_hamata
'2': Acalitus_brevitarsus
'3': Acalitus_ferrugineum
'4': Acalitus_longisetosus
'5': Acanthepeira_stellata
'6': Acantholycosa_lignaria
'7': Acanthopachylus_robustus
'8': Acanthophrynus_coronatus
'9': Acanthoscurria_natalensis
'10': Aceria_aloinis
'11': Aceria_baccharices
'12': Aceria_baccharipha
'13': Aceria_boycei
'14': Aceria_brachytarsa
'15': Aceria_calaceris
'16': Aceria_caliberberis
'17': Aceria_campestricola
'18': Aceria_caryae
'19': Aceria_caulis
'20': Aceria_celtis
'21': Aceria_cephalanthi
'22': Aceria_cephalonea
'23': Aceria_cinereae
'24': Aceria_dina
'25': Aceria_dispar
'26': Aceria_echii
'27': Aceria_elongata
'28': Aceria_erinea
'29': Aceria_fraxini
'30': Aceria_fraxiniflora
'31': Aceria_fraxinivora
'32': Aceria_genistae
'33': Aceria_ilicis
'34': Aceria_mackiei
'35': Aceria_macrochela
'36': Aceria_macrorhyncha
'37': Aceria_modesta
'38': Aceria_myriadeum
'39': Aceria_negundi
'40': Aceria_nyssae
'41': Aceria_paracalifornica
'42': Aceria_parapopuli
'43': Aceria_parulmi
'44': Aceria_pseudoplatani
'45': Aceria_quercerina
'46': Aceria_querci
'47': Aceria_theospyri
'48': Aceria_trichophila
'49': Aceria_trinema
'50': Aceria_triplacis
'51': Aceria_vaga
'52': Actinosoma_pentacanthum
'53': Aculepeira_armida
'54': Aculepeira_ceropegia
'55': Aculepeira_packardi
'56': Aculops_aenigma
'57': Aculops_rhois
'58': Aculus_minutissimus
'59': Aculus_tetanothrix
'60': Aegaeobuthus_gibbosus
'61': Aelurillus_dubatolovi
'62': Aelurillus_luctuosus
'63': Aelurillus_m-nigrum
'64': Aelurillus_v-insignitus
'65': Agalenatea_redii
'66': Agelena_labyrinthica
'67': Agelena_orientalis
'68': Agelenopsis_aperta
'69': Agelenopsis_potteri
'70': Aglaoctenus_castaneus
'71': Aglaoctenus_lagotis
'72': Algidia_chiltoni
'73': Algidia_nigriflava
'74': Allagelena_gracilens
'75': Allocosa_funerea
'76': Allocyclosa_bifurca
'77': Allotrochosina_schauinslandi
'78': Alopecosa_albofasciata
'79': Alopecosa_barbipes
'80': Alopecosa_cuneata
'81': Alopecosa_inquilina
'82': Alopecosa_kochi
'83': Alopecosa_pulverulenta
'84': Alpaida_acuta
'85': Alpaida_alticeps
'86': Alpaida_bicornuta
'87': Alpaida_carminea
'88': Alpaida_gallardoi
'89': Alpaida_grayi
'90': Alpaida_leucogramma
'91': Alpaida_rubellula
'92': Alpaida_truncata
'93': Alpaida_variabilis
'94': Alpaida_veniliae
'95': Alpaida_versicolor
'96': Amaurobius_erberi
'97': Amaurobius_fenestralis
'98': Amaurobius_ferox
'99': Amaurobius_similis
'100': Amblyocarenum_walckenaeri
'101': Amblyomma_americanum
'102': Amblyomma_hebraeum
'103': Amblyomma_maculatum
'104': Amblyomma_triguttatum
'105': Amilenus_aurantiacus
'106': Amyciaea_forticeps
'107': Anahita_punctulata
'108': Anarrhotus_fossulatus
'109': Anasaitis_canosa
'110': Ancylometes_bogotensis
'111': Ancylometes_concolor
'112': Ancylometes_rufus
'113': Anelosimus_eximius
'114': Anelosimus_studiosus
'115': Anelosimus_vittatus
'116': Anepsion_maritatum
'117': Anoteropsis_hilaris
'118': Anoteropsis_litoralis
'119': Antrodiaetus_pacificus
'120': Antrodiaetus_unicolor
'121': Anuroctonus_phaiodactylus
'122': Anuroctonus_pococki
'123': Anyphaena_accentuata
'124': Anyphaena_numida
'125': Aoaraneus_pentagrammicus
'126': Aphantaulax_trifasciata
'127': Aphantochilus_rogersi
'128': Aphonopelma_anax
'129': Aphonopelma_armada
'130': Aphonopelma_chalcodes
'131': Aphonopelma_crinirufum
'132': Aphonopelma_eutylenum
'133': Aphonopelma_gabeli
'134': Aphonopelma_hentzi
'135': Aphonopelma_iodius
'136': Aphonopelma_johnnycashi
'137': Aphonopelma_marxi
'138': Aphonopelma_pallidum
'139': Aphonopelma_seemanni
'140': Aphonopelma_steindachneri
'141': Aphonopelma_vorhiesi
'142': Apricia_bracteata
'143': Apricia_jovialis
'144': Arachnura_feredayi
'145': Arachnura_higginsi
'146': Arachnura_melanura
'147': Arachnura_scorpionoides
'148': Arachosia_praesignis
'149': Araneus_albotriangulus
'150': Araneus_alboventris
'151': Araneus_alsine
'152': Araneus_andrewsi
'153': Araneus_angulatus
'154': Araneus_apricus
'155': Araneus_bicentenarius
'156': Araneus_cavaticus
'157': Araneus_cingulatus
'158': Araneus_circe
'159': Araneus_circulissparsus
'160': Araneus_detrimentosus
'161': Araneus_diadematus
'162': Araneus_ejusmodi
'163': Araneus_gemma
'164': Araneus_gemmoides
'165': Araneus_granadensis
'166': Araneus_grossus
'167': Araneus_guttatus
'168': Araneus_guttulatus
'169': Araneus_lathyrinus
'170': Araneus_marmoreus
'171': Araneus_miniatus
'172': Araneus_nordmanni
'173': Araneus_pallidus
'174': Araneus_pegnia
'175': Araneus_pratensis
'176': Araneus_quadratus
'177': Araneus_rotundulus
'178': Araneus_saevus
'179': Araneus_sturmi
'180': Araneus_talipedatus
'181': Araneus_thaddeus
'182': Araneus_trifolium
'183': Araneus_triguttatus
'184': Araneus_uniformis
'185': Araneus_venatrix
'186': Araneus_ventricosus
'187': Araneus_viridiventris
'188': Araneus_workmani
'189': Araniella_alpica
'190': Araniella_cucurbitina
'191': Araniella_displicata
'192': Araniella_opisthographa
'193': Arasia_mollicoma
'194': Architis_spinipes
'195': Arctosa_cinerea
'196': Arctosa_leopardus
'197': Arctosa_littoralis
'198': Arctosa_perita
'199': Arctosa_personata
'200': Argiope_aemula
'201': Argiope_aetherea
'202': Argiope_aetheroides
'203': Argiope_amoena
'204': Argiope_anasuja
'205': Argiope_appensa
'206': Argiope_argentata
'207': Argiope_aurantia
'208': Argiope_australis
'209': Argiope_bruennichi
'210': Argiope_catenulata
'211': Argiope_dang
'212': Argiope_florida
'213': Argiope_keyserlingi
'214': Argiope_lobata
'215': Argiope_magnifica
'216': Argiope_mascordi
'217': Argiope_minuta
'218': Argiope_ocula
'219': Argiope_ocyaloides
'220': Argiope_perforata
'221': Argiope_picta
'222': Argiope_protensa
'223': Argiope_radon
'224': Argiope_reinwardti
'225': Argiope_submaronica
'226': Argiope_trifasciata
'227': Argiope_versicolor
'228': Argyrodes_antipodianus
'229': Argyrodes_argyrodes
'230': Argyrodes_elevatus
'231': Argyrodes_flavescens
'232': Argyrodes_miniaceus
'233': Argyroneta_aquatica
'234': Ariadna_bicolor
'235': Ariamnes_colubrinus
'236': Ariamnes_cylindrogaster
'237': Arkys_alatus
'238': Arkys_alticephala
'239': Arkys_cornutus
'240': Arkys_curtulus
'241': Arkys_dilatatus
'242': Arkys_furcatus
'243': Arkys_lancearius
'244': Arkys_speechleyi
'245': Arkys_tuberculatus
'246': Arkys_walckenaeri
'247': Artabrus_erythrocephalus
'248': Artema_atlanta
'249': Asagena_americana
'250': Asagena_phalerata
'251': Asaphobelis_physonychus
'252': Asemonea_tenuipes
'253': Asianellus_festivus
'254': Asianopis_aurita
'255': Asianopis_subrufa
'256': Asthenoctenus_borellii
'257': Astia_hariola
'258': Astilodes_mariae
'259': Attinella_concolor
'260': Attinella_dorsata
'261': Attulus_ammophilus
'262': Attulus_avocator
'263': Attulus_fasciger
'264': Attulus_floricola
'265': Attulus_mirandus
'266': Attulus_monstrabilis
'267': Attulus_pubescens
'268': Attulus_terebratus
'269': Attulus_zimmermanni
'270': Atypoides_riversi
'271': Atypus_affinis
'272': Aulonia_albimana
'273': Austracantha_minax
'274': Australomimetus_hartleyensis
'275': Australomisidia_pilula
'276': Avicularia_avicularia
'277': Avicularia_juruensis
'278': Avicularia_purpurea
'279': Avicularia_rufa
'280': Backobourkia_brouni
'281': Badumna_insignis
'282': Badumna_longinqua
'283': Bagheera_prosper
'284': Balaustium_leanderi
'285': Ballus_chalybeius
'286': Ballus_rufipes
'287': Barronopsis_texana
'288': Baryphas_ahenus
'289': Bassaniana_utahensis
'290': Bassaniana_versicolor
'291': Bassaniodes_bufo
'292': Bavia_sexpunctata
'293': Beata_wickhami
'294': Bidentolophus_bidens
'295': Bijoaraneus_mitificus
'296': Bijoaraneus_praesignis
'297': Bothriocyrtum_californicum
'298': Bothriurus_asper
'299': Bothriurus_bonariensis
'300': Brachypelma_albiceps
'301': Brachypelma_emilia
'302': Brachypelma_klaasi
'303': Brettus_cingulatus
'304': Brigittea_civica
'305': Brigittea_latens
'306': Bryantella_smaragda
'307': Burmattus_pococki
'308': Buthus_elongatus
'309': Buthus_ibericus
'310': Buthus_occitanus
'311': Buthus_pyrenaeus
'312': Caddo_agilis
'313': Caerostris_sexcuspidata
'314': Calisoga_longitarsis
'315': Callilepis_nocturna
'316': Callobius_bennetti
'317': Callobius_pictus
'318': Callobius_severus
'319': Camaricus_formosus
'320': Camaricus_maugei
'321': Cambridgea_foliata
'322': Carrhotus_sannio
'323': Carrhotus_viduus
'324': Carrhotus_xanthogramma
'325': Castianeira_amoena
'326': Castianeira_cingulata
'327': Castianeira_descripta
'328': Castianeira_longipalpa
'329': Castianeira_thalia
'330': Catalinia_andreas
'331': Catalinia_thompsoni
'332': Cecidophyes_nudus
'333': Cecidophyes_rouhollahi
'334': Celaenia_calotoides
'335': Celaenia_excavata
'336': Centroctenus_brevipes
'337': Centruroides_bicolor
'338': Centruroides_edwardsii
'339': Centruroides_elegans
'340': Centruroides_exilicauda
'341': Centruroides_fulvipes
'342': Centruroides_gracilis
'343': Centruroides_hentzi
'344': Centruroides_limbatus
'345': Centruroides_limpidus
'346': Centruroides_ochraceus
'347': Centruroides_ornatus
'348': Centruroides_sculpturatus
'349': Centruroides_suffusus
'350': Centruroides_vittatus
'351': Cercidia_prominens
'352': Cercophonius_squama
'353': Cesonia_bilineata
'354': Cetratus_rubropunctatus
'355': Chaetopelma_olivaceum
'356': Chalcoscirtus_diminutus
'357': Cheiracanthium_erraticum
'358': Cheiracanthium_gracile
'359': Cheiracanthium_inclusum
'360': Cheiracanthium_mildei
'361': Cheiracanthium_punctorium
'362': Chelifer_cancroides
'363': Chihuahuanus_coahuilae
'364': Chikunia_nigra
'365': Chira_gounellei
'366': Chira_lucina
'367': Chira_simoni
'368': Chira_spinosa
'369': Chrysilla_acerosa
'370': Chrysilla_lauta
'371': Chrysilla_volupe
'372': Cicurina_cicur
'373': Cithaeron_praedonius
'374': Clynotis_severus
'375': Colaranea_verutum
'376': Colaranea_viriditas
'377': Colomerus_vitis
'378': Colonus_hesperus
'379': Colonus_puerperus
'380': Colonus_sylvanus
'381': Coriarachne_depressa
'382': Corinnomma_severum
'383': Coryphasia_nigriventris
'384': Corythalia_argentinensis
'385': Corythalia_conferta
'386': Corythalia_opima
'387': Cosmobunus_granarius
'388': Cosmophasis_baehrae
'389': Cosmophasis_bitaeniata
'390': Cosmophasis_lami
'391': Cosmophasis_micarioides
'392': Cosmophasis_thalassina
'393': Cosmophasis_valerieae
'394': Cresmatoneta_mutinensis
'395': Crossopriza_lyoni
'396': Cryptachaea_blattea
'397': Cryptachaea_gigantipes
'398': Cryptachaea_veruculata
'399': Ctenus_amphora
'400': Ctenus_hibernalis
'401': Ctenus_medius
'402': Ctenus_ornatus
'403': Cupiennius_coccineus
'404': Cupiennius_getazi
'405': Cupiennius_salei
'406': Curicaberis_culiacan
'407': Cyclosa_bifida
'408': Cyclosa_bifurcata
'409': Cyclosa_caroli
'410': Cyclosa_conica
'411': Cyclosa_diversa
'412': Cyclosa_insulana
'413': Cyclosa_mulmeinensis
'414': Cyclosa_octotuberculata
'415': Cyclosa_oculata
'416': Cyclosa_trilobata
'417': Cyclosa_turbinata
'418': Cyclosa_walckenaeri
'419': Cymbacha_ocellata
'420': Cyrba_algerina
'421': Cyriocosmus_leetzi
'422': Cyrtarachne_inaequalis
'423': Cyrtarachne_ixoides
'424': Cyrtopholis_portoricae
'425': Cyrtophora_cicatrosa
'426': Cyrtophora_citricola
'427': Cyrtophora_exanthematica
'428': Cyrtophora_moluccensis
'429': Cyrtophora_unicolor
'430': Cytaea_alburna
'431': Cytaea_aspera
'432': Cytaea_dispalans
'433': Cytaea_maoming
'434': Dalquestia_formosa
'435': Damon_annulatipes
'436': Damon_variegatus
'437': Dasylobus_graniferus
'438': Davus_ruficeps
'439': Deinopis_longipes
'440': Deinopis_spinosa
'441': Delena_cancerides
'442': Deliochus_zelivira
'443': Dendrolycosa_icadia
'444': Dendryphantes_mordax
'445': Dendryphantes_rudis
'446': Dendryphantes_zygoballoides
'447': Dermacentor_andersoni
'448': Dermacentor_marginatus
'449': Dermacentor_occidentalis
'450': Dermacentor_reticulatus
'451': Dermacentor_variabilis
'452': Desis_marina
'453': Diaea_ambara
'454': Diaea_dorsata
'455': Diaea_livens
'456': Diapontia_uruguayensis
'457': Dicranopalpus_larvatus
'458': Dicranopalpus_ramosus
'459': Dictis_striatipes
'460': Dictyna_calcarata
'461': Diguetinus_raptator
'462': Dinothrombium_gigas
'463': Diplocentrus_lindo
'464': Dipoena_melanogaster
'465': Dolichothele_exilis
'466': Dolomedes_albineus
'467': Dolomedes_dondalei
'468': Dolomedes_facetus
'469': Dolomedes_fimbriatus
'470': Dolomedes_minor
'471': Dolomedes_mizhoanus
'472': Dolomedes_raptor
'473': Dolomedes_scriptus
'474': Dolomedes_striatus
'475': Dolomedes_sulfureus
'476': Dolomedes_tenebrosus
'477': Dolomedes_triton
'478': Dolomedes_vittatus
'479': Drapetisca_alteranda
'480': Drapetisca_socialis
'481': Dugesiella_anitahoffmannae
'482': Dysdera_crocata
'483': Ebrechtella_tricuspidata
'484': Edricus_productus
'485': Egaenus_convexus
'486': Elaver_excepta
'487': Enoplognatha_mandibularis
'488': Enoplognatha_ovata
'489': Epeus_flavobilineatus
'490': Epeus_glorius
'491': Epicadus_heterogaster
'492': Epicadus_trituberculatus
'493': Episinus_angulatus
'494': Episinus_maculipes
'495': Episinus_truncatus
'496': Epocilla_blairei
'497': Epocilla_calcarata
'498': Eratigena_agrestis
'499': Eratigena_atrica
'500': Eratigena_duellica
'501': Eratigena_inermis
'502': Eresus_kollari
'503': Eresus_sandaliatus
'504': Erginulus_subserialis
'505': Eriophora_edax
'506': Eriophora_fuliginea
'507': Eriophora_nephiloides
'508': Eriophora_ravilla
'509': Eriophyes_aceris
'510': Eriophyes_adenostomae
'511': Eriophyes_cerasicrumena
'512': Eriophyes_emarginatae
'513': Eriophyes_exilis
'514': Eriophyes_hoheriae
'515': Eriophyes_inangulis
'516': Eriophyes_laevis
'517': Eriophyes_leiosoma
'518': Eriophyes_paraviburni
'519': Eriophyes_pyri
'520': Eriophyes_rhoinus
'521': Eriophyes_similis
'522': Eriophyes_sorbi
'523': Eriophyes_tiliae
'524': Eriovixia_excelsa
'525': Eriovixia_laglaizei
'526': Eris_flava
'527': Eris_floridana
'528': Eris_militaris
'529': Ero_aphana
'530': Ero_tuberculata
'531': Euagrus_chisoseus
'532': Eucteniza_relata
'533': Eumesosoma_roeweri
'534': Euophrys_frontalis
'535': Euophrys_herbigrada
'536': Euophrys_monadnock
'537': Euophrys_rufibarbis
'538': Eupalaestrus_weijenberghi
'539': Euprosthenopsis_pulchella
'540': Euryattus_bleekeri
'541': Euryopis_episinoides
'542': Euryopis_funebris
'543': Eurytetranychus_buxi
'544': Euscorpius_flavicaudis
'545': Euscorpius_italicus
'546': Eusparassus_dufouri
'547': Eusparassus_walckenaeri
'548': Eustala_anastera
'549': Evarcha_albaria
'550': Evarcha_arcuata
'551': Evarcha_bulbosa
'552': Evarcha_falcata
'553': Evarcha_hoyi
'554': Evarcha_jucunda
'555': Evarcha_michailovi
'556': Evarcha_proszynskii
'557': Falconina_gracilis
'558': Filistata_insidiatrix
'559': Florinda_coccinea
'560': Forsteropsalis_inconstans
'561': Forsteropsalis_pureora
'562': Freya_nigrotaeniata
'563': Frigga_crocuta
'564': Frigga_pratensis
'565': Frigga_quintensis
'566': Frontinella_pyramitela
'567': Frontinellina_frutetorum
'568': Garypus_californicus
'569': Gasteracantha_cancriformis
'570': Gasteracantha_curvispina
'571': Gasteracantha_diadesmia
'572': Gasteracantha_diardi
'573': Gasteracantha_doriae
'574': Gasteracantha_falcicornis
'575': Gasteracantha_fornicata
'576': Gasteracantha_geminata
'577': Gasteracantha_kuhli
'578': Gasteracantha_milvoides
'579': Gasteracantha_quadrispinosa
'580': Gasteracantha_sacerdotalis
'581': Gasteracantha_sanguinolenta
'582': Gasteracantha_sauteri
'583': Gasteracantha_versicolor
'584': Gea_heptagon
'585': Gea_spinipes
'586': Gea_theridioides
'587': Geolycosa_vultuosa
'588': Gibbaranea_bituberculata
'589': Gibbaranea_gibbosa
'590': Gigantometrus_swammerdami
'591': Gladicosa_gulosa
'592': Gladicosa_pulchra
'593': Gluvia_dorsalis
'594': Graemeloweus_iviei
'595': Grammostola_rosea
'596': Gyas_annulatus
'597': Gyas_titanus
'598': Habrocestum_hongkongiense
'599': Habronattus_altanus
'600': Habronattus_americanus
'601': Habronattus_amicus
'602': Habronattus_borealis
'603': Habronattus_brunneus
'604': Habronattus_californicus
'605': Habronattus_captiosus
'606': Habronattus_clypeatus
'607': Habronattus_coecatus
'608': Habronattus_cognatus
'609': Habronattus_conjunctus
'610': Habronattus_cuspidatus
'611': Habronattus_decorus
'612': Habronattus_elegans
'613': Habronattus_fallax
'614': Habronattus_festus
'615': Habronattus_formosus
'616': Habronattus_forticulus
'617': Habronattus_hallani
'618': Habronattus_hirsutus
'619': Habronattus_jucundus
'620': Habronattus_klauseri
'621': Habronattus_mexicanus
'622': Habronattus_mustaciatus
'623': Habronattus_ophrys
'624': Habronattus_orbus
'625': Habronattus_oregonensis
'626': Habronattus_paratus
'627': Habronattus_peckhami
'628': Habronattus_pyrrithrix
'629': Habronattus_sansoni
'630': Habronattus_tarsalis
'631': Habronattus_texanus
'632': Habronattus_ustulatus
'633': Habronattus_viridipes
'634': Hadrobunus_maculosus
'635': Hadrurus_anzaborrego
'636': Hadrurus_arizonensis
'637': Hadrurus_spadix
'638': Hakka_himeshimensis
'639': Hamadruas_hieroglyphica
'640': Hamataliwa_grisea
'641': Harmochirus_brachiatus
'642': Harpactea_hombergi
'643': Harpactea_rubicunda
'644': Harpactira_atra
'645': Hasarius_adansoni
'646': Hebestatis_theveneti
'647': Heliophanus_apiatus
'648': Heliophanus_auratus
'649': Heliophanus_cupreus
'650': Heliophanus_hamifer
'651': Heliophanus_kochii
'652': Heliophanus_melinus
'653': Heliophanus_tribulosus
'654': Helpis_minitabunda
'655': Hemicloea_rogenhoferi
'656': Hentzia_grenada
'657': Hentzia_mitrata
'658': Hentzia_palmarum
'659': Herennia_multipuncta
'660': Heriaeus_hirtus
'661': Heriaeus_oblongus
'662': Herpyllus_ecclesiasticus
'663': Herpyllus_propinquus
'664': Hesperonemastoma_modestum
'665': Heterometrus_laoticus
'666': Heterometrus_longimanus
'667': Heterometrus_silenus
'668': Heterophrynus_batesii
'669': Heterophrynus_longicornis
'670': Heteropoda_amphora
'671': Heteropoda_boiei
'672': Heteropoda_davidbowie
'673': Heteropoda_jugulans
'674': Heteropoda_longipes
'675': Heteropoda_pingtungensis
'676': Heteropoda_procera
'677': Heteropoda_tetrica
'678': Heteropoda_venatoria
'679': Heterotheridion_nigrovariegatum
'680': Hibana_gracilis
'681': Hibana_incursa
'682': Hinewaia_embolica
'683': Hippasa_holmerae
'684': Hogna_antelucana
'685': Hogna_baltimoriana
'686': Hogna_bivittata
'687': Hogna_carolinensis
'688': Hogna_crispipes
'689': Hogna_frondicola
'690': Hogna_gumia
'691': Hogna_radiata
'692': Holcolaetis_zuluensis
'693': Holconia_immanis
'694': Holconia_insignis
'695': Holocnemus_pluchei
'696': Holoplatys_apressus
'697': Holoplatys_invenusta
'698': Holothele_longipes
'699': Homalenotus_quadridentatus
'700': Homalonychus_theologus
'701': Hortophora_biapicata
'702': Hortophora_tatianeae
'703': Hortophora_transmarina
'704': Hottentotta_judaicus
'705': Hottentotta_tamulus
'706': Hygropoda_lineata
'707': Hyllus_argyrotoxus
'708': Hyllus_brevitarsis
'709': Hyllus_diardi
'710': Hyllus_keratodes
'711': Hyllus_semicupreus
'712': Hyllus_treleaveni
'713': Hypochilus_pococki
'714': Hypodrassodes_maoricus
'715': Hypselistes_florens
'716': Hypsosinga_albovittata
'717': Hypsosinga_heri
'718': Hyptiotes_cavatus
'719': Hyptiotes_gertschi
'720': Hyptiotes_paradoxus
'721': Icius_hamatus
'722': Icius_subinermis
'723': Intruda_signata
'724': Iridopelma_hirsutum
'725': Irura_bidenticulata
'726': Isala_cambridgei
'727': Ischnothele_annulata
'728': Ischnothele_caudata
'729': Isometrus_maculatus
'730': Isopeda_leishmanni
'731': Isopeda_montana
'732': Isopeda_queenslandensis
'733': Isopeda_vasta
'734': Isopeda_villosa
'735': Isopedella_cerussata
'736': Isopedella_flavida
'737': Isopedella_leai
'738': Isopedella_pessleri
'739': Isopedella_victorialis
'740': Isoxya_cicatricosa
'741': Isoxya_tabulata
'742': Ixodes_holocyclus
'743': Ixodes_pacificus
'744': Ixodes_persulcatus
'745': Ixodes_ricinus
'746': Ixodes_scapularis
'747': Jaguajir_rochae
'748': Janula_bicornis
'749': Javanimetrus_cyaneus
'750': Jotus_auripes
'751': Jotus_frosti
'752': Judalana_lutea
'753': Kankuamo_marquezi
'754': Kelawakaju_frenata
'755': Kochiura_aulica
'756': Kovarikia_angelena
'757': Kovarikia_oxy
'758': Kovarikia_williamsi
'759': Krateromaspis_dilatata
'760': Kukulcania_arizonica
'761': Kukulcania_hibernalis
'762': Labulla_thoracica
'763': Lacinius_dentiger
'764': Lacinius_ephippiatus
'765': Lacinius_horridus
'766': Lampona_cylindrata
'767': Lampona_murina
'768': Larinia_borealis
'769': Larinia_directa
'770': Larinia_lineata
'771': Larinioides_cornutus
'772': Larinioides_ixobolus
'773': Larinioides_patagiatus
'774': Larinioides_sclopetarius
'775': Lathys_humilis
'776': Latonigena_auricomis
'777': Latrodectus_bishopi
'778': Latrodectus_curacaviensis
'779': Latrodectus_geometricus
'780': Latrodectus_hasselti
'781': Latrodectus_hesperus
'782': Latrodectus_katipo
'783': Latrodectus_mactans
'784': Latrodectus_mirabilis
'785': Latrodectus_renivulvatus
'786': Latrodectus_tredecimguttatus
'787': Latrodectus_variolus
'788': Leiobunum_aldrichi
'789': Leiobunum_bimaculatum
'790': Leiobunum_blackwalli
'791': Leiobunum_calcar
'792': Leiobunum_exilipes
'793': Leiobunum_flavum
'794': Leiobunum_gracile
'795': Leiobunum_limbatum
'796': Leiobunum_nigropalpi
'797': Leiobunum_rotundum
'798': Leiobunum_townsendi
'799': Leiobunum_uxorium
'800': Leiobunum_ventricosum
'801': Leiobunum_verrucosum
'802': Leiobunum_vittatum
'803': Leiurus_hebraeus
'804': Leptobunus_parvulus
'805': Leptofreya_ambigua
'806': Leptorchestes_berolinensis
'807': Leucauge_argentina
'808': Leucauge_argyra
'809': Leucauge_argyrobapta
'810': Leucauge_blanda
'811': Leucauge_celebesiana
'812': Leucauge_decorata
'813': Leucauge_dromedaria
'814': Leucauge_fastigata
'815': Leucauge_festiva
'816': Leucauge_granulata
'817': Leucauge_licina
'818': Leucauge_mariana
'819': Leucauge_regnyi
'820': Leucauge_tessellata
'821': Leucauge_venusta
'822': Leucauge_volupis
'823': Leuronychus_pacificus
'824': Leviana_dimidiata
'825': Leviellus_stroemi
'826': Ligurra_latidens
'827': Linyphia_hortensis
'828': Linyphia_triangularis
'829': Liocheles_australasiae
'830': Liocranum_rupicola
'831': Liophrurillus_flavitarsis
'832': Lophopilio_palpinalis
'833': Loxosceles_amazonica
'834': Loxosceles_deserta
'835': Loxosceles_laeta
'836': Loxosceles_reclusa
'837': Loxosceles_rufescens
'838': Loxosceles_tenochtitlan
'839': Loxosceles_yucatana
'840': Lupettiana_mordax
'841': Lurio_conspicuus
'842': Lychas_marmoreus
'843': Lychas_mucronatus
'844': Lychas_scutilus
'845': Lychas_variatus
'846': Lycosa_erythrognatha
'847': Lycosa_hispanica
'848': Lycosa_pampeana
'849': Lycosa_praegrandis
'850': Lycosa_singoriensis
'851': Lycosa_tarantula
'852': Lycosoides_coarctata
'853': Lyssomanes_pauper
'854': Lyssomanes_viridis
'855': Macaroeris_nidicolens
'856': Macracantha_arcuata
'857': Macracantha_hasselti
'858': Macrothele_calpeiana
'859': Maeota_dichrura
'860': Maevia_inclemens
'861': Maimuna_vestita
'862': Mangora_acalypha
'863': Mangora_gibberosa
'864': Mangora_maculata
'865': Mangora_placida
'866': Mangora_spiculata
'867': Manogea_porracea
'868': Maratus_anomalus
'869': Maratus_chrysomelas
'870': Maratus_expolitus
'871': Maratus_griseus
'872': Maratus_harrisi
'873': Maratus_karrie
'874': Maratus_leo
'875': Maratus_literatus
'876': Maratus_pavonis
'877': Maratus_plumosus
'878': Maratus_scutulatus
'879': Maratus_tasmanicus
'880': Maratus_vespertilio
'881': Maratus_volans
'882': Marchena_minuta
'883': Marma_nigritarsis
'884': Marpissa_formosa
'885': Marpissa_lineata
'886': Marpissa_muscosa
'887': Marpissa_nivoyi
'888': Marpissa_obtusa
'889': Marpissa_pikei
'890': Marpissa_radiata
'891': Massuria_simplex
'892': Mastigoproctus_giganteus
'893': Mastigoproctus_tohono
'894': Mastophora_cornigera
'895': Mastophora_phrynosoma
'896': Mecaphesa_asperata
'897': Mecaphesa_celer
'898': Mecynogea_lemniscata
'899': Megabunus_diadema
'900': Megadolomedes_trux
'901': Megafreya_sutrix
'902': Megahexura_fulva
'903': Megaphobema_mesomelas
'904': Megaphobema_velvetosoma
'905': Mendoza_canestrinii
'906': Menemerus_bivittatus
'907': Menemerus_nigli
'908': Menemerus_semilimbatus
'909': Menemerus_taeniatus
'910': Meriola_decepta
'911': Messua_limbata
'912': Meta_bourneti
'913': Meta_menardi
'914': Meta_ovalis
'915': Metacyrba_floridana
'916': Metacyrba_punctata
'917': Metacyrba_taeniola
'918': Metaltella_simoni
'919': Metaphalangium_cirtanum
'920': Metaphidippus_chera
'921': Metaphidippus_manni
'922': Metaphidippus_siticulosus
'923': Metaplatybunus_grandissimus
'924': Metazygia_wittfeldae
'925': Metazygia_zilloides
'926': Metellina_curtisi
'927': Metellina_mengei
'928': Metellina_merianae
'929': Metellina_segmentata
'930': Metepeira_labyrinthea
'931': Mexcala_elegans
'932': Mexigonus_minutus
'933': Micrathena_acuta
'934': Micrathena_brevipes
'935': Micrathena_clypeata
'936': Micrathena_crassa
'937': Micrathena_duodecimspinosa
'938': Micrathena_fissispina
'939': Micrathena_funebris
'940': Micrathena_furcata
'941': Micrathena_gracilis
'942': Micrathena_horrida
'943': Micrathena_kirbyi
'944': Micrathena_lucasi
'945': Micrathena_mitrata
'946': Micrathena_nigrichelis
'947': Micrathena_patruelis
'948': Micrathena_pichincha
'949': Micrathena_picta
'950': Micrathena_plana
'951': Micrathena_pungens
'952': Micrathena_raimondi
'953': Micrathena_saccata
'954': Micrathena_sagittata
'955': Micrathena_sanctispiritus
'956': Micrathena_schreibersi
'957': Micrathena_sexspinosa
'958': Micrathena_swainsoni
'959': Micrathena_triangularis
'960': Micrathena_vigorsi
'961': Microlinyphia_dana
'962': Microlinyphia_pusilla
'963': Micrommata_ligurina
'964': Micrommata_virescens
'965': Micropholcus_fauroti
'966': Mimetus_laevigatus
'967': Mimetus_puritanus
'968': Mischonyx_squalidus
'969': Missulena_bradleyi
'970': Missulena_occatoria
'971': Misumena_spinifera
'972': Misumena_vatia
'973': Misumenoides_formosipes
'974': Misumenops_callinurus
'975': Misumenops_maculissparsus
'976': Misumenops_rubrodecoratus
'977': Misumessus_oblongus
'978': Mitopus_glacialis
'979': Mitopus_morio
'980': Mitostoma_chrysomelas
'981': Mituliodon_tarantulinus
'982': Molinaranea_clymene
'983': Monaeses_paradoxus
'984': Mopsus_mormon
'985': Myrmaplata_plataleoides
'986': Myrmarachne_formicaria
'987': Myrmarachne_formosana
'988': Myrmarachne_ichneumon
'989': Myrmarachne_japonica
'990': Myrmarachne_melanocephala
'991': Myrmekiaphila_comstocki
'992': Nanometa_lagenifera
'993': Naphrys_acerba
'994': Naphrys_pulex
'995': Natta_horizontalis
'996': Nelima_doriae
'997': Nelima_paessleri
'998': Nemastoma_bimaculatum
'999': Nemastoma_lugubre
'1000': Neomolgus_littoralis
'1001': Neopantopsalis_pentheter
'1002': Neoscona_adianta
'1003': Neoscona_arabesca
'1004': Neoscona_byzanthina
'1005': Neoscona_crucifera
'1006': Neoscona_domiciliorum
'1007': Neoscona_mellotteei
'1008': Neoscona_moreli
'1009': Neoscona_nautica
'1010': Neoscona_oaxacensis
'1011': Neoscona_orizabensis
'1012': Neoscona_punctigera
'1013': Neoscona_scylla
'1014': Neoscona_scylloides
'1015': Neoscona_subfusca
'1016': Neoscona_theisi
'1017': Neoscona_triangula
'1018': Neoscona_vigilans
'1019': Neosparassus_calligaster
'1020': Neosparassus_diana
'1021': Neosparassus_magareyi
'1022': Neosparassus_patellatus
'1023': Neosparassus_salacius
'1024': Neospintharus_trigonum
'1025': Neotama_mexicana
'1026': Neottiura_bimaculata
'1027': Nephila_kuhli
'1028': Nephila_pilipes
'1029': Nephila_vitiana
'1030': Nephilengys_malabarensis
'1031': Nephilengys_papuana
'1032': Nephilingis_cruentata
'1033': Nephilingis_livida
'1034': Neriene_clathrata
'1035': Neriene_digna
'1036': Neriene_emphana
'1037': Neriene_litigiosa
'1038': Neriene_montana
'1039': Neriene_peltata
'1040': Neriene_radiata
'1041': Nesticodes_rufipes
'1042': Nesticus_cellulanus
'1043': Nicodamus_peregrinus
'1044': Nigma_flavescens
'1045': Nigma_linsdalei
'1046': Nigma_puella
'1047': Nigma_walckenaeri
'1048': Nihonhimea_mundula
'1049': Nihonhimea_tesselata
'1050': Nilus_albocinctus
'1051': Novakiella_trituberculosa
'1052': Novaranea_queribunda
'1053': Nuctenea_umbratica
'1054': Nungia_epigynalis
'1055': Nurscia_albomaculata
'1056': Nycerella_delecta
'1057': Nyssus_albopunctatus
'1058': Nyssus_coloripes
'1059': Ocrisiona_leucocomis
'1060': Odiellus_lendlii
'1061': Odiellus_pictus
'1062': Odiellus_spinosus
'1063': Oecobius_maculatus
'1064': Oecobius_navus
'1065': Oligolophus_hansenii
'1066': Oligolophus_tridens
'1067': Olios_argelasius
'1068': Olios_giganteus
'1069': Olios_lamarcki
'1070': Opilio_canestrinii
'1071': Opilio_parietinus
'1072': Opilio_saxatilis
'1073': Opisthacanthus_asper
'1074': Opisthacanthus_capensis
'1075': Opisthacanthus_validus
'1076': Opisthoncus_abnormis
'1077': Opisthoncus_nigrofemoratus
'1078': Opisthoncus_polyphemus
'1079': Opisthoncus_quadratarius
'1080': Opisthoncus_serratofasciatus
'1081': Opisthoncus_sexmaculatus
'1082': Opistophthalmus_capensis
'1083': Opistophthalmus_carinatus
'1084': Opistophthalmus_glabrifrons
'1085': Opistophthalmus_karrooensis
'1086': Opistophthalmus_macer
'1087': Opistophthalmus_pallipes
'1088': Opistophthalmus_pugnax
'1089': Opistophthalmus_wahlbergii
'1090': Ordgarius_magnificus
'1091': Ortholasma_rugosum
'1092': Ostearius_melanopygius
'1093': Oxyopes_amoenus
'1094': Oxyopes_flavipalpis
'1095': Oxyopes_gracilipes
'1096': Oxyopes_heterophthalmus
'1097': Oxyopes_lineatus
'1098': Oxyopes_macilentus
'1099': Oxyopes_ramosus
'1100': Oxyopes_salticus
'1101': Oxyopes_scalaris
'1102': Oxyopes_sertatus
'1103': Oxyopes_shweta
'1104': Oxyopes_tridens
'1105': Oxyopes_variabilis
'1106': Oxytate_striatipes
'1107': Oxytate_virens
'1108': Ozyptila_pacifica
'1109': Ozyptila_praticola
'1110': Pachygnatha_autumnalis
'1111': Pachygnatha_clercki
'1112': Pachygnatha_degeeri
'1113': Pachygnatha_listeri
'1114': Pachyloides_thorellii
'1115': Paidiscura_pallens
'1116': Palpimanus_gibbulus
'1117': Palystes_castaneus
'1118': Palystes_superciliosus
'1119': Pancorius_crassipes
'1120': Pandercetes_gracilis
'1121': Parabuthus_capensis
'1122': Parabuthus_granulatus
'1123': Parabuthus_planicauda
'1124': Parabuthus_raudus
'1125': Parabuthus_transvaalicus
'1126': Parabuthus_villosus
'1127': Paramaevia_poultoni
'1128': Paranemastoma_quadripunctatum
'1129': Paraphidippus_aurantius
'1130': Paraphidippus_fartilis
'1131': Paraphilaeus_daemeli
'1132': Paraphrynus_carolynae
'1133': Paraphrynus_laevifrons
'1134': Parasteatoda_lunata
'1135': Parasteatoda_tepidariorum
'1136': Parasynema_cirripes
'1137': Paratrochosina_amica
'1138': Paravaejovis_confusus
'1139': Paravaejovis_puritanus
'1140': Paravaejovis_spinigerus
'1141': Paravaejovis_waeringi
'1142': Parawixia_audax
'1143': Parawixia_bistriata
'1144': Parawixia_dehaani
'1145': Pardosa_amentata
'1146': Pardosa_lapidicina
'1147': Pardosa_mercurialis
'1148': Pardosa_moesta
'1149': Pardosa_wagleri
'1150': Parnaenus_cyanidens
'1151': Paroligolophus_agrestis
'1152': Paruroctonus_becki
'1153': Paruroctonus_boreus
'1154': Paruroctonus_silvestrii
'1155': Pediana_regina
'1156': Pelegrina_aeneola
'1157': Pelegrina_balia
'1158': Pelegrina_exigua
'1159': Pelegrina_flavipes
'1160': Pelegrina_galathea
'1161': Pelegrina_pervaga
'1162': Pelegrina_proterva
'1163': Pellenes_allegrii
'1164': Pellenes_geniculatus
'1165': Pellenes_nigrociliatus
'1166': Pellenes_seriatus
'1167': Pellenes_tripunctatus
'1168': Penthaleus_major
'1169': Peucetia_flava
'1170': Peucetia_longipalpis
'1171': Peucetia_rubrolineata
'1172': Peucetia_viridana
'1173': Peucetia_viridans
'1174': Peucetia_viridis
'1175': Phaeacius_malayensis
'1176': Phalangium_opilio
'1177': Phanias_albeolus
'1178': Phiale_formosa
'1179': Phiale_gratiosa
'1180': Phiale_guttata
'1181': Phiale_mimica
'1182': Phiale_roburifoliata
'1183': Phiale_tristis
'1184': Phidippus_adumbratus
'1185': Phidippus_apacheanus
'1186': Phidippus_ardens
'1187': Phidippus_arizonensis
'1188': Phidippus_asotus
'1189': Phidippus_audax
'1190': Phidippus_borealis
'1191': Phidippus_californicus
'1192': Phidippus_cardinalis
'1193': Phidippus_carneus
'1194': Phidippus_carolinensis
'1195': Phidippus_clarus
'1196': Phidippus_comatus
'1197': Phidippus_cruentus
'1198': Phidippus_cryptus
'1199': Phidippus_insignarius
'1200': Phidippus_johnsoni
'1201': Phidippus_mystaceus
'1202': Phidippus_nikites
'1203': Phidippus_octopunctatus
'1204': Phidippus_olympus
'1205': Phidippus_otiosus
'1206': Phidippus_pacosauritus
'1207': Phidippus_phoenix
'1208': Phidippus_pius
'1209': Phidippus_princeps
'1210': Phidippus_purpuratus
'1211': Phidippus_putnami
'1212': Phidippus_regius
'1213': Phidippus_texanus
'1214': Phidippus_tyrrelli
'1215': Phidippus_whitmani
'1216': Phidippus_workmani
'1217': Philaeus_chrysops
'1218': Philira_micans
'1219': Philodromus_dispar
'1220': Philodromus_fuscomarginatus
'1221': Philodromus_margaritatus
'1222': Philodromus_marxi
'1223': Philodromus_poecilus
'1224': Philodromus_rufus
'1225': Philoponella_congregabilis
'1226': Phintella_accentifera
'1227': Phintella_aequipes
'1228': Phintella_bifurcilinea
'1229': Phintella_castriesiana
'1230': Phintella_piatensis
'1231': Phintella_vittata
'1232': Phintelloides_versicolor
'1233': Phlegra_bresnieri
'1234': Phlegra_fasciata
'1235': Phlegra_hentzi
'1236': Pholcus_manueli
'1237': Pholcus_opilionoides
'1238': Pholcus_phalangioides
'1239': Phoneutria_boliviensis
'1240': Phoneutria_depilata
'1241': Phoneutria_fera
'1242': Phoneutria_nigriventer
'1243': Phoneutria_pertyi
'1244': Phoneutria_reidyi
'1245': Phonognatha_graeffei
'1246': Phoroncidia_sextuberculata
'1247': Phrixotrichus_vulpinus
'1248': Phrurolithus_festivus
'1249': Phrynarachne_ceylonica
'1250': Phrynarachne_katoi
'1251': Phrynarachne_rugosa
'1252': Phrynus_operculatus
'1253': Phycosoma_digitula
'1254': Phyllocoptes_didelphis
'1255': Phyllocoptes_eupadi
'1256': Phyllocoptes_goniothorax
'1257': Phyllocoptes_populi
'1258': Phylloneta_impressa
'1259': Phylloneta_pictipes
'1260': Physocyclus_globosus
'1261': Phytoptus_avellanae
'1262': Pimoa_altioculata
'1263': Pirata_piraticus
'1264': Pisaura_mirabilis
'1265': Pisaurina_dubia
'1266': Pisaurina_mira
'1267': Pisaurina_undulata
'1268': Pistius_truncatus
'1269': Pityohyphantes_phrygianus
'1270': Platnickina_mneon
'1271': Platnickina_tincta
'1272': Platybunus_pinetorum
'1273': Platycryptus_californicus
'1274': Platycryptus_undatus
'1275': Platyoides_walteri
'1276': Plebs_bradleyi
'1277': Plebs_eburnus
'1278': Plexippus_paykulli
'1279': Plexippus_petersi
'1280': Plexippus_setipes
'1281': Poecilopachys_australasia
'1282': Polybetes_pythagoricus
'1283': Polybetes_rapidus
'1284': Porrhothele_antipodiana
'1285': Portacosa_cinerea
'1286': Portia_schultzi
'1287': Poultonella_alboimmaculata
'1288': Prosoponoides_sinense
'1289': Prostheclina_amplior
'1290': Prostheclina_pallida
'1291': Protolophus_singularis
'1292': Psalmopoeus_cambridgei
'1293': Psalmopoeus_reduncus
'1294': Pseudeuophrys_erratica
'1295': Pseudeuophrys_lanigera
'1296': Pseudeuophrys_vafra
'1297': Pseudicius_encarpatus
'1298': Pseudogagrella_splendens
'1299': Pseudolychas_ochraceus
'1300': Pseudouroctonus_reddelli
'1301': Psilochorus_simoni
'1302': Pterinopelma_longisternale
'1303': Pterinopelma_roseum
'1304': Ptocasius_strupifer
'1305': Ptocasius_weyersi
'1306': Pulchellodromus_bistigma
'1307': Pulchellodromus_pulchellus
'1308': Pungalina_plurilineata
'1309': Pystira_ephippigera
'1310': Rabidosa_hentzi
'1311': Rabidosa_punctulata
'1312': Rabidosa_rabida
'1313': Rhene_flavicomans
'1314': Rhene_flavigera
'1315': Rhene_rubrigera
'1316': Rhipicephalus_sanguineus
'1317': Rhomphaea_fictilium
'1318': Rhomphaea_projiciens
'1319': Rhomphaea_urquharti
'1320': Rhysodromus_histrio
'1321': Rilaena_triangularis
'1322': Ruborridion_musivum
'1323': Runcinia_acuminata
'1324': Runcinia_grammica
'1325': Runcinioides_litteratus
'1326': Sadocus_asperatus
'1327': Sadocus_polyacanthus
'1328': Saitis_barbipes
'1329': Saitis_tauricus
'1330': Saitis_variegatus
'1331': Saitis_virgatus
'1332': Salpesia_squalida
'1333': Salsa_brisbanae
'1334': Salsa_fuliginata
'1335': Salticus_austinensis
'1336': Salticus_cingulatus
'1337': Salticus_mutabilis
'1338': Salticus_palpalis
'1339': Salticus_peckhamae
'1340': Salticus_propinquus
'1341': Salticus_scenicus
'1342': Salticus_zebraneus
'1343': Sandalodes_bipenicillatus
'1344': Sandalodes_scopifer
'1345': Sandalodes_superbus
'1346': Saphrys_rusticana
'1347': Sardinidion_blackwalli
'1348': Sarinda_hentzi
'1349': Sassacus_cyaneus
'1350': Sassacus_papenhoei
'1351': Sassacus_vitis
'1352': Schizocosa_avida
'1353': Schizocosa_malitiosa
'1354': Schizocosa_mccooki
'1355': Sclerobunus_nondimorphicus
'1356': Scotina_celans
'1357': Scotophaeus_blackwalli
'1358': Scytodes_atlacoya
'1359': Scytodes_fusca
'1360': Scytodes_globula
'1361': Scytodes_pallida
'1362': Scytodes_thoracica
'1363': Scytodes_univittata
'1364': Segestria_bavarica
'1365': Segestria_florentina
'1366': Segestria_pacifica
'1367': Segestria_senoculata
'1368': Selenops_mexicanus
'1369': Selenops_submaculosus
'1370': Sergiolus_capulatus
'1371': Sergiolus_montanus
'1372': Serradigitus_gertschi
'1373': Servaea_incana
'1374': Servaea_villosa
'1375': Sicarius_thomisoides
'1376': Sidymella_angularis
'1377': Sidymella_hirsuta
'1378': Sidymella_longipes
'1379': Sidymella_rubrosignata
'1380': Sidymella_trapezia
'1381': Siler_collingwoodi
'1382': Siler_cupreus
'1383': Siler_semiglaucus
'1384': Simaetha_tenuidens
'1385': Simitidion_simile
'1386': Singa_hamata
'1387': Singa_nitidula
'1388': Siro_rubens
'1389': Sittisax_ranieri
'1390': Smeringopus_pallidus
'1391': Smeringurus_mesaensis
'1392': Smeringurus_vachoni
'1393': Socca_pustulosa
'1394': Soerensenella_prehensor
'1395': Sosippus_californicus
'1396': Spartaeus_spinimanus
'1397': Spermophora_senoculata
'1398': Sphodros_niger
'1399': Sphodros_rufipes
'1400': Spintharus_flavidus
'1401': Spiracme_striatipes
'1402': Steatoda_albomaculata
'1403': Steatoda_ancorata
'1404': Steatoda_bipunctata
'1405': Steatoda_borealis
'1406': Steatoda_capensis
'1407': Steatoda_castanea
'1408': Steatoda_grossa
'1409': Steatoda_lepida
'1410': Steatoda_nobilis
'1411': Steatoda_paykulliana
'1412': Steatoda_triangulosa
'1413': Stegodyphus_dumicola
'1414': Stegodyphus_lineatus
'1415': Stegodyphus_sarasinorum
'1416': Stemonyphantes_lineatus
'1417': Stenacis_euonymi
'1418': Stenacis_triradiata
'1419': Stephanopis_altifrons
'1420': Stephanopis_barbipes
'1421': Stephanopis_carcinoides
'1422': Stiphidion_facetum
'1423': Strigoplus_guizhouensis
'1424': Sumampattus_quinqueradiatus
'1425': Superstitionia_donensis
'1426': Synageles_venator
'1427': Synema_globosum
'1428': Synema_imitatrix
'1429': Synema_parvulum
'1430': Synemosyna_formica
'1431': Talavera_minuta
'1432': Tamopsis_brisbanensis
'1433': Tamopsis_fickerti
'1434': Tamopsis_tweedensis
'1435': Tapinillus_longipes
'1436': Tarkas_maculatipes
'1437': Tegenaria_domestica
'1438': Tegenaria_ferruginea
'1439': Tegenaria_parietina
'1440': Telamonia_caprina
'1441': Telamonia_dimidiata
'1442': Telamonia_festiva
'1443': Telamonia_vlijmi
'1444': Telaprocera_maudae
'1445': Teminius_affinis
'1446': Teminius_insularis
'1447': Terralonus_californicus
'1448': Tetragnatha_extensa
'1449': Tetragnatha_hasselti
'1450': Tetragnatha_laboriosa
'1451': Tetragnatha_montana
'1452': Tetragnatha_obtusa
'1453': Tetragnatha_squamata
'1454': Tetragnatha_versicolor
'1455': Tetragnatha_viridis
'1456': Tetranychus_lintearius
'1457': Tetranychus_urticae
'1458': Teuthraustes_atramentarius
'1459': Textrix_denticulata
'1460': Thanatus_formicinus
'1461': Tharpyna_campestrata
'1462': Tharpyna_decorata
'1463': Thaumasia_velox
'1464': Thelacantha_brevispina
'1465': Thelcticopis_severa
'1466': Theraphosa_blondi
'1467': Theridion_pyramidale
'1468': Theridion_varians
'1469': Theridion_zonulatum
'1470': Theridiosoma_gemmosum
'1471': Theridula_emertoni
'1472': Theridula_gonygaster
'1473': Thiania_bhamoensis
'1474': Thiania_suboppressa
'1475': Thomisus_citrinellus
'1476': Thomisus_labefactus
'1477': Thomisus_onustus
'1478': Thomisus_scrupeus
'1479': Thomisus_spectabilis
'1480': Thorelliola_ensifera
'1481': Thwaitesia_margaritifera
'1482': Thwaitesia_nigronodosa
'1483': Thyene_coccineovittata
'1484': Thyene_imperialis
'1485': Thyene_inflata
'1486': Thyene_natalii
'1487': Thyene_ogdeni
'1488': Thyene_orientalis
'1489': Tibellus_oblongus
'1490': Tigrosa_annexa
'1491': Tigrosa_aspersa
'1492': Tigrosa_georgicola
'1493': Tigrosa_helluo
'1494': Tinus_peregrinus
'1495': Titanattus_andinus
'1496': Tityus_carrilloi
'1497': Tityus_columbianus
'1498': Tityus_metuendus
'1499': Tityus_obscurus
'1500': Tityus_serrulatus
'1501': Tityus_stigmurus
'1502': Tliltocatl_epicureanus
'1503': Tliltocatl_kahlenbergi
'1504': Tliltocatl_vagans
'1505': Tmarus_angulatus
'1506': Tmarus_piger
'1507': Togwoteeus_biceps
'1508': Tomopisthes_horrendus
'1509': Toxeus_magnus
'1510': Toxeus_maxillosus
'1511': Toxopsoides_huttoni
'1512': Trachelas_pacificus
'1513': Trachelas_tranquillus
'1514': Trachyzelotes_pedestris
'1515': Trichonephila_antipodiana
'1516': Trichonephila_clavata
'1517': Trichonephila_clavipes
'1518': Trichonephila_edulis
'1519': Trichonephila_fenestrata
'1520': Trichonephila_inaurata
'1521': Trichonephila_plumipes
'1522': Trichonephila_senegalensis
'1523': Trichonephila_sexpunctata
'1524': Trite_auricoma
'1525': Trite_mustilina
'1526': Trite_planiceps
'1527': Trochosa_ruricola
'1528': Trochosa_sepulchralis
'1529': Trochosa_terricola
'1530': Tropicosa_moesta
'1531': Tutelina_elegans
'1532': Tutelina_harti
'1533': Tutelina_similis
'1534': Tylorida_striata
'1535': Tylorida_ventralis
'1536': Typopeltis_crucifer
'1537': Typostola_barbata
'1538': Uliodon_albopunctatus
'1539': Uloborus_diversus
'1540': Uloborus_glomosus
'1541': Uloborus_plumipes
'1542': Uloborus_walckenaerius
'1543': Ummidia_audouini
'1544': Uroctea_durandi
'1545': Uroctonites_montereus
'1546': Uroctonus_mordax
'1547': Urodacus_manicatus
'1548': Urodacus_novaehollandiae
'1549': Uroplectes_carinatus
'1550': Uroplectes_flavoviridis
'1551': Uroplectes_formosus
'1552': Uroplectes_lineatus
'1553': Uroplectes_planimanus
'1554': Uroplectes_triangulifer
'1555': Uroplectes_vittatus
'1556': Vaejovis_carolinianus
'1557': Vaejovis_deboerae
'1558': Vaejovis_mexicanus
'1559': Varroa_destructor
'1560': Vasates_aceriscrumena
'1561': Vasates_quadripedes
'1562': Vectius_niger
'1563': Venator_immansuetus
'1564': Venator_spenceri
'1565': Venatrix_furcillata
'1566': Ventrivomer_ancyrophorus
'1567': Verrucosa_arenata
'1568': Verrucosa_meridionalis
'1569': Verrucosa_scapofracta
'1570': Verrucosa_undecimvariolata
'1571': Viciria_pavesii
'1572': Vicirionessa_mustela
'1573': Vonones_sayi
'1574': Wadicosa_fidelis
'1575': Wagneriana_spicata
'1576': Wagneriana_tauricornis
'1577': Witica_crassicauda
'1578': Wulfila_albens
'1579': Wulfila_saltabundus
'1580': Xerolycosa_miniata
'1581': Xerolycosa_nemoralis
'1582': Xysticus_cristatus
'1583': Xysticus_kochi
'1584': Xysticus_lanio
'1585': Xysticus_punctatus
'1586': Xysticus_texanus
'1587': Xysticus_ulmi
'1588': Yllenus_arenarius
'1589': Yllenus_uiguricus
'1590': Yllenus_zyuzini
'1591': Yunohamella_lyrica
'1592': Zachaeus_crista
'1593': Zealaranea_crassa
'1594': Zenodorus_orbiculatus
'1595': Zenodorus_swiftorum
'1596': Zilla_diodia
'1597': Zimiris_doriae
'1598': Zora_spinimana
'1599': Zoropsis_spinimana
'1600': Zosis_geniculata
'1601': Zygiella_atrica
'1602': Zygiella_x-notata
'1603': Zygoballus_nervosus
'1604': Zygoballus_rufipes
'1605': Zygoballus_sexpunctatus
'1606': Zygometis_xanthogaster
splits:
- name: train
num_bytes: 38785458087.024
num_examples: 2049928
download_size: 41403446692
dataset_size: 38785458087.024
---
# Dataset Card for "inatSpiders"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 59,525 | [
[
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0.039093017578125,
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-0.039276123046875,
-0.04400634765625,
... |
tinhpx2911/thanhnien_raw_html | 2023-10-05T04:49:07.000Z | [
"region:us"
] | tinhpx2911 | null | null | 0 | 0 | 2023-10-05T04:45:47 | Entry not found | 15 | [
[
-0.0213775634765625,
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0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
BangumiBase/karakaijouzunotakagisan | 2023-10-05T08:19:45.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T05:28:26 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Karakai Jouzu No Takagi-san
This is the image base of bangumi Karakai Jouzu no Takagi-san, we detected 21 characters, 6297 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 | 2534 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 205 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 45 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 37 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 36 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 17 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 108 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 16 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 56 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 13 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 344 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 2029 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 46 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 292 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 81 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 255 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 17 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 16 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 5 | [Download](18/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 19 | 30 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 115 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,829 | [
[
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0.0104827880859375,
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0.04046630859375,
0.0305633544921875,
-0.05950927734375,
-0.053558349609375,
-0.0421142578125,
0... |
BangumiBase/denpaonnatoseishunotoko | 2023-10-05T06:36:29.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T05:30:06 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Denpa Onna To Seishun Otoko
This is the image base of bangumi Denpa Onna to Seishun Otoko, we detected 15 characters, 1491 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 | 109 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 106 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 16 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 126 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 22 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 546 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 13 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 163 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 8 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 29 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 8 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 185 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 26 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 5 | [Download](13/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 129 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 5,945 | [
[
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0.00943756103515625,
0.01513671875,
-0.017578125,
-0.00888824462890625,
-0.0005474090576171875,
-0.0235137939453125,
0.038818359375,
0.03472900390625,
-0.058990478515625,
-0.052642822265625,
-0.044189453125,
0.032562255859... |
BangumiBase/kagenojitsuryokushaninaritakute | 2023-10-05T07:01:47.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T05:42:20 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Kage No Jitsuryokusha Ni Naritakute!
This is the image base of bangumi Kage no Jitsuryokusha ni Naritakute!, we detected 41 characters, 1746 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 | 259 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 83 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 36 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 30 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 26 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 15 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 27 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 7 | [Download](7/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 8 | 44 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 16 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 10 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 17 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 23 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 25 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 23 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 27 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 19 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 16 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 16 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 13 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 20 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 41 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 11 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 12 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 10 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 87 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 70 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 44 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 19 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 63 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 23 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 9 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 9 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 22 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 51 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 9 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 8 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 9 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 38 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 7 | [Download](39/dataset.zip) |  |  |  |  |  |  |  | N/A |
| noise | 452 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 14,127 | [
[
-0.044158935546875,
-0.0094757080078125,
0.0077972412109375,
0.01513671875,
-0.016448974609375,
-0.004337310791015625,
-0.0031871795654296875,
-0.0243072509765625,
0.041473388671875,
0.031829833984375,
-0.060150146484375,
-0.0538330078125,
-0.042022705078125,
... |
autoevaluate/autoeval-eval-ag_news-default-f7fd0a-93091145748 | 2023-10-05T06:00:01.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T05:59:56 | Entry not found | 15 | [
[
-0.02142333984375,
-0.014984130859375,
0.057220458984375,
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0.052520751953125,
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0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060455322265625,
0.03793334... |
NobodyExistsOnTheInternet/AlpacaToxicQA | 2023-10-05T06:29:25.000Z | [
"region:us"
] | NobodyExistsOnTheInternet | null | null | 0 | 0 | 2023-10-05T06:22:34 | 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... |
dhanush23/aaa1 | 2023-10-05T06:23:18.000Z | [
"region:us"
] | dhanush23 | null | null | 0 | 0 | 2023-10-05T06:23:18 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
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0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
BangumiBase/isekainonbirinouka | 2023-10-05T07:40:00.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T06:40:21 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Isekai Nonbiri Nouka
This is the image base of bangumi Isekai Nonbiri Nouka, we detected 41 characters, 1820 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 | 619 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 6 | [Download](1/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 2 | 8 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 16 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 7 | [Download](4/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 5 | 30 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 10 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 7 | [Download](7/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 8 | 156 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 41 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 14 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 15 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 105 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 209 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 42 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 10 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 16 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 18 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 20 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 21 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 8 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 47 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 6 | [Download](22/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 23 | 18 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 17 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 55 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 57 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 7 | [Download](27/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 28 | 10 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 5 | [Download](29/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 30 | 11 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 11 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 26 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 7 | [Download](33/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 34 | 8 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 13 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 7 | [Download](36/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 37 | 9 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 18 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 10 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 100 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 14,095 | [
[
-0.043975830078125,
-0.0092010498046875,
0.0089569091796875,
0.01445770263671875,
-0.0184173583984375,
-0.005680084228515625,
0.000009417533874511719,
-0.0245513916015625,
0.04278564453125,
0.033050537109375,
-0.0601806640625,
-0.05517578125,
-0.04351806640625,
... |
BangumiBase/datealive | 2023-10-05T11:59:27.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T06:42:20 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Date A Live
This is the image base of bangumi DATE A LIVE, we detected 92 characters, 9273 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 | 348 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 105 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 67 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 84 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 42 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 2476 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 108 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 82 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 63 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 33 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 54 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 789 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 40 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 132 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 19 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 12 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 25 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 15 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 12 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 26 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 15 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 40 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 21 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 60 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 60 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 32 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 65 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 27 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 13 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 13 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 30 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 16 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 12 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 35 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 94 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 207 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 402 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 156 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 64 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 23 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 34 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 45 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 19 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 26 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 691 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 43 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 15 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 373 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 16 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 48 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 76 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 22 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 124 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
| 53 | 22 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 42 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 6 | [Download](55/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 56 | 29 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 114 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 38 | [Download](58/dataset.zip) |  |  |  |  |  |  |  |  |
| 59 | 430 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 13 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 17 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 17 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 13 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| 64 | 15 | [Download](64/dataset.zip) |  |  |  |  |  |  |  |  |
| 65 | 22 | [Download](65/dataset.zip) |  |  |  |  |  |  |  |  |
| 66 | 35 | [Download](66/dataset.zip) |  |  |  |  |  |  |  |  |
| 67 | 219 | [Download](67/dataset.zip) |  |  |  |  |  |  |  |  |
| 68 | 44 | [Download](68/dataset.zip) |  |  |  |  |  |  |  |  |
| 69 | 44 | [Download](69/dataset.zip) |  |  |  |  |  |  |  |  |
| 70 | 9 | [Download](70/dataset.zip) |  |  |  |  |  |  |  |  |
| 71 | 8 | [Download](71/dataset.zip) |  |  |  |  |  |  |  |  |
| 72 | 34 | [Download](72/dataset.zip) |  |  |  |  |  |  |  |  |
| 73 | 47 | [Download](73/dataset.zip) |  |  |  |  |  |  |  |  |
| 74 | 15 | [Download](74/dataset.zip) |  |  |  |  |  |  |  |  |
| 75 | 35 | [Download](75/dataset.zip) |  |  |  |  |  |  |  |  |
| 76 | 15 | [Download](76/dataset.zip) |  |  |  |  |  |  |  |  |
| 77 | 17 | [Download](77/dataset.zip) |  |  |  |  |  |  |  |  |
| 78 | 18 | [Download](78/dataset.zip) |  |  |  |  |  |  |  |  |
| 79 | 12 | [Download](79/dataset.zip) |  |  |  |  |  |  |  |  |
| 80 | 8 | [Download](80/dataset.zip) |  |  |  |  |  |  |  |  |
| 81 | 9 | [Download](81/dataset.zip) |  |  |  |  |  |  |  |  |
| 82 | 14 | [Download](82/dataset.zip) |  |  |  |  |  |  |  |  |
| 83 | 11 | [Download](83/dataset.zip) |  |  |  |  |  |  |  |  |
| 84 | 8 | [Download](84/dataset.zip) |  |  |  |  |  |  |  |  |
| 85 | 11 | [Download](85/dataset.zip) |  |  |  |  |  |  |  |  |
| 86 | 9 | [Download](86/dataset.zip) |  |  |  |  |  |  |  |  |
| 87 | 24 | [Download](87/dataset.zip) |  |  |  |  |  |  |  |  |
| 88 | 6 | [Download](88/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 89 | 20 | [Download](89/dataset.zip) |  |  |  |  |  |  |  |  |
| 90 | 19 | [Download](90/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 355 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 30,091 | [
[
-0.041015625,
-0.01090240478515625,
0.00791168212890625,
0.01476287841796875,
-0.017181396484375,
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0.040313720703125,
0.031768798828125,
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-0.0535888671875,
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0.03... |
autoevaluate/autoeval-eval-samsum-samsum-f09cc2-93106145752 | 2023-10-05T07:20:13.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T07:17:22 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- samsum
eval_info:
task: summarization
model: 0x70DA/pegasus-cnn_dailymail
metrics: []
dataset_name: samsum
dataset_config: samsum
dataset_split: test
col_mapping:
text: dialogue
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: 0x70DA/pegasus-cnn_dailymail
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Saravanan007](https://huggingface.co/Saravanan007) for evaluating this model. | 820 | [
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0.03271484375,
-0.0780029296875,
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... |
khursani8/tmp | 2023-10-05T07:44:38.000Z | [
"region:us"
] | khursani8 | null | null | 0 | 0 | 2023-10-05T07:41:32 | Entry not found | 15 | [
[
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-0.0604248046875,
0.0379028... |
jpata/particleflow-clic-clusters | 2023-10-05T07:47:48.000Z | [
"region:us"
] | jpata | null | null | 0 | 0 | 2023-10-05T07:47:48 | Entry not found | 15 | [
[
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0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
Fatma03/my-awesome-dataset | 2023-10-05T07:59:37.000Z | [
"region:us"
] | Fatma03 | null | null | 0 | 0 | 2023-10-05T07:59:37 | Entry not found | 15 | [
[
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0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
BangumiBase/fullmetalalchemist | 2023-10-05T14:29:27.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T08:12:39 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Fullmetal Alchemist
This is the image base of bangumi Fullmetal Alchemist, we detected 44 characters, 5107 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 | 1190 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 164 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 20 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 61 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 56 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 80 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 384 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 427 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 179 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 73 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 93 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 33 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 84 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 113 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 95 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 129 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 318 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 187 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 26 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 48 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 78 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 54 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 53 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 97 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 142 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 217 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 12 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 246 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 58 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 32 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 19 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 15 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 39 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 23 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 9 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 14 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 23 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 11 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 12 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 13 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 18 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 40 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 14 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 108 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 15,035 | [
[
-0.0413818359375,
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0.040435791015625,
0.033782958984375,
-0.0576171875,
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-0.04217529296875,... |
casey-martin/vquanda | 2023-10-05T08:46:50.000Z | [
"task_categories:table-question-answering",
"task_categories:text2text-generation",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"sparql",
"semantic web",
"knowledge graph",
"knowledge base",
"dbpedia",
"region:us"
] | casey-martin | null | null | 0 | 0 | 2023-10-05T08:17:39 | ---
license: cc-by-4.0
task_categories:
- table-question-answering
- text2text-generation
language:
- en
tags:
- sparql
- semantic web
- knowledge graph
- knowledge base
- dbpedia
pretty_name: VQuAnDa - Verbalization Question Answering Dataset
size_categories:
- 1K<n<10K
---
# VQuAnDa - Verbalization Question Answering Dataset
## Background
[VQuAnDa](https://dl.acm.org/doi/abs/10.1007/978-3-030-49461-2_31) is knowledge base QA dataset based on
[LC-QuAD](https://github.com/AskNowQA/LC-QuAD) which uses
[DBpedia v04.16](https://wiki.dbpedia.org/dbpedia-version-2016-04) as the target KB.
This QA task consists of two components:
1. A Text2Sparql task where a natural language query is translated to a SPARQL query.
2. An RDF triple to verbalized answer task where the knowledge base query result must be translated back into natural language.
The dataset is in JSON format, and it contains 5000 examples (4000 train/1000 test).
An example is shown below. The query result is surrounded by brackets `[]` in the verbalized answer.
```
{
"uid" : "3508"
"question" : "How many shows are aired on Comedy Central?"
"verbalized_answer" : "There are [73] television shows broadcasted by..."
"query" : "SELECT DISTINCT COUNT(?uri) WHERE {?uri <http:..."
}
```
## Baseline models
Alongside the dataset, the authors provide some baseline models.
[Here](https://github.com/endrikacupaj/VQUANDA-Baseline-Models) you can find the baseline implementations and instructions for how to run them.
## License
The dataset is under [Attribution 4.0 International (CC BY 4.0)](LICENSE)
## Cite
```
@InProceedings{kacupaj2020vquanda,
title={VQuAnDa: Verbalization QUestion ANswering DAtaset},
author={Kacupaj, Endri and Zafar, Hamid and Lehmann, Jens and Maleshkova, Maria},
booktitle={The Semantic Web},
pages={531--547},
year={2020},
publisher={Springer International Publishing},
}
``` | 1,995 | [
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RtwC/issues | 2023-10-05T08:22:48.000Z | [
"region:us"
] | RtwC | null | null | 0 | 0 | 2023-10-05T08:19:39 | Entry not found | 15 | [
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0.0379... |
apf1/datafilteringnetworks_2b | 2023-10-09T21:39:30.000Z | [
"license:cc-by-4.0",
"arxiv:2309.17425",
"region:us"
] | apf1 | null | null | 2 | 0 | 2023-10-05T08:21:45 | ---
license: cc-by-4.0
---
Paper Link: https://arxiv.org/abs/2309.17425 | 71 | [
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-0.028289794921875,
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BangumiBase/kuzunohonkai | 2023-10-05T09:25:29.000Z | [
"size_categories:n<1K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T08:31:14 | ---
license: mit
tags:
- art
size_categories:
- n<1K
---
# Bangumi Image Base of Kuzu No Honkai
This is the image base of bangumi Kuzu no Honkai, we detected 13 characters, 869 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 | 298 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 12 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 22 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 48 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 37 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 29 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 114 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 92 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 48 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 14 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 40 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 10 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 105 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 5,286 | [
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agucci/v | 2023-10-05T09:02:59.000Z | [
"region:us"
] | agucci | null | null | 0 | 0 | 2023-10-05T09:02:59 | Entry not found | 15 | [
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0.03790283... |
bongoServer2112/oct-04-2023-veeam-agent-full-backup-dataset | 2023-10-05T15:33:57.000Z | [
"region:us"
] | bongoServer2112 | null | null | 0 | 0 | 2023-10-05T09:10:23 | Entry not found | 15 | [
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0.03790283... |
autoevaluate/autoeval-eval-dair-ai__emotion-split-3c2153-93136145758 | 2023-10-05T09:16:56.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T09:16:29 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- dair-ai/emotion
eval_info:
task: multi_class_classification
model: esuriddick/distilbert-base-uncased-finetuned-emotion
metrics: []
dataset_name: dair-ai/emotion
dataset_config: split
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: esuriddick/distilbert-base-uncased-finetuned-emotion
* Dataset: dair-ai/emotion
* Config: split
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | 906 | [
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autoevaluate/autoeval-eval-dair-ai__emotion-split-3c2153-93136145759 | 2023-10-05T09:16:41.000Z | [
"region:us"
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autoevaluate/autoeval-eval-dair-ai__emotion-split-3c2153-93136145760 | 2023-10-05T09:16:46.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T09:16:41 | Entry not found | 15 | [
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huggingface/site-images | 2023-10-05T09:49:17.000Z | [
"region:us"
] | huggingface | null | null | 0 | 0 | 2023-10-05T09:48:06 | Entry not found | 15 | [
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0.03790283... |
MilitaryACE/JohnZ_Data | 2023-10-05T09:52:18.000Z | [
"region:us"
] | MilitaryACE | null | null | 0 | 0 | 2023-10-05T09:52:18 | Entry not found | 15 | [
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0.0169830322265625,
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0.03790283... |
hongyin/pretrain | 2023-10-05T10:14:48.000Z | [
"region:us"
] | hongyin | null | null | 0 | 0 | 2023-10-05T10:14:48 | Entry not found | 15 | [
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0.005069732666015625,
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0.0169830322265625,
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0.03790283... |
BangumiBase/demichanwakataritai | 2023-10-05T11:40:25.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T10:24:57 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Demi-chan Wa Kataritai
This is the image base of bangumi Demi-chan wa Kataritai, we detected 16 characters, 1889 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 | 379 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 33 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 221 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 373 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 35 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 59 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 11 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 75 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 14 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 18 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 34 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 20 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 252 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 203 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 87 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 75 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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daraiii/test | 2023-10-05T10:37:49.000Z | [
"language:ja",
"license:unknown",
"region:us"
] | daraiii | null | null | 0 | 0 | 2023-10-05T10:33:12 | ---
license: unknown
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: image
dtype: image
splits:
- name: train
num_bytes: 50283
num_examples: 1
download_size: 50580
dataset_size: 50283
language:
- ja
---
# これはうｐテストだよ This is uploading test.
## Dataset Description, Summary
サムネ画像 my thumbnail.
7z か parquet
やがて消す | 409 | [
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0.020660400... |
autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145766 | 2023-10-05T10:52:02.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T10:51:58 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145767 | 2023-10-05T10:52:08.000Z | [
"region:us"
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autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145768 | 2023-10-05T10:52:13.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T10:52:09 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145769 | 2023-10-05T10:52:20.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T10:52:16 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145770 | 2023-10-05T10:52:25.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T10:52:21 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-imdb-plain_text-046839-93153145771 | 2023-10-05T10:52:32.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T10:52:28 | Entry not found | 15 | [
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mayur456/langchain_docs | 2023-10-05T10:59:01.000Z | [
"region:us"
] | mayur456 | null | null | 0 | 0 | 2023-10-05T10:52:29 | Entry not found | 15 | [
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CloudFish/Oday_loraV3 | 2023-10-05T11:06:40.000Z | [
"region:us"
] | CloudFish | null | null | 0 | 0 | 2023-10-05T11:05:43 | Entry not found | 15 | [
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librarian-bot/dataset_abstracts | 2023-10-05T11:10:41.000Z | [
"region:us"
] | librarian-bot | null | null | 0 | 0 | 2023-10-05T11:10:37 | Entry not found | 15 | [
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BangumiBase/naginoasukara | 2023-10-05T13:05:11.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T11:11:39 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Nagi No Asukara
This is the image base of bangumi Nagi no Asukara, we detected 23 characters, 3162 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 | 564 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 79 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 76 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 29 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 67 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 239 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 49 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 40 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 261 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 15 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 11 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 15 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 31 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 117 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 245 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 168 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 17 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 373 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 176 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 385 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 24 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 54 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 127 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 8,433 | [
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manlyboy/laion-dalle3 | 2023-10-05T11:13:29.000Z | [
"region:us"
] | manlyboy | null | null | 1 | 0 | 2023-10-05T11:12:33 | Entry not found | 15 | [
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sleepyboyeyes/Kim | 2023-10-05T14:36:39.000Z | [
"region:us"
] | sleepyboyeyes | null | null | 0 | 0 | 2023-10-05T11:48:11 | Entry not found | 15 | [
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BangumiBase/yuukiyuunawayuushadearu | 2023-10-05T14:27:28.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T12:08:05 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Yuuki Yuuna Wa Yuusha De Aru
This is the image base of bangumi Yuuki Yuuna wa Yuusha de Aru, we detected 27 characters, 3455 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 | 462 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 76 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 57 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 71 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 18 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 190 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 16 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 23 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 370 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 358 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 137 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 75 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 296 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 40 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 195 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 81 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 18 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 21 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 481 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 130 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 8 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 11 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 16 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 9 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 6 | [Download](24/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 25 | 6 | [Download](25/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 284 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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mcmohammad/test | 2023-10-05T13:16:51.000Z | [
"region:us"
] | mcmohammad | null | null | 0 | 0 | 2023-10-05T13:16:51 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad_v2-squad_v2-b97c64-93186145774 | 2023-10-05T13:23:35.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:23:31 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad_v2-squad_v2-a7ce38-93187145775 | 2023-10-05T13:38:49.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:38:45 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad_v2-squad_v2-bac899-93188145776 | 2023-10-05T13:38:53.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:38:49 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145777 | 2023-10-05T13:39:01.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:38:57 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145778 | 2023-10-05T13:39:05.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:01 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145779 | 2023-10-05T13:39:12.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:08 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145780 | 2023-10-05T13:39:19.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:16 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145781 | 2023-10-05T13:39:28.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:23 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-squad-plain_text-865c05-93189145782 | 2023-10-05T13:39:35.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:30 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-glue-cola-b842f7-93190145783 | 2023-10-05T13:39:41.000Z | [
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:37 | Entry not found | 15 | [
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autoevaluate/autoeval-eval-samsum-samsum-52efcb-93192145784 | 2023-10-05T13:41:45.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:44 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- samsum
eval_info:
task: summarization
model: sshleifer/distilbart-xsum-12-6
metrics: []
dataset_name: samsum
dataset_config: samsum
dataset_split: test
col_mapping:
text: dialogue
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: sshleifer/distilbart-xsum-12-6
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 810 | [
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autoevaluate/autoeval-eval-samsum-samsum-52efcb-93192145785 | 2023-10-05T13:42:14.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T13:39:51 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- samsum
eval_info:
task: summarization
model: sshleifer/distilbart-cnn-12-6
metrics: []
dataset_name: samsum
dataset_config: samsum
dataset_split: test
col_mapping:
text: dialogue
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: sshleifer/distilbart-cnn-12-6
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 808 | [
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-0.003877639770... |
berzanmikaili/gaussian-splatting | 2023-10-17T09:00:11.000Z | [
"region:us"
] | berzanmikaili | null | null | 0 | 0 | 2023-10-05T13:50:11 | Entry not found | 15 | [
[
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0.0379... |
wuming156/xxmix9realisticsdxl_v10 | 2023-10-13T12:54:46.000Z | [
"region:us"
] | wuming156 | null | null | 0 | 0 | 2023-10-05T14:12:56 | Entry not found | 15 | [
[
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0.0379... |
GiovanniHD/GiovanniVoice | 2023-10-05T14:13:00.000Z | [
"region:us"
] | GiovanniHD | null | null | 0 | 0 | 2023-10-05T14:13:00 | Entry not found | 15 | [
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0.0379... |
autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-36c277-93197145789 | 2023-10-05T17:41:31.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T14:20:13 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: google/pegasus-large
metrics: []
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: google/pegasus-large
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 811 | [
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autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-36c277-93197145790 | 2023-10-05T14:29:24.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T14:20:19 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: ainize/bart-base-cnn
metrics: []
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ainize/bart-base-cnn
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 811 | [
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autoevaluate/autoeval-eval-xsum-default-0288cc-93201145793 | 2023-10-05T14:57:36.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T14:49:20 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- xsum
eval_info:
task: summarization
model: ainize/bart-base-cnn
metrics: []
dataset_name: xsum
dataset_config: default
dataset_split: test
col_mapping:
text: document
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ainize/bart-base-cnn
* Dataset: xsum
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 786 | [
[
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autoevaluate/autoeval-eval-samsum-samsum-ccdc20-93203145794 | 2023-10-05T14:50:08.000Z | [
"autotrain",
"evaluation",
"region:us"
] | autoevaluate | null | null | 0 | 0 | 2023-10-05T14:49:24 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- samsum
eval_info:
task: summarization
model: ainize/bart-base-cnn
metrics: []
dataset_name: samsum
dataset_config: samsum
dataset_split: test
col_mapping:
text: dialogue
target: summary
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: ainize/bart-base-cnn
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@sasha](https://huggingface.co/sasha) for evaluating this model. | 790 | [
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loubnabnl/test_kaggle_3 | 2023-10-05T15:12:14.000Z | [
"region:us"
] | loubnabnl | null | null | 0 | 0 | 2023-10-05T15:10:30 | Entry not found | 15 | [
[
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freddyaboulton/alpaca-csv | 2023-10-05T15:13:26.000Z | [
"region:us"
] | freddyaboulton | null | null | 0 | 0 | 2023-10-05T15:12:45 | Entry not found | 15 | [
[
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0.0379... |
thrshr/cc12m_part_1b | 2023-10-06T06:05:00.000Z | [
"region:us"
] | thrshr | null | null | 0 | 0 | 2023-10-05T15:18:12 | Entry not found | 15 | [
[
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0.0379... |
thrshr/cc12m_part_2a | 2023-10-05T15:18:27.000Z | [
"region:us"
] | thrshr | null | null | 0 | 0 | 2023-10-05T15:18:27 | Entry not found | 15 | [
[
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thrshr/cc12m_part_2b | 2023-10-05T15:18:37.000Z | [
"region:us"
] | thrshr | null | null | 0 | 0 | 2023-10-05T15:18:37 | Entry not found | 15 | [
[
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BangumiBase/kaifukujutsushinoyarinaoshi | 2023-10-05T16:33:19.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T15:31:09 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Kaifuku Jutsushi No Yarinaoshi
This is the image base of bangumi Kaifuku Jutsushi no Yarinaoshi, we detected 27 characters, 1301 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 | 63 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 8 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 77 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 12 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 185 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 39 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 48 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 7 | [Download](7/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 8 | 143 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 208 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 25 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 8 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 7 | [Download](12/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 13 | 22 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 15 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 36 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 20 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 23 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 17 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 71 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 7 | [Download](20/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 21 | 6 | [Download](21/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 22 | 7 | [Download](22/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 23 | 24 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 7 | [Download](24/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 25 | 5 | [Download](25/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 211 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 9,719 | [
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SCLRM/pdf_chatbot | 2023-10-14T13:55:09.000Z | [
"region:us"
] | SCLRM | null | null | 0 | 0 | 2023-10-05T15:37:57 | Entry not found | 15 | [
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snirjhar-colab/probs50-val3d | 2023-10-05T15:50:08.000Z | [
"region:us"
] | snirjhar-colab | null | null | 0 | 0 | 2023-10-05T15:43:11 | Entry not found | 15 | [
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basilepp19/dolly-15k-it | 2023-10-05T15:48:15.000Z | [
"license:cc-by-nc-sa-3.0",
"region:us"
] | basilepp19 | null | null | 0 | 0 | 2023-10-05T15:44:12 | ---
license: cc-by-nc-sa-3.0
---
This dataset is obtained by automatically translating the dolly 15k dataset (https://huggingface.co/datasets/databricks/databricks-dolly-15k) in Italian using an open-source machine translation tool: https://pypi.org/project/argostranslate/ | 274 | [
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x1101/uraaaaa | 2023-10-05T15:52:01.000Z | [
"region:us"
] | x1101 | null | null | 0 | 0 | 2023-10-05T15:51:29 | Entry not found | 15 | [
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loubnabnl/test_kaggle_2 | 2023-10-05T16:08:33.000Z | [
"region:us"
] | loubnabnl | null | null | 0 | 0 | 2023-10-05T15:51:32 | Entry not found | 15 | [
[
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basilepp19/evalita2020-AH-instr | 2023-10-05T15:59:14.000Z | [
"license:cc-by-nd-4.0",
"region:us"
] | basilepp19 | null | null | 0 | 0 | 2023-10-05T15:55:07 | ---
license: cc-by-nd-4.0
---
This dataset is obtained by transforming the training and test data of the two EVALITA tasks into an LLM prompt following a template.
The involved tasks are: AMI2020 (misogyny detection) and HASPEEDE-v2-2020 (hate-speech detection).
For the AMI task, we used the following template:
*instruction: Nel testo seguente si esprime odio contro le donne? Rispondi sì o no., input: \<text\>, output: \<sì/no\>.*
Similarly, for HASPEEDE we used:
*instruction: “Il testo seguente incita all’odio? Rispondi sì o no., input: \<text\>, output: \<sì/no\>.*
To fill these templates, we mapped the label "1" with the word "sì" and the label "0" with the word "no", \<text\> is just the sentence from the
dataset to classify. | 744 | [
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0.0026111602783203125,
0.05426025390625,
-0.06121826171875,
-0.05615234375,
-0.05865478515625,
0.0242919... |
snirjhar-colab/pcqm | 2023-10-05T16:03:34.000Z | [
"region:us"
] | snirjhar-colab | null | null | 0 | 0 | 2023-10-05T16:02:57 | 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/overlord | 2023-10-05T19:02:49.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T16:07:12 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Overlord
This is the image base of bangumi OVERLORD, we detected 65 characters, 4389 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 | 76 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 27 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 354 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 117 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 48 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 89 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 32 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 60 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 64 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 17 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 45 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 38 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 84 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 152 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 132 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 62 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 42 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 174 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 26 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 28 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 163 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 112 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 55 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 53 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 17 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 29 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 42 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 16 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 32 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 72 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 14 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 49 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 51 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 6 | [Download](33/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 34 | 70 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 11 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 113 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 12 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 8 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 11 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 167 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 13 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 64 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 53 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 6 | [Download](44/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 45 | 183 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 48 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 278 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 157 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 16 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 41 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 117 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 8 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
| 53 | 9 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 27 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 27 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 181 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 13 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 9 | [Download](58/dataset.zip) |  |  |  |  |  |  |  |  |
| 59 | 31 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 35 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 43 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 51 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 24 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 185 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 21,607 | [
[
-0.0447998046875,
-0.00994873046875,
0.00907135009765625,
0.0102691650390625,
-0.01611328125,
-0.00286865234375,
-0.0018892288208007812,
-0.0232391357421875,
0.0408935546875,
0.034149169921875,
-0.05450439453125,
-0.0531005859375,
-0.043914794921875,
0.03082... |
BangumiBase/haiyorenyarukosan | 2023-10-05T17:50:57.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T16:08:02 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Haiyore! Nyaruko-san
This is the image base of bangumi Haiyore! Nyaruko-san, we detected 31 characters, 3214 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 | 271 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 848 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 50 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 28 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 63 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 120 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 17 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 443 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 20 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 19 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 784 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 23 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 27 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 11 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 12 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 99 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 9 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 55 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 12 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 7 | [Download](19/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 20 | 34 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 23 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 13 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 15 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 8 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 10 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 7 | [Download](26/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 27 | 8 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 10 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 152 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 10,955 | [
[
-0.042724609375,
-0.00890350341796875,
0.0096588134765625,
0.01192474365234375,
-0.016204833984375,
-0.00555419921875,
-0.0018453598022460938,
-0.024017333984375,
0.040313720703125,
0.031341552734375,
-0.057373046875,
-0.0537109375,
-0.0421142578125,
0.03372... |
Hikari0608/UIEB | 2023-10-05T16:34:37.000Z | [
"region:us"
] | Hikari0608 | null | null | 0 | 0 | 2023-10-05T16:17:44 | ---
dataset_info:
features:
- name: raw
dtype: image
- name: gt
dtype: image
splits:
- name: train
num_bytes: 1351356308.0
num_examples: 800
- name: val
num_bytes: 136425185.0
num_examples: 90
download_size: 1487875235
dataset_size: 1487781493.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
---
# Dataset Card for "UIEB"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 570 | [
[
-0.05126953125,
-0.01454925537109375,
0.009918212890625,
0.020233154296875,
-0.00543975830078125,
0.0036792755126953125,
0.03173828125,
-0.01534271240234375,
0.05194091796875,
0.037506103515625,
-0.048614501953125,
-0.047637939453125,
-0.017120361328125,
-0.... |
Hikari0608/Eval | 2023-10-05T16:23:07.000Z | [
"region:us"
] | Hikari0608 | null | null | 0 | 0 | 2023-10-05T16:17:55 | ---
dataset_info:
features:
- name: raw
dtype: image
splits:
- name: UIEB
num_bytes: 31221694.0
num_examples: 60
download_size: 31218498
dataset_size: 31221694.0
configs:
- config_name: default
data_files:
- split: UIEB
path: data/UIEB-*
---
# Dataset Card for "Eval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | 432 | [
[
-0.035491943359375,
-0.041168212890625,
0.0209503173828125,
0.00881195068359375,
-0.0012102127075195312,
0.0233001708984375,
0.01180267333984375,
-0.005374908447265625,
0.048736572265625,
0.037933349609375,
-0.046600341796875,
-0.049346923828125,
-0.028457641601... |
BangumiBase/spiceandwolf | 2023-10-05T18:08:16.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T16:27:36 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Spice And Wolf
This is the image base of bangumi Spice and Wolf, we detected 21 characters, 2749 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 | 155 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 176 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 61 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 66 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 25 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 31 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 18 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 948 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 93 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 64 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 778 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 43 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 73 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 36 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 24 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 22 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 23 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 16 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 14 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 20 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 63 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 7,803 | [
[
-0.042388916015625,
-0.006725311279296875,
0.01035308837890625,
0.0170745849609375,
-0.01280975341796875,
-0.004184722900390625,
-0.00232696533203125,
-0.024322509765625,
0.03826904296875,
0.0321044921875,
-0.060546875,
-0.051971435546875,
-0.04052734375,
0.... |
BangumiBase/lastexile | 2023-10-05T17:49:29.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T16:28:02 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Last Exile
This is the image base of bangumi LAST EXILE, we detected 29 characters, 2019 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 | 74 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 95 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 73 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 36 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 158 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 46 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 74 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 75 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 39 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 53 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 65 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 312 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 47 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 162 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 53 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 43 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 206 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 20 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 73 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 39 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 10 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 104 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 10 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 38 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 8 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 10 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 9 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 16 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 71 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 10,307 | [
[
-0.04180908203125,
-0.00862884521484375,
0.0106353759765625,
0.01059722900390625,
-0.01806640625,
-0.00130462646484375,
-0.0018587112426757812,
-0.0239715576171875,
0.041229248046875,
0.03668212890625,
-0.056671142578125,
-0.0546875,
-0.04205322265625,
0.033... |
BangumiBase/shakugannoshana | 2023-10-05T21:01:17.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T16:28:52 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Shakugan No Shana
This is the image base of bangumi Shakugan no Shana, we detected 66 characters, 8549 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 | 744 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 928 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 91 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 41 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 39 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 170 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 1431 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 128 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 222 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 263 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 133 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 84 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 152 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 15 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 43 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 71 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 32 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 36 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 32 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 44 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 289 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 59 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 441 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 22 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 46 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 620 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 130 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 41 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 45 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 17 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 31 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 111 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 100 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 25 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 43 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 89 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 12 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 17 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 54 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 118 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 42 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 390 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 26 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 126 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 34 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 14 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 17 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 61 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 18 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 22 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 20 | [Download](50/dataset.zip) |  |  |  |  |  |  |  |  |
| 51 | 22 | [Download](51/dataset.zip) |  |  |  |  |  |  |  |  |
| 52 | 15 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
| 53 | 11 | [Download](53/dataset.zip) |  |  |  |  |  |  |  |  |
| 54 | 41 | [Download](54/dataset.zip) |  |  |  |  |  |  |  |  |
| 55 | 43 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 11 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 29 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 58 | [Download](58/dataset.zip) |  |  |  |  |  |  |  |  |
| 59 | 13 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 27 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 18 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 12 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 13 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| 64 | 13 | [Download](64/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 444 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
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sigel600/your-dataset-name | 2023-10-05T16:47:12.000Z | [
"region:us"
] | sigel600 | null | null | 0 | 0 | 2023-10-05T16:47:12 | Entry not found | 15 | [
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nlpkevinl/wikipedia_openai_embeddings | 2023-10-06T17:40:07.000Z | [
"region:us"
] | nlpkevinl | null | null | 0 | 0 | 2023-10-05T17:27:50 | The embeddings for `text-embedding-ada-002` are stored in this repo.
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AnikaBasu/TempDatasetViewer | 2023-10-05T17:31:05.000Z | [
"region:us"
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lofcz/l2cs2 | 2023-10-05T17:48:29.000Z | [
"region:us"
] | lofcz | null | null | 0 | 0 | 2023-10-05T17:48:29 | Entry not found | 15 | [
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BangumiBase/highschoolfleet | 2023-10-05T19:38:22.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | BangumiBase | null | null | 0 | 0 | 2023-10-05T18:00:58 | ---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of High School Fleet
This is the image base of bangumi High School Fleet, we detected 52 characters, 3269 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 | 10 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 95 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 44 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 16 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 49 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 77 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 32 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 26 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 63 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 22 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 439 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 32 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 118 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 14 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 38 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 44 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 31 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 58 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 234 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 32 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 53 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 80 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 67 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 312 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 64 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 37 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 83 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 12 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 47 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 27 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 58 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 196 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 17 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 31 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 55 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 38 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 24 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 43 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 51 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 44 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 12 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 10 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 35 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 8 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 24 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 7 | [Download](45/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 46 | 5 | [Download](46/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 47 | 18 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 22 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 13 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
| 50 | 7 | [Download](50/dataset.zip) |  |  |  |  |  |  |  | N/A |
| noise | 295 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
| 17,543 | [
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