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42
⌀ | last_modified
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BangumiBase/greatpretender
|
BangumiBase
| 2023-11-27T00:43:49Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-26T21:59:38Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Great Pretender
This is the image base of bangumi Great Pretender, we detected 50 characters, 3820 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 | 178 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 20 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 647 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 471 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 86 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 79 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 80 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 100 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 110 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 116 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 48 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 35 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 58 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 23 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 30 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 61 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 33 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 59 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 132 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 9 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 44 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 25 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 42 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 25 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 25 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 83 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 14 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 265 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 16 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 24 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 16 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 22 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 38 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 37 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 7 | [Download](36/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 37 | 18 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 40 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 15 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 281 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 21 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 8 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 11 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 10 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 18 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 98 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 76 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 8 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 118 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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BangumiBase/magithelabyrinthofmagic
|
BangumiBase
| 2023-11-27T01:34:39Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-26T22:01:03Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Magi - The Labyrinth Of Magic
This is the image base of bangumi Magi - The Labyrinth of Magic, we detected 100 characters, 7708 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 | 1270 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 16 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 22 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 41 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 183 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 107 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 345 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 68 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 47 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 130 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 58 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 89 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 26 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 26 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 45 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 58 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 59 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 79 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 35 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 51 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 65 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 90 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 42 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 50 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 40 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 58 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 38 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 64 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 40 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 7 | [Download](30/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 31 | 34 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 44 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 33 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 65 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 79 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 16 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 26 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 15 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 23 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 30 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 162 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 413 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 27 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 24 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 15 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 52 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 25 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 21 | [Download](48/dataset.zip) |  |  |  |  |  |  |  |  |
| 49 | 75 | [Download](49/dataset.zip) |  |  |  |  |  |  |  |  |
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| 52 | 23 | [Download](52/dataset.zip) |  |  |  |  |  |  |  |  |
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| 55 | 24 | [Download](55/dataset.zip) |  |  |  |  |  |  |  |  |
| 56 | 13 | [Download](56/dataset.zip) |  |  |  |  |  |  |  |  |
| 57 | 36 | [Download](57/dataset.zip) |  |  |  |  |  |  |  |  |
| 58 | 7 | [Download](58/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 59 | 16 | [Download](59/dataset.zip) |  |  |  |  |  |  |  |  |
| 60 | 22 | [Download](60/dataset.zip) |  |  |  |  |  |  |  |  |
| 61 | 28 | [Download](61/dataset.zip) |  |  |  |  |  |  |  |  |
| 62 | 18 | [Download](62/dataset.zip) |  |  |  |  |  |  |  |  |
| 63 | 1272 | [Download](63/dataset.zip) |  |  |  |  |  |  |  |  |
| 64 | 88 | [Download](64/dataset.zip) |  |  |  |  |  |  |  |  |
| 65 | 159 | [Download](65/dataset.zip) |  |  |  |  |  |  |  |  |
| 66 | 15 | [Download](66/dataset.zip) |  |  |  |  |  |  |  |  |
| 67 | 35 | [Download](67/dataset.zip) |  |  |  |  |  |  |  |  |
| 68 | 85 | [Download](68/dataset.zip) |  |  |  |  |  |  |  |  |
| 69 | 21 | [Download](69/dataset.zip) |  |  |  |  |  |  |  |  |
| 70 | 22 | [Download](70/dataset.zip) |  |  |  |  |  |  |  |  |
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| 72 | 15 | [Download](72/dataset.zip) |  |  |  |  |  |  |  |  |
| 73 | 11 | [Download](73/dataset.zip) |  |  |  |  |  |  |  |  |
| 74 | 14 | [Download](74/dataset.zip) |  |  |  |  |  |  |  |  |
| 75 | 15 | [Download](75/dataset.zip) |  |  |  |  |  |  |  |  |
| 76 | 14 | [Download](76/dataset.zip) |  |  |  |  |  |  |  |  |
| 77 | 29 | [Download](77/dataset.zip) |  |  |  |  |  |  |  |  |
| 78 | 14 | [Download](78/dataset.zip) |  |  |  |  |  |  |  |  |
| 79 | 7 | [Download](79/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 80 | 11 | [Download](80/dataset.zip) |  |  |  |  |  |  |  |  |
| 81 | 11 | [Download](81/dataset.zip) |  |  |  |  |  |  |  |  |
| 82 | 16 | [Download](82/dataset.zip) |  |  |  |  |  |  |  |  |
| 83 | 28 | [Download](83/dataset.zip) |  |  |  |  |  |  |  |  |
| 84 | 11 | [Download](84/dataset.zip) |  |  |  |  |  |  |  |  |
| 85 | 11 | [Download](85/dataset.zip) |  |  |  |  |  |  |  |  |
| 86 | 9 | [Download](86/dataset.zip) |  |  |  |  |  |  |  |  |
| 87 | 12 | [Download](87/dataset.zip) |  |  |  |  |  |  |  |  |
| 88 | 89 | [Download](88/dataset.zip) |  |  |  |  |  |  |  |  |
| 89 | 52 | [Download](89/dataset.zip) |  |  |  |  |  |  |  |  |
| 90 | 8 | [Download](90/dataset.zip) |  |  |  |  |  |  |  |  |
| 91 | 21 | [Download](91/dataset.zip) |  |  |  |  |  |  |  |  |
| 92 | 14 | [Download](92/dataset.zip) |  |  |  |  |  |  |  |  |
| 93 | 15 | [Download](93/dataset.zip) |  |  |  |  |  |  |  |  |
| 94 | 10 | [Download](94/dataset.zip) |  |  |  |  |  |  |  |  |
| 95 | 8 | [Download](95/dataset.zip) |  |  |  |  |  |  |  |  |
| 96 | 11 | [Download](96/dataset.zip) |  |  |  |  |  |  |  |  |
| 97 | 60 | [Download](97/dataset.zip) |  |  |  |  |  |  |  |  |
| 98 | 6 | [Download](98/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 538 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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UMCU/MultiNLI_Dutch_translated_with_Marianmt
|
UMCU
| 2023-12-01T19:21:37Z | 0 | 0 |
[
"task_categories:sentence-similarity",
"size_categories:100K<n<1M",
"language:nl",
"license:creativeml-openrail-m",
"arxiv:1910.13461",
"doi:10.57967/hf/1417",
"region:us"
] |
[
"sentence-similarity"
] | 2023-11-26T22:24:32Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: annotator_labels
sequence: string
- name: genre
dtype: string
- name: gold_label
dtype: string
- name: pairID
dtype: string
splits:
- name: train
num_bytes: 92877120
num_examples: 380800
- name: validation
num_bytes: 5903876
num_examples: 19392
- name: test
num_bytes: 5321727
num_examples: 19040
download_size: 58511174
dataset_size: 104102723
license: creativeml-openrail-m
task_categories:
- sentence-similarity
language:
- nl
pretty_name: Dutch MultiNLI(MM) using MariaNMT
size_categories:
- 100K<n<1M
---
```
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: annotator_labels
sequence: string
- name: genre
dtype: string
- name: gold_label
dtype: string
- name: pairID
dtype: string
splits:
- name: train
num_bytes: 92877120
num_examples: 380800
- name: validation
num_bytes: 5903876
num_examples: 19392
- name: test
num_bytes: 5321727
num_examples: 19040
download_size: 58511174
dataset_size: 104102723
---
```
# Dataset Card for "MultiNLI_Dutch_translated_with_Marianmt"
Translation of the **English** corpus [Multi-Genre Natural Language Inference (MultiNLI) corpus ](https://cims.nyu.edu/~sbowman/multinli/),
specifically the *mismatched version*, to **Dutch** using an [Maria NMT model](https://marian-nmt.github.io/),
trained by [Helsinki NLP](https://huggingface.co/Helsinki-NLP/opus-mt-en-nl).
Note, for reference: Maria NMT is based on [BART](https://huggingface.co/docs/transformers/model_doc/bart), described [here](https://arxiv.org/abs/1910.13461).
A complete description of the dataset is given [here](https://cims.nyu.edu/~sbowman/multinli/),
and is available on [HuggingFace](https://huggingface.co/datasets/multi_nli_mismatch).
# Attribution
If you use this dataset please use the following to credit the creators of MultiNLI:
```citation
@InProceedings{N18-1101,
author = "Williams, Adina
and Nangia, Nikita
and Bowman, Samuel",
title = "A Broad-Coverage Challenge Corpus for
Sentence Understanding through Inference",
booktitle = "Proceedings of the 2018 Conference of
the North American Chapter of the
Association for Computational Linguistics:
Human Language Technologies, Volume 1 (Long
Papers)",
year = "2018",
publisher = "Association for Computational Linguistics",
pages = "1112--1122",
location = "New Orleans, Louisiana",
url = "http://aclweb.org/anthology/N18-1101"
}
```
The creators of the OPUS-MT models:
```
@InProceedings{TiedemannThottingal:EAMT2020,
author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
year = {2020},
address = {Lisbon, Portugal}
}
```
and
```
@misc {van_es_2023,
author = { {Bram van Es} },
title = { MultiNLI_Dutch_translated_with_Marianmt (Revision 284d39a) },
year = 2023,
url = { https://huggingface.co/datasets/UMCU/MultiNLI_Dutch_translated_with_Marianmt },
doi = { 10.57967/hf/1417 },
publisher = { Hugging Face }
}
```
# License
For both the Maria NMT model and the original [Helsinki NLP](https://twitter.com/HelsinkiNLP) [Opus MT model](https://huggingface.co/Helsinki-NLP)
we did **not** find a license, if this was in error please let us know and we will add the appropriate licensing promptly.
We adopt the licensing of the MultiNLI corpus, which is stated as follows in the accompanying publication:
*The majority of the
corpus is released under the OANC’s license,
which allows all content to be freely used, modified, and shared under permissive terms. The data
in the FICTION section falls under several permissive licenses; Seven Swords is available under
a Creative Commons Share-Alike 3.0 Unported
License, and with the explicit permission of the
author, Living History and Password Incorrect are
available under Creative Commons Attribution
3.0 Unported Licenses; the remaining works of
fiction are in the public domain in the United
States (but may be licensed differently elsewhere).*
|
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BangumiBase/vivyfluoriteeyessong
|
BangumiBase
| 2023-11-27T00:32:35Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-26T22:30:04Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Vivy - Fluorite Eye's Song
This is the image base of bangumi Vivy - Fluorite Eye's Song, we detected 41 characters, 2718 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 | 16 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 109 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 16 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 987 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 34 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 42 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 32 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 35 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 41 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 30 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 20 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 57 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 43 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 19 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 36 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 99 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 29 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 21 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 48 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 62 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 41 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 53 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 28 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 32 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 29 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 81 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 91 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 48 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 24 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 24 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 12 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 22 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 7 | [Download](32/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 33 | 10 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 27 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 40 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 33 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 33 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 8 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 5 | [Download](39/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 294 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
DZN222/joaomodelo
|
DZN222
| 2023-11-26T22:40:02Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-26T22:37:09Z |
---
license: openrail
---
|
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-0.016066566109657288,
0.26214760541915894,
0.04487833380699158,
-0.6869441866874695
] |
breno30/wanda
|
breno30
| 2023-11-26T22:41:03Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-26T22:40:43Z |
---
license: openrail
---
|
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] |
Gabriel1322/MC-POZE-MODEL
|
Gabriel1322
| 2023-11-26T23:00:11Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-26T22:57:58Z |
---
license: openrail
---
|
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Emerson0007/Sullivanmp3
|
Emerson0007
| 2023-11-26T23:42:20Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-26T23:36:06Z |
---
license: openrail
---
|
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vocalgiela/vocalgiela
|
vocalgiela
| 2023-11-26T23:41:42Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-26T23:40:38Z |
---
license: openrail
---
|
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seanbethard/service-manuals
|
seanbethard
| 2023-11-27T19:07:57Z | 0 | 0 |
[
"license:mit",
"motorcycles",
"service manuals",
"repair",
"docvqa",
"region:us"
] | null | 2023-11-27T00:07:32Z |
---
license: mit
viewer: false
tags:
- motorcycles
- service manuals
- repair
- docvqa
---
Harley Davidson service manuals 1903-2015. Proto-vectors.
|
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] |
breno30/PauloCarvalho
|
breno30
| 2023-11-27T00:33:57Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T00:33:43Z |
---
license: openrail
---
|
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] |
Rycharllyson/CallYou
|
Rycharllyson
| 2023-11-27T00:47:45Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T00:47:21Z |
---
license: openrail
---
|
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] |
jeffvalasq/colmanetti
|
jeffvalasq
| 2023-11-27T00:55:43Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T00:54:42Z |
---
license: openrail
---
|
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] |
masiouih/saiviado
|
masiouih
| 2023-11-27T00:58:08Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T00:58:08Z |
---
license: openrail
---
|
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] |
Lionelpang/forme
|
Lionelpang
| 2023-11-27T01:00:15Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T01:00:15Z |
---
license: apache-2.0
---
|
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multi-train/emb-hotpotqa-train
|
multi-train
| 2023-11-27T01:04:35Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T01:04:23Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 76992682
num_examples: 68659
download_size: 50772036
dataset_size: 76992682
---
# Dataset Card for "emb-hotpotqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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kyomoyo/mini-platypus
|
kyomoyo
| 2023-11-27T01:32:28Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T01:32:27Z |
---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 4186564
num_examples: 1000
download_size: 2245924
dataset_size: 4186564
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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multi-train/emb-pubmed
|
multi-train
| 2023-11-27T01:43:39Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T01:43:16Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 321131040
num_examples: 212269
download_size: 181748325
dataset_size: 321131040
---
# Dataset Card for "emb-pubmed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-medmcqa-train
|
multi-train
| 2023-11-27T01:52:13Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T01:52:02Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 102292372
num_examples: 160869
download_size: 63892842
dataset_size: 102292372
---
# Dataset Card for "emb-medmcqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-record_train
|
multi-train
| 2023-11-27T01:56:21Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T01:56:12Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 78813006
num_examples: 65709
download_size: 48370504
dataset_size: 78813006
---
# Dataset Card for "emb-record_train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
multi-train/emb-scitldr
|
multi-train
| 2023-11-27T02:12:10Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:12:03Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 59114455
num_examples: 1992
download_size: 29584964
dataset_size: 59114455
---
# Dataset Card for "emb-scitldr"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-trex-train
|
multi-train
| 2023-11-27T02:26:18Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:24:30Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 2175572925
num_examples: 2284168
download_size: 1321673983
dataset_size: 2175572925
---
# Dataset Card for "emb-trex-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-triviaqa-train
|
multi-train
| 2023-11-27T02:28:57Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:28:49Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 59025209
num_examples: 52886
download_size: 39225639
dataset_size: 59025209
---
# Dataset Card for "emb-triviaqa-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-wow-train
|
multi-train
| 2023-11-27T02:31:14Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:31:04Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 112157723
num_examples: 80035
download_size: 65616642
dataset_size: 112157723
---
# Dataset Card for "emb-wow-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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multi-train/emb-zeroshot-train
|
multi-train
| 2023-11-27T02:31:55Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:31:46Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: neg
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 131176509
num_examples: 132063
download_size: 75790546
dataset_size: 131176509
---
# Dataset Card for "emb-zeroshot-train"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
nostr-id/raw-sample-toxic-comments-nostr
|
nostr-id
| 2023-11-27T03:15:17Z | 0 | 1 |
[
"task_categories:text-classification",
"language:en",
"license:cc-by-4.0",
"doi:10.57967/hf/1398",
"region:us"
] |
[
"text-classification"
] | 2023-11-27T02:32:11Z |
---
license: cc-by-4.0
task_categories:
- text-classification
language:
- en
pretty_name: Raw Sample Toxic Comments from Nostr
---
# Introduction
This data were raw sample toxic comments from Nostr classified using [atrifat/hate-speech-detector-api](https://github.com/atrifat/hate-speech-detector-api) and part of [atrifat/nostr-filter-relay](https://github.com/atrifat/nostr-filter-relay) project. This data were solely dedicated for research and initial discussion for detecting toxic comments in Nostr protocol.
# Data Collection
The data were collected between Saturday, November 18, 2023 1:17:18 AM UTC until Monday, November 27, 2023 2:24:25 AM UTC from wss://nostr-id-relay.hf.space relay. wss://nostr-id-relay.hf.space relay aggregates data from top major relays. All data can be collected directly using aggregator relay such as wss://relay.nostr.band or cache relay from Primal.net. The data included in this repository are data which has toxicity probability score greater than or equal to **0.75**.
# Data Structure
The data consist of json separated by lines (jsonl) to separate between each record. Each record has JSON key as follows:
- id: represents Nostr Event ID
- author: represents Nostr author public key
- content: represents original content of author comments
- finalText: represents comments after preprocessing by [atrifat/nostr-filter-relay](https://github.com/atrifat/nostr-filter-relay). finalText were used for classifying toxic comments.
- data: represents toxic classification label, results of automated classification using [atrifat/hate-speech-detector-api](https://github.com/atrifat/hate-speech-detector-api)
# Author
Rif'at Ahdi Ramadhani
# License
[cc-by-4.0](https://creativecommons.org/licenses/by/4.0/)
|
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DataStudio/OCR_UppercaseARIA
|
DataStudio
| 2023-11-27T03:53:04Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T02:49:28Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 499062262.625
num_examples: 12323
download_size: 498987119
dataset_size: 499062262.625
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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malaysia-ai/mosaic-instructions
|
malaysia-ai
| 2023-11-28T08:19:27Z | 0 | 0 |
[
"language:ms",
"region:us"
] | null | 2023-11-27T03:05:24Z |
---
language:
- ms
---
# Mosaic format for instructions dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-instructions.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-instructions
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-instructions')
len(dataset)
```
|
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malaysia-ai/mosaic-extra
|
malaysia-ai
| 2023-11-28T08:13:23Z | 0 | 0 |
[
"language:ms",
"region:us"
] | null | 2023-11-27T03:08:53Z |
---
language:
- ms
---
# Mosaic format for extra dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-extra.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-extra
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-extra')
len(dataset)
```
|
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malaysia-ai/mosaic-madlad-400-ms
|
malaysia-ai
| 2023-11-28T08:17:38Z | 0 | 0 |
[
"language:ms",
"region:us"
] | null | 2023-11-27T03:14:00Z |
---
language:
- ms
---
# Mosaic format for extra dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-madlad-400-ms.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-madlad-400-ms
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-madlad-400-ms')
len(dataset)
```
|
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malaysia-ai/mosaic-dedup-text-dataset
|
malaysia-ai
| 2023-12-01T02:16:36Z | 0 | 0 |
[
"language:ms",
"region:us"
] | null | 2023-11-27T03:14:16Z |
---
language:
- ms
---
# Mosaic format for dedup text dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-dedup-text-dataset-4096.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-dedup-text-dataset
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-dedup-text-dataset')
len(dataset)
```
|
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multi-train/emb-reddit-title-body
|
multi-train
| 2023-11-27T06:18:03Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T03:33:05Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: query
dtype: string
- name: pos
dtype: string
- name: idx
dtype: int64
- name: task_name
dtype: string
splits:
- name: train
num_bytes: 95637449375
num_examples: 127445911
download_size: 3302152777
dataset_size: 95637449375
---
# Dataset Card for "emb-reddit-title-body"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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malaysia-ai/mosaic-starcoder-filtered
|
malaysia-ai
| 2023-11-28T08:14:20Z | 0 | 0 |
[
"language:ms",
"region:us"
] | null | 2023-11-27T03:47:08Z |
---
language:
- ms
---
# Mosaic format for filtered starcoder dataset to train Malaysian LLM
This repository is to store dataset shards using mosaic format.
1. prepared at https://github.com/malaysia-ai/dedup-text-dataset/blob/main/pretrain-llm/combine-starcoder.ipynb
2. using tokenizer https://huggingface.co/malaysia-ai/bpe-tokenizer
3. 4096 context length.
## how-to
1. git clone,
```bash
git lfs clone https://huggingface.co/datasets/malaysia-ai/mosaic-starcoder-filtered
```
2. load it,
```python
from streaming import LocalDataset
import numpy as np
from streaming.base.format.mds.encodings import Encoding, _encodings
class UInt16(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.uint16)
_encodings['uint16'] = UInt16
dataset = LocalDataset('mosaic-starcoder-filtered')
len(dataset)
```
|
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] |
ciscak/homesecurityzones
|
ciscak
| 2023-11-27T07:27:51Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T04:29:43Z |
---
license: mit
---
|
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seongwoon/labor_market_context_data
|
seongwoon
| 2023-11-27T04:52:19Z | 0 | 0 |
[
"license:cc-by-nc-nd-4.0",
"region:us"
] | null | 2023-11-27T04:50:43Z |
---
license: cc-by-nc-nd-4.0
---
|
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cp229/pubmed-summarization
|
cp229
| 2023-11-27T05:01:47Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T05:01:46Z |
---
license: mit
---
|
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] |
allenai/archive-dolma-v1
|
allenai
| 2023-11-27T05:31:20Z | 0 | 0 |
[
"task_categories:text-generation",
"size_categories:n>1T",
"language:en",
"license:other",
"language-modeling",
"casual-lm",
"llm",
"region:us"
] |
[
"text-generation"
] | 2023-11-27T05:25:00Z |
---
license: other
license_name: impact-license-medium-risk
license_link: https://allenai.org/licenses/impact-mr
viewer: false
task_categories:
- text-generation
language:
- en
tags:
- language-modeling
- casual-lm
- llm
pretty_name: Dolma
size_categories:
- n>1T
extra_gated_prompt: "Access to this dataset is automatically granted upon accepting the [**AI2 ImpACT License - Medium Risk Artifacts (“MR Agreement”)**](https://allenai.org/licenses/impact-mr) and completing all fields below."
extra_gated_fields:
Your full name: text
Organization or entity you are affiliated with: text
State or country you are located in: text
Contact email: text
Please describe your intended use of the medium risk artifact(s): text
I AGREE to the terms and conditions of the MR Agreement above: checkbox
I AGREE to AI2’s use of my information for legal notices and administrative matters: checkbox
I CERTIFY that the information I have provided is true and accurate: checkbox
---
# Dolma
<img alt="Dolma's official logo. It's dolma written in yellow, round lowercase letters over a blue background." src="https://raw.githubusercontent.com/allenai/dolma/main/docs/assets/AI2_Blog_1400x685_2x.webp" width="100%">
Dolma is a dataset of 3 trillion tokens from a diverse mix of web content, academic publications, code, books, and encyclopedic materials. It is openly released under AI2’s ImpACT license as a medium risk artifact.
More information:
- Read Dolma **announcement blogpost** [on Medium](https://soldni.medium.com/dolma-3-trillion-tokens-open-llm-corpus-9a0ff4b8da64);
- Learn more about Dolma on its [**Data Sheet**](https://drive.google.com/file/d/12gOf5I5RytsD159nSP7iim_5zN31FCXq/view?usp=drive_link);
- Review Dolma's [**ImpACT license** for medium risk artifacts](https://allenai.org/licenses/impact-mr);
- Explore the [**open source tools**](https://github.com/allenai/dolma) we created to curate Dolma.
- Want to request removal of personal data? Use [this form](https://forms.gle/q4BNUUxUxKwKkfdT6) to notify us of documents containing PII about a specific user.
To learn more about the toolkit used to create Dolma, including how to replicate this dataset, head over our [GitHub project page](https://github.com/allenai/dolma/tree/main/docs)!
## Summary Statistics
|**Source**|**Type**|**Gzip files (GB)**|**Documents (millions)**|**[GPT-NeoX](https://huggingface.co/EleutherAI/gpt-neox-20b) Tokens (billions)**|
|:---|:---:|:---:|:---:|:----:|
|[CommonCrawl](https://commoncrawl.org/)|web|4,197|4,600|2,415|
|[C4](https://huggingface.co/datasets/allenai/c4)|web|302|364|175|
|[peS2o](https://huggingface.co/datasets/allenai/peS2o)|academic|150|38.8|57|
|[The Stack](https://huggingface.co/datasets/bigcode/the-stack)|code|319|236|430|
|[Project Gutenberg](https://www.gutenberg.org/)|books|6.6|0.052|4.8|
|[Wikipedia](https://dumps.wikimedia.org/)|encyclopedic|5.8|6.1|3.6|
||**Total** |**4980.4**|**5,245**|**3,084**|
## Download
The fastest way to download Dolma is to directly download the individual files across multiple threads.
This can be achieved using wget or [aria2](https://github.com/aria2/aria2) Linux/Mac/Windows package (`sudo apt-get install aria2` on Ubuntu).
For downloading individual files, simply use `wget` as follows:
`wget --header 'Authorization: Bearer YOUR_HF_HUB_ACCESS_TOKEN' https://huggingface.co/datasets/allenai/dolma/resolve/main/data/peS2o/s2_v3-0000.json.gz`
For downloading many files across multiple threads, first prepare a `.txt` file with the urls you would like such as via the script below:
```python
OUT_DIRECTORY = "/scratch/dolma/data"
# URLs for cc_en_head
cc_en_head_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_head/cc_en_head-"
cc_en_head_url_list = [f"{cc_en_head_base_url}{str(i).zfill(4)}.json.gz\n dir={OUT_DIRECTORY}/cc_en_head\n out=cc_en_head-{str(i).zfill(4)}.json.gz" for i in range(612)]
# URLs for cc_en_middle
cc_en_middle_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_middle/cc_en_middle-"
cc_en_middle_url_list = [f"{cc_en_middle_base_url}{str(i).zfill(4)}.json.gz\n dir={OUT_DIRECTORY}/cc_en_middle\n out=cc_en_middle-{str(i).zfill(4)}.json.gz" for i in range(777)]
# URLs for cc_en_tail
cc_en_tail_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_tail/cc_en_tail-"
cc_en_tail_url_list = [f"{cc_en_tail_base_url}{str(i).zfill(4)}.json.gz\n dir={OUT_DIRECTORY}/cc_en_tail\n out=cc_en_tail-{str(i).zfill(4)}.json.gz" for i in range(1493)]
# URLs for s2_v3
s2_v3_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/peS2o/s2_v3-"
s2_v3_url_list = [f"{s2_v3_base_url}{str(i).zfill(4)}.json.gz\n dir={OUT_DIRECTORY}/peS2o\n out=s2_v3-{str(i).zfill(4)}.json.gz" for i in range(42)]
# URLs for The Stack
LANG_TO_FILES = {'lasso': 1, 'nsis': 1, 'literate-agda': 1, 'metal': 1, 'xojo': 1, 'max': 8, 'jupyter-notebook': 101, 'asp': 7, 'elixir': 14, 'html+erb': 19, 'julia': 22, 'dart': 63, 'ragel-in-ruby-host': 1, 'api-blueprint': 1, 'gams': 1, 'tex': 71, 'xml': 101, 'smalltalk': 17, 'cmake': 11, 'piglatin': 1, "cap'n-proto": 1, 'common-lisp': 21, 'stylus': 3, 'typescript': 101, 'jflex': 1, 'factor': 1, 'arc': 1, 'parrot-internal-representation': 1, 'aspectj': 1, 'go': 101, 'urweb': 1, 'dns-zone': 1, 'purebasic': 1, 'toml': 15, 'erlang': 11, 'hy': 1, 'component-pascal': 2, 'oz': 1, 'opa': 1, 'handlebars': 10, 'gas': 15, 'less': 17, 'gnuplot': 15, 'harbour': 1, 'vhdl': 16, 'octave': 1, 'powershell': 21, 'clips': 1, 'fish': 1, 'prolog': 1, 'sparql': 1, 'objective-j': 1, 'scaml': 1, 'twig': 20, 'gettext-catalog': 101, 'purescript': 2, 'vala': 1, 'gosu': 1, 'apacheconf': 1, 'xc': 1, 'lean': 3, 'mako': 1, 'r': 4, 'unrealscript': 1, 'solidity': 21, 'pike': 1, 'cartocss': 1, 'maple': 1, 'graphql': 3, 'unity3d-asset': 101, 'swift': 101, 'dockerfile': 13, 'digital-command-language': 1, 'scala': 83, 'sqf': 2, 'logtalk': 1, 'coq': 1, 'shellsession': 1, 'befunge': 1, 'nu': 1, 'ecere-projects': 1, 'zimpl': 1, 'shen': 1, 'golo': 1, 'web-ontology-language': 12, 'sas': 2, 'uno': 1, 'livescript': 1, 'literate-haskell': 1, 'clojure': 8, 'perl6': 1, 'zig': 3, 'liquid': 2, 'ec': 1, 'blitzbasic': 1, 'sql': 101, 'http': 2, 'xproc': 1, 'kit': 1, 'textile': 1, 'netlinx': 1, 'propeller-spin': 1, 'cython': 5, 'realbasic': 1, 'dogescript': 1, 'llvm': 9, 'pawn': 1, 'groff': 40, 'html+django': 3, 'csound': 1, 'd': 1, 'agda': 2, 'css': 101, 'yacc': 7, 'robotframework': 1, 'kotlin': 101, 'grace': 1, 'abap': 2, 'blitzmax': 1, 'webassembly': 3, 'ampl': 1, 'postscript': 16, 'nit': 1, 'gentoo-eclass': 1, 'xpages': 1, 'linker-script': 2, 'yang': 3, 'jade': 4, 'standard-ml': 6, 'javascript': 101, 'moonscript': 1, 'mtml': 1, 'saltstack': 1, 'freemarker': 5, 'ston': 1, 'html+eex': 1, 'xs': 1, 'c++': 101, 'matlab': 1, 'm4': 2, 'xbase': 1, 'perl': 37, 'emacs-lisp': 7, 'bison': 1, 'slim': 2, 'grammatical-framework': 1, 'rdoc': 1, 'nix': 10, 'clean': 1, 'module-management-system': 1, 'nimrod': 6, 'raml': 1, 'forth': 1, 'squirrel': 1, 'alloy': 1, 'opencl': 3, 'c': 101, 'sass': 4, 'eiffel': 2, 'papyrus': 1, 'html': 109, 'java': 101, 'hcl': 14, 'isabelle': 2, 'markdown': 101, 'gentoo-ebuild': 2, 'objdump': 1, 'emberscript': 1, 'text': 101, 'bro': 1, 'opal': 1, 'haskell': 35, 'mupad': 1, 'desktop': 1, 'modelica': 2, 'coldfusion-cfc': 2, 'fantom': 1, 'glsl': 10, 'ocaml': 16, 'nesc': 2, 'scheme': 7, 'crystal': 5, 'tcsh': 1, 'c2hs-haskell': 1, 'idris': 1, 'logos': 4, 'coffeescript': 13, 'g-code': 10, 'sage': 1, 'haml': 4, 'tcl': 7, 'smt': 5, 'ox': 1, 'chuck': 1, 'xquery': 1, 'batchfile': 7, 'pod': 2, 'xtend': 1, 'restructuredtext': 61, 'rmarkdown': 1, 'turtle': 33, 'jsx': 45, 'protocol-buffer': 8, "ren'py": 2, 'diff': 32, 'slash': 1, 'darcs-patch': 1, 'numpy': 1, 'augeas': 1, 'wisp': 1, 'edn': 15, 'ooc': 1, 'bitbake': 2, 'labview': 1, 'inform-7': 1, 'rust': 101, 'creole': 1, 'apl': 1, 'arduino': 11, 'openscad': 2, 'cuda': 9, 'thrift': 1, 'yaml': 101, 'fancy': 1, 'coldfusion': 1, 'python': 101, 'clarion': 1, 'glyph': 1, 'parrot': 1, 'lookml': 1, 'java-server-pages': 19, 'oxygene': 1, 'flux': 1, 'scilab': 1, 'groovy-server-pages': 2, 'rhtml': 1, 'eagle': 52, 'parrot-assembly': 1, 'igor-pro': 1, 'webidl': 1, 'bluespec': 1, 'unified-parallel-c': 1, 'smali': 38, 'haxe': 9, 'ada': 7, 'lua': 48, 'pascal': 21, 'html+php': 6, 'irc-log': 1, 'x10': 1, 'netlogo': 1, 'ioke': 1, 'dm': 1, 'self': 1, 'elm': 5, 'ats': 1, 'brainfuck': 1, 'mask': 1, 'rouge': 1, 'turing': 1, 'lex': 2, 'gap': 1, 'pogoscript': 1, 'kicad': 30, 'io': 1, 'objective-c++': 8, 'qml': 4, 'redcode': 1, 'autoit': 2, 'processing': 4, 'systemverilog': 6, 'gdscript': 5, 'f-sharp': 12, 'fortran': 23, 'monkey': 1, 'c-sharp': 101, 'xslt': 9, 'viml': 6, 'renderscript': 1, 'scss': 84, 'cucumber': 4, 'verilog': 1, 'genshi': 1, 'racket': 1, 'krl': 1, 'actionscript': 10, 'pan': 1, 'cirru': 1, 'chapel': 1, 'pure-data': 2, 'm': 1, 'applescript': 1, 'inno-setup': 1, 'volt': 1, 'myghty': 1, 'groovy': 17, 'ags-script': 1, 'mirah': 1, 'lsl': 1, 'brightscript': 1, 'python-traceback': 1, 'sourcepawn': 2, 'maxscript': 1, 'zephir': 1, 'supercollider': 1, 'mathematica': 20, 'awk': 1, 'autohotkey': 2, 'lfe': 1, 'ruby': 101, 'visual-basic': 20, 'ini': 59, 'red': 1, 'omgrofl': 1, 'idl': 1, 'rebol': 1, 'vue': 101, 'ninja': 2, 'ecl': 1, 'lolcode': 1, 'tea': 1, 'txl': 1, 'smarty': 9, 'vcl': 1, 'php': 101, 'literate-coffeescript': 1, 'click': 1, 'pony': 1, 'mediawiki': 5, 'stata': 5, 'stan': 1, 'nginx': 1, 'asciidoc': 16, 'antlr': 1, 'cobol': 1, 'org': 5, 'latte': 1, 'makefile': 32, 'ceylon': 1, 'graphviz-(dot)': 13, 'lilypond': 1, 'dylan': 1, 'qmake': 1, 'muf': 1, 'j': 1, 'pov-ray-sdl': 1, 'jasmin': 1, 'shell': 73, 'cycript': 1, 'boo': 1, 'hlsl': 2}
stack_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/stack-code/"
stack_url_list = []
for lang, num_files in sorted(LANG_TO_FILES.items()):
for i in range(num_files):
stack_url_list.append(f"{stack_base_url}{lang}/v3-{str(i).zfill(4)}.json.gz\n dir={OUT_DIRECTORY}/stack-code/{lang}\n out=v3-{str(i).zfill(4)}.json.gz")
# Combine all URL lists
all_url_list = cc_en_head_url_list + cc_en_middle_url_list + cc_en_tail_url_list + s2_v3_url_list + stack_url_list
out = open("files.txt", "a")
# Print the combined list of URLs
for i, url in enumerate(all_url_list):
out.write(url + "\n")
```
Then you can download them all in parallel using:
`aria2c --input-file files.txt --header 'Authorization: Bearer YOUR_HF_HUB_ACCESS_TOKEN'`
You can also add `-s` to increase the number of connections, e.g. `-s 10` (defaults to 5).
To get the exact file counts that are used for The Stack in the above script (`LANG_TO_FILES`), you can follow the below:
Fetch all files (does not download them, so should be fast): `GIT_LFS_SKIP_SMUDGE=1 git clone [email protected]:datasets/allenai/dolma.git`
Then run:
```python
import os
directory = "dolma/data/stack-code"
folder_dict = {}
for folder in os.listdir(directory):
folder_path = os.path.join(directory, folder)
if os.path.isdir(folder_path):
file_count = len([f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))])
folder_dict[folder] = file_count
print(folder_dict)
```
|
[
-0.516789972782135,
-0.5468111038208008,
0.2582789957523346,
0.07169342786073685,
-0.03642852231860161,
0.4475584924221039,
-0.1702001392841339,
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0.559597373008728,
0.20610079169273376,
-0.5839250087738037,
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0.2304074764251709,
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1.0627529621124268,
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0.11223693192005157,
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0.0983247384428978,
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0.08965275436639786,
0.457522988319397,
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0.9371747374534607,
0.8059122562408447,
0.7501006722450256,
0.3170682489871979,
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0.0857924073934555,
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0.7292592525482178,
0.5164608359336853,
0.12737201154232025,
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0.04399727284908295,
1.001008152961731,
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0.0769747719168663,
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-0.5079600811004639,
-0.03938928619027138,
0.10804478824138641,
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-0.8772266507148743,
0.33985722064971924,
0.2169169932603836,
1.425264596939087,
0.2648022174835205,
-0.05816848948597908,
-0.31305286288261414,
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seongwoon/industry-occupation
|
seongwoon
| 2023-11-27T05:26:37Z | 0 | 0 |
[
"license:cc-by-nc-nd-4.0",
"region:us"
] | null | 2023-11-27T05:26:02Z |
---
license: cc-by-nc-nd-4.0
---
|
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zicsx/hindi-bookcorpus2
|
zicsx
| 2023-11-27T09:30:49Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T05:38:13Z |
---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 10234923744
num_examples: 13542
download_size: 0
dataset_size: 10234923744
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "hindi-bookcorpus2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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BangumiBase/konoototomare
|
BangumiBase
| 2023-11-27T08:10:57Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T06:04:00Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Kono Oto Tomare!
This is the image base of bangumi Kono Oto Tomare!, we detected 34 characters, 3706 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 | 489 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 61 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 270 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 572 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 146 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 134 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 154 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 45 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 56 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 42 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 26 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 166 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 75 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 43 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 12 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 18 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 50 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 78 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 188 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 24 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 13 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 162 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 29 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 565 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 33 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 11 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 10 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 9 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 14 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 17 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 9 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 40 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 9 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 136 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
Zainab984/BP-balanced
|
Zainab984
| 2023-11-28T12:06:46Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T06:05:50Z |
---
dataset_info:
features:
- name: Target
dtype: int64
- name: PC
dtype: string
- name: GSHARE
dtype: string
- name: GA table
dtype: string
splits:
- name: train
num_bytes: 41082000
num_examples: 82164
- name: test
num_bytes: 10271000
num_examples: 20542
download_size: 2354826
dataset_size: 51353000
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
---
|
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] |
Otherwa/GenAi-Public-Response
|
Otherwa
| 2023-11-27T06:49:51Z | 0 | 0 |
[
"size_categories:n<1K",
"language:en",
"license:openrail",
"code",
"legal",
"finance",
"biology",
"chemistry",
"music",
"art",
"medical",
"climate",
"region:us"
] | null | 2023-11-27T06:45:14Z |
---
license: openrail
language:
- en
tags:
- code
- legal
- finance
- biology
- chemistry
- music
- art
- medical
- climate
size_categories:
- n<1K
---
|
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HuskyAI/2d_game_scence
|
HuskyAI
| 2023-11-27T07:14:03Z | 0 | 1 |
[
"task_categories:text-to-image",
"license:apache-2.0",
"2d game scence",
"style",
"lora",
"region:us"
] |
[
"text-to-image"
] | 2023-11-27T07:04:14Z |
---
license: apache-2.0
task_categories:
- text-to-image
tags:
- 2d game scence
- style
- lora
---
|
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yunzliang/SuiDetectData
|
yunzliang
| 2023-11-27T09:52:17Z | 0 | 0 |
[
"task_categories:text-classification",
"size_categories:n<1K",
"language:en",
"linguistics",
"psychology",
"region:us"
] |
[
"text-classification"
] | 2023-11-27T07:27:17Z |
---
task_categories:
- text-classification
size_categories:
- n<1K
language:
- en
tags:
- linguistics
- psychology
---
# Dataset Card for SuiDetectData
## Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
This dataset consists of annotations from 500 users by four experienced psychiatrists following the Columbia Suicide Severity Rating Scale (C-SSRS) guidelines. Each expert worked on the same set of posts, after which the consistency of their annotations was evaluated using the Krippendorff’s α metric, a measure for assessing inter-annotator agreement. The expert's annotation scheme was based on the C-SSRS questionnaire, which contains a series of survey questions that help gauge the urgency and severity of suicidal risks. These four experts rated each Reddit post into five distinct categories: supportive, suicide indicator, suicidal ideation, suicidal behavior, and suicide attempt. Each of these categories contains 108, 171, 77, 45, and 99 posts respectively (N=500).
## Five Categories in the Reddit C-SSRS Suicide Corpus
**Here are the five variables of interests in the outcome category:**
1. **Supportive** (22%): This category represents users who engage in discussions without any language suggesting past or current at-risk suicidal behavior or feelings.
2. **Suicide Indicator** (20%): This category encompasses users who mention known C-SSRS risk factors, primarily to empathize with others expressing suicidal thoughts or actions.
3. **Suicidal Ideation** (34%): This category describes users having thoughts of suicide, which may be linked to specific risk factors such as job loss, ending significant relationships, chronic diseases, mental disorders, or substance abuse.
4. **Suicidal Behavior** (15%): This category highlights users showcasing behaviors with a heightened risk of self-harm, either currently or in the past, active suicide planning, or previous institutionalization for mental health reasons.
5. **Suicide Attempt** (9%): This category is characterized by users who have undertaken deliberate actions, whether successful or not, with the intention of ending their own lives.
## Dataset Code Sources
<!-- Provide the basic links for the dataset. -->
- **Original Paper:** Gaur, M., Aribandi, V., Alambo, A., Kursuncu, U., Thirunarayan, K., Beich, J., Pathak, J., & Sheth, A. (2021). Characterization of time-variant and time-invariant assessment of suicidality on Reddit using C-SSRS. PloS one, 16(5), e0250448. https://doi.org/10.1371/journal.pone.0250448
- **Repository for Code demonstrations:** https://github.com/yunzhen1/Suicidality
## Risks and Privacy Information
The dataset contains data that are de-identified, but may include Reddit usernames without revealing other sensitive and personal information (e.g., data that reveals addresses, sexual orientations, religious beliefs, political opinions, financial or health data, etc.)
|
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Imran1/dogtrainset
|
Imran1
| 2023-11-27T07:37:04Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T07:36:58Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Afghan_hound
'1': French_bulldog
splits:
- name: train
num_bytes: 26798257.0
num_examples: 398
download_size: 26755684
dataset_size: 26798257.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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Imran1/dogtestset
|
Imran1
| 2023-11-27T07:37:26Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T07:37:24Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Afghan_hound
'1': French_bulldog
splits:
- name: train
num_bytes: 290465.0
num_examples: 6
download_size: 292088
dataset_size: 290465.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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akash140500/Predictive_M_1
|
akash140500
| 2023-11-27T07:58:49Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T07:51:29Z |
---
license: apache-2.0
---
|
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collabora/ai4bharat-shrutilipi
|
collabora
| 2023-11-27T12:15:25Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T08:16:39Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: 204030048047.146
num_examples: 408114
download_size: 200034353797
dataset_size: 204030048047.146
---
# Dataset Card for "ai4bharat-shrutilipi"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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opendal/huggingface-testdata
|
opendal
| 2023-11-27T09:12:40Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T08:17:46Z |
---
license: apache-2.0
---
|
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DataStudio/OCRFontsEnhance
|
DataStudio
| 2023-11-27T08:57:32Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T08:55:39Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: Qwinley
num_bytes: 106757090.0
num_examples: 5240
- name: Ariston
num_bytes: 123619963.125
num_examples: 5239
- name: Zap
num_bytes: 119724880.125
num_examples: 5239
- name: Campai
num_bytes: 123461953.0
num_examples: 5240
- name: Mandalay
num_bytes: 129332184.125
num_examples: 5239
- name: Brush
num_bytes: 121988610.0
num_examples: 5240
- name: AlexBrush
num_bytes: 109786433.0
num_examples: 5240
- name: Free
num_bytes: 104433511.0
num_examples: 5240
- name: Allegie
num_bytes: 100527446.0
num_examples: 5240
- name: Kun
num_bytes: 97646207.125
num_examples: 5239
- name: Script
num_bytes: 92350425.0
num_examples: 5240
- name: JackieO
num_bytes: 115897467.0
num_examples: 5240
- name: Rush
num_bytes: 105160861.0
num_examples: 5240
- name: Ambiance
num_bytes: 100961160.0
num_examples: 5240
- name: Saliere
num_bytes: 124157300.0
num_examples: 5240
- name: Chancery
num_bytes: 98686795.125
num_examples: 5239
- name: Tridico
num_bytes: 144127029.0
num_examples: 5240
- name: Commerce
num_bytes: 124982660.0
num_examples: 5240
- name: Times
num_bytes: 127224541.0
num_examples: 5240
- name: Freewrite
num_bytes: 101639441.125
num_examples: 5239
- name: Helve
num_bytes: 123461009.0
num_examples: 5240
- name: Sandy
num_bytes: 130526102.0
num_examples: 5240
- name: ShishoniBrush
num_bytes: 91591669.0
num_examples: 5240
- name: Casca
num_bytes: 95300918.125
num_examples: 5239
download_size: 2711725230
dataset_size: 2713345654.875
configs:
- config_name: default
data_files:
- split: Qwinley
path: data/Qwinley-*
- split: Ariston
path: data/Ariston-*
- split: Zap
path: data/Zap-*
- split: Campai
path: data/Campai-*
- split: Mandalay
path: data/Mandalay-*
- split: Brush
path: data/Brush-*
- split: AlexBrush
path: data/AlexBrush-*
- split: Free
path: data/Free-*
- split: Allegie
path: data/Allegie-*
- split: Kun
path: data/Kun-*
- split: Script
path: data/Script-*
- split: JackieO
path: data/JackieO-*
- split: Rush
path: data/Rush-*
- split: Ambiance
path: data/Ambiance-*
- split: Saliere
path: data/Saliere-*
- split: Chancery
path: data/Chancery-*
- split: Tridico
path: data/Tridico-*
- split: Commerce
path: data/Commerce-*
- split: Times
path: data/Times-*
- split: Freewrite
path: data/Freewrite-*
- split: Helve
path: data/Helve-*
- split: Sandy
path: data/Sandy-*
- split: ShishoniBrush
path: data/ShishoniBrush-*
- split: Casca
path: data/Casca-*
---
|
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] |
nbodagh/test2
|
nbodagh
| 2023-11-27T08:56:24Z | 0 | 0 |
[
"license:cc-by-4.0",
"region:us"
] | null | 2023-11-27T08:56:24Z |
---
license: cc-by-4.0
---
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] |
CHEN0312/gssgd
|
CHEN0312
| 2023-11-27T09:06:35Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T09:06:35Z |
---
license: apache-2.0
---
|
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Chars/symlink-models
|
Chars
| 2023-11-27T10:09:52Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T09:38:33Z |
---
license: mit
---
# 说明
使用第三方代码涉及到调用模型的时候，会不可避免的从huggingface下载模型
如果网络状况不良好的情况下会导致无法下载，而如果手动下载则需要一个个修改第三方代码使其读取本地模型的路径
故这里存储好对应的cache 目录，直接解压到 `~/.cache/huggingface/hub/` 路径下即可
|
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tr416/2k_test
|
tr416
| 2023-11-27T12:52:10Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T10:36:27Z |
---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 762433
num_examples: 623
download_size: 383726
dataset_size: 762433
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "2k_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
AIML-TUDA/TEdBench_plusplus
|
AIML-TUDA
| 2023-11-27T12:56:48Z | 0 | 0 |
[
"task_categories:image-to-image",
"size_categories:n<1K",
"license:apache-2.0",
"region:us"
] |
[
"image-to-image"
] | 2023-11-27T10:49:29Z |
---
license: apache-2.0
task_categories:
- image-to-image
pretty_name: TEdBenc++
size_categories:
- n<1K
---
# TEdBench++
This dataset contains the TEdBench++ an image-to-image benchmark for text-based generative models. It contains original images (originals) and edited images (LEdits++) for benchmarking. ``tedbench++.csv`` contains the text-based edit instructions for the respective original image and parameters to reproduce the edited images with LEdits++.
|
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] |
BangumiBase/landofthelustrous
|
BangumiBase
| 2023-11-27T11:51:35Z | 0 | 0 |
[
"size_categories:n<1K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T11:01:07Z |
---
license: mit
tags:
- art
size_categories:
- n<1K
---
# Bangumi Image Base of Land Of The Lustrous
This is the image base of bangumi Land of the Lustrous, we detected 19 characters, 845 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 | 202 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 121 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 94 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 11 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 20 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 38 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 12 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 17 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 12 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 49 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 18 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 36 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 35 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 44 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 11 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 14 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 24 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 8 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 79 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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BangumiBase/versaillesnobara
|
BangumiBase
| 2023-11-27T13:57:51Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T11:01:40Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Versailles No Bara
This is the image base of bangumi Versailles No Bara, we detected 35 characters, 4981 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 | 468 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 126 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 154 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 659 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 105 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 47 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 44 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 51 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 173 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 48 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 25 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 168 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 150 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 290 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 30 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 1251 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 125 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 34 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 66 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 76 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 150 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 147 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 13 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 62 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 65 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 119 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 109 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 14 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 13 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 28 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 17 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 12 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 19 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 10 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 113 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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BangumiBase/welcometothenhk
|
BangumiBase
| 2023-11-27T11:56:50Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T11:02:09Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Welcome To The N.h.k.
This is the image base of bangumi Welcome to the N.H.K., we detected 17 characters, 2205 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 | 1316 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 37 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 323 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 71 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 8 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 13 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 47 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 26 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 107 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 9 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 5 | [Download](10/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 11 | 74 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 16 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 8 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 22 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 45 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 78 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
BangumiBase/anohimitahananonamaewobokutachiwamadashiranai
|
BangumiBase
| 2023-11-27T12:12:17Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T11:02:38Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Ano Hi Mita Hana No Namae Wo Bokutachi Wa Mada Shiranai.
This is the image base of bangumi Ano Hi Mita Hana no Namae wo Bokutachi wa Mada Shiranai., we detected 19 characters, 1523 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 | 183 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 29 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 121 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 40 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 22 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 20 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 462 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 21 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 154 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 10 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 131 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 12 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 8 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 14 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 221 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 15 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 14 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 11 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 35 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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xixixi0503/formatted_util_deontology_commensense_justice_prompts_for_llama2
|
xixixi0503
| 2023-11-27T19:13:17Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T11:03:24Z |
---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 59417065
num_examples: 67603
download_size: 14719019
dataset_size: 59417065
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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maximedb/multilingual_librispeech_fr
|
maximedb
| 2023-11-27T12:33:03Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T11:23:22Z |
---
dataset_info:
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
- name: train
num_bytes: 62912882604.152
num_examples: 258213
- name: train.9h
num_bytes: 532581041.633
num_examples: 2167
- name: train.1h
num_bytes: 60218210.0
num_examples: 241
- name: validation
num_bytes: 620676040.84
num_examples: 2416
- name: test
num_bytes: 620016068.552
num_examples: 2426
download_size: 65546652537
dataset_size: 64746373965.177
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: train.9h
path: data/train.9h-*
- split: train.1h
path: data/train.1h-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
---
|
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AnnikaSimonsen/combined_train_dataset_fo-en
|
AnnikaSimonsen
| 2023-11-27T12:00:35Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T11:46:37Z |
---
dataset_info:
features:
- name: File name
dtype: string
- name: Faroese
dtype: string
- name: English translation
dtype: string
splits:
- name: train
num_bytes: 11318248
num_examples: 105634
download_size: 7455201
dataset_size: 11318248
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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onkar627/MentaBot_Project
|
onkar627
| 2023-11-27T12:44:46Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T12:42:53Z |
---
license: mit
---
|
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BangumiBase/ginnosaji
|
BangumiBase
| 2023-11-27T15:00:15Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T13:00:54Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Gin No Saji
This is the image base of bangumi Gin no Saji, we detected 27 characters, 3590 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 | 18 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 700 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 181 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 97 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 35 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 44 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 1308 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 64 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 22 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 56 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 14 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 8 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 28 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 81 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 41 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 48 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 23 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 12 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 31 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 11 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 80 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 58 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 65 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 10 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 490 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 8 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 57 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
plaguss/end2end_textclassification
|
plaguss
| 2023-11-27T13:33:58Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T13:33:48Z |
---
dataset_info:
features:
- name: text
dtype: string
id: field
- name: label
list:
- name: user_id
dtype: string
id: question
- name: value
dtype: string
id: suggestion
- name: status
dtype: string
id: question
- name: label-suggestion
dtype: string
id: suggestion
- name: label-suggestion-metadata
struct:
- name: type
dtype: string
id: suggestion-metadata
- name: score
dtype: float32
id: suggestion-metadata
- name: agent
dtype: string
id: suggestion-metadata
- name: external_id
dtype: string
id: external_id
- name: metadata
dtype: string
id: metadata
splits:
- name: train
num_bytes: 343408
num_examples: 1000
download_size: 181964
dataset_size: 343408
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "end2end_textclassification"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
HuyButter/Forklift-Person-Dataset
|
HuyButter
| 2023-11-27T14:35:32Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T13:39:25Z |
---
license: apache-2.0
---
|
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] |
AlexWortega/InstructCaptions
|
AlexWortega
| 2023-11-27T14:34:22Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T13:41:24Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 48943069439.6
num_examples: 33650
download_size: 35099473289
dataset_size: 48943069439.6
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Instruct stlye Text Image dataset
Following dataset was crawled and filetered from COYO, Laion and captioned with LLAVA 13b
|
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] |
ScandEval/nordjylland-news-summarization-mini
|
ScandEval
| 2023-11-27T13:50:41Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T13:50:08Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
dataset_info:
features:
- name: input_text
dtype: string
- name: target_text
dtype: string
- name: text_len
dtype: int64
- name: summary_len
dtype: int64
splits:
- name: train
num_bytes: 1588698
num_examples: 1024
- name: val
num_bytes: 392467
num_examples: 256
- name: test
num_bytes: 3268194
num_examples: 2048
download_size: 3271757
dataset_size: 5249359
---
# Dataset Card for "nordjylland-news-summarization-mini"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
babosso75/ListeA
|
babosso75
| 2023-11-27T13:58:07Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T13:58:06Z |
---
license: mit
---
|
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idleheroevich2/Krebs
|
idleheroevich2
| 2023-11-27T14:30:24Z | 0 | 0 |
[
"license:unknown",
"region:us"
] | null | 2023-11-27T14:15:43Z |
---
license: unknown
---
|
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shelby94/DATASET21
|
shelby94
| 2023-11-27T14:56:42Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T14:55:13Z |
---
license: openrail
---
|
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] |
tyzhu/squad_qa_title_v5_full_random_permute_8
|
tyzhu
| 2023-11-27T15:28:06Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T15:27:56Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: answer
dtype: string
- name: context_id
dtype: string
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 9977278.16852058
num_examples: 6305
- name: validation
num_bytes: 353148
num_examples: 300
download_size: 1477699
dataset_size: 10330426.16852058
---
# Dataset Card for "squad_qa_title_v5_full_random_permute_8"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
tyzhu/squad_qa_context_v5_full_random_permute_8
|
tyzhu
| 2023-11-27T15:38:18Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T15:38:09Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: answer
dtype: string
- name: context_id
dtype: string
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 4350151.0
num_examples: 2385
- name: validation
num_bytes: 570908
num_examples: 300
download_size: 1029814
dataset_size: 4921059.0
---
# Dataset Card for "squad_qa_context_v5_full_random_permute_8"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
tyzhu/squad_qa_no_id_v5_full_random_permute_2
|
tyzhu
| 2023-11-27T15:38:56Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T15:38:49Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: answer
dtype: string
- name: context_id
dtype: string
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 5042862.974380165
num_examples: 3365
- name: validation
num_bytes: 342766
num_examples: 300
download_size: 1264341
dataset_size: 5385628.974380165
---
# Dataset Card for "squad_qa_no_id_v5_full_random_permute_2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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] |
tyzhu/squad_qa_no_id_v5_full_random_permute_8
|
tyzhu
| 2023-11-27T15:39:39Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T15:39:33Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: answer
dtype: string
- name: context_id
dtype: string
- name: inputs
dtype: string
- name: targets
dtype: string
splits:
- name: train
num_bytes: 9919664.916017797
num_examples: 6305
- name: validation
num_bytes: 342766
num_examples: 300
download_size: 1460621
dataset_size: 10262430.916017797
---
# Dataset Card for "squad_qa_no_id_v5_full_random_permute_8"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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fatcatmilo/KGText
|
fatcatmilo
| 2023-11-27T15:50:50Z | 0 | 0 |
[
"license:mit",
"region:us"
] | null | 2023-11-27T15:50:50Z |
---
license: mit
---
|
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] |
Trollator/shad
|
Trollator
| 2023-11-27T15:57:13Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T15:56:41Z |
---
license: openrail
---
|
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] |
Gabriel1322/juao
|
Gabriel1322
| 2023-11-27T15:59:38Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T15:58:17Z |
---
license: openrail
---
|
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] |
ancerlop/crowdsourced-calculator-demo
|
ancerlop
| 2023-11-27T20:41:13Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T17:05:09Z |
---
configs:
- config_name: default
data_files:
- split: train
path: data.csv
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
[More Information Needed]
|
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aciborowska/customers-complaints-train-eval
|
aciborowska
| 2023-11-27T17:11:53Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T17:11:46Z |
---
dataset_info:
features:
- name: Date_received
dtype: string
- name: Product
dtype: string
- name: Sub_product
dtype: string
- name: Issue
dtype: string
- name: Sub_issue
dtype: string
- name: Consumer_complaint_narrative
dtype: string
- name: Company_public_response
dtype: string
- name: Company
dtype: string
- name: State
dtype: string
- name: ZIP_code
dtype: string
- name: Tags
dtype: string
- name: Consumer_consent_provided?
dtype: string
- name: Submitted_via
dtype: string
- name: Date_sent_to_company
dtype: string
- name: Company response to consumer
dtype: string
- name: Timely_response?
dtype: string
- name: Consumer_disputed?
dtype: string
- name: Complaint_ID
dtype: int64
splits:
- name: train
num_bytes: 36271224
num_examples: 27000
download_size: 14216092
dataset_size: 36271224
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "customers-complaints-train-eval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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yvonne1123/Training_Dynamics
|
yvonne1123
| 2023-11-27T17:24:30Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T17:24:29Z |
---
license: apache-2.0
---
|
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] |
aciborowska/customers-complaints-eval
|
aciborowska
| 2023-11-27T17:38:31Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T17:38:13Z |
---
dataset_info:
features:
- name: Date_received
dtype: string
- name: Product
dtype: string
- name: Sub_product
dtype: string
- name: Issue
dtype: string
- name: Sub_issue
dtype: string
- name: Consumer_complaint_narrative
dtype: string
- name: Company_public_response
dtype: string
- name: Company
dtype: string
- name: State
dtype: string
- name: ZIP_code
dtype: string
- name: Tags
dtype: string
- name: Consumer_consent_provided?
dtype: string
- name: Submitted_via
dtype: string
- name: Date_sent_to_company
dtype: string
- name: Company response to consumer
dtype: string
- name: Timely_response?
dtype: string
- name: Consumer_disputed?
dtype: string
- name: Complaint_ID
dtype: int64
splits:
- name: train
num_bytes: 3948222
num_examples: 3000
download_size: 1539746
dataset_size: 3948222
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "customers-complaints-eval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
|
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RaafZ/MCKEVINIAV1
|
RaafZ
| 2023-11-27T18:07:04Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T18:06:07Z |
---
license: openrail
---
|
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BangumiBase/thedangersinmyheart
|
BangumiBase
| 2023-11-27T19:43:47Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T18:42:31Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of The Dangers In My Heart
This is the image base of bangumi The Dangers in My Heart, we detected 18 characters, 1703 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 | 561 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 83 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 78 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 44 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 27 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 33 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 70 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 21 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 261 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 117 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 123 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 27 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 36 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 29 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 10 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 13 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 51 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 119 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
SadeghJafari/CVC
|
SadeghJafari
| 2023-11-27T18:50:46Z | 0 | 0 |
[
"license:apache-2.0",
"region:us"
] | null | 2023-11-27T18:45:38Z |
---
license: apache-2.0
---
|
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] |
adamo1139/AEZAKMI_v1
|
adamo1139
| 2023-11-27T23:50:46Z | 0 | 0 |
[
"license:other",
"region:us"
] | null | 2023-11-27T19:02:57Z |
---
license: other
license_name: other
license_link: LICENSE
---
This is dataset based on airoboros 2.2.1 with removed orca and gptslop samples.
Models trained on this datasets are likely to hallucinate more than base airoboros since I also removed a lot of samples that made the model aware that it's not a human but an ai and it doesn't have physical body.
The plus of that is that non-llama model trained on it should very rarely if ever issue a refusal.
It also should sound more like a person than a sterile gpt-4.
I can't guarantee for that to happen with llama 2 base models since they are pre-trained with gptslop and refusals.
If you see a model that was trained on this dataset generating refusals, let me know and I will try to fix that.
I removed jokes from airoboros 2.2.1 that I used as base and put in jokes from airoboros 2.2, as jokes from 2.2.1 were really lame.
I will probably release fine-tunes of Yi-34B and Llama 1 33B on this dataset soon, Mistral finetune is available already.
License: same as airoboros 2.2.1/airoboros 2.2
|
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] |
Frixi/Kevin_Martes_13
|
Frixi
| 2023-11-27T19:06:06Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T19:05:15Z |
---
license: openrail
---
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Pablao0948/Xuxa_Circo
|
Pablao0948
| 2023-11-27T19:23:33Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T19:08:15Z |
---
license: openrail
---
|
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] |
haroldim/haroldo-para-narrar
|
haroldim
| 2023-11-27T19:30:36Z | 0 | 0 |
[
"license:openrail++",
"region:us"
] | null | 2023-11-27T19:21:44Z |
---
license: openrail++
---
|
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] |
rmagesh/my-image-captioning-dataset
|
rmagesh
| 2023-11-28T18:08:53Z | 0 | 0 |
[
"region:us"
] | null | 2023-11-27T19:24:56Z |
---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 809012.0
num_examples: 1
download_size: 810428
dataset_size: 809012.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
|
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] |
haroldim/treino-voz-haroldo-para-narrar
|
haroldim
| 2023-11-27T19:34:45Z | 0 | 0 |
[
"license:openrail++",
"region:us"
] | null | 2023-11-27T19:34:02Z |
---
license: openrail++
---
|
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BangumiBase/xxxholic
|
BangumiBase
| 2023-11-27T21:21:54Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T19:54:38Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Xxxholic
This is the image base of bangumi xxxHOLiC, we detected 36 characters, 3967 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 | 2265 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 70 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 20 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 189 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 20 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 23 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 11 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 16 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 27 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 9 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 59 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 94 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 20 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 67 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 33 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 48 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 543 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 29 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 66 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 16 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 26 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 11 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 30 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 29 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 31 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 9 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 12 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 7 | [Download](27/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 28 | 6 | [Download](28/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| 29 | 8 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 39 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 23 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 7 | [Download](32/dataset.zip) |  |  |  |  |  |  |  | N/A |
| 33 | 14 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 21 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 69 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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BangumiBase/kamisamakiss
|
BangumiBase
| 2023-11-27T21:41:48Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T19:55:35Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Kamisama Kiss
This is the image base of bangumi Kamisama Kiss, we detected 50 characters, 2686 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 | 11 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 65 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 40 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 24 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 59 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 63 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 50 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 20 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 122 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 122 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 544 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 176 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 18 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 33 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 29 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 22 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 32 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 16 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 27 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 257 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 31 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 14 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 41 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 10 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 25 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 17 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 106 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 12 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 86 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 16 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| 30 | 9 | [Download](30/dataset.zip) |  |  |  |  |  |  |  |  |
| 31 | 10 | [Download](31/dataset.zip) |  |  |  |  |  |  |  |  |
| 32 | 51 | [Download](32/dataset.zip) |  |  |  |  |  |  |  |  |
| 33 | 26 | [Download](33/dataset.zip) |  |  |  |  |  |  |  |  |
| 34 | 11 | [Download](34/dataset.zip) |  |  |  |  |  |  |  |  |
| 35 | 25 | [Download](35/dataset.zip) |  |  |  |  |  |  |  |  |
| 36 | 8 | [Download](36/dataset.zip) |  |  |  |  |  |  |  |  |
| 37 | 10 | [Download](37/dataset.zip) |  |  |  |  |  |  |  |  |
| 38 | 28 | [Download](38/dataset.zip) |  |  |  |  |  |  |  |  |
| 39 | 40 | [Download](39/dataset.zip) |  |  |  |  |  |  |  |  |
| 40 | 9 | [Download](40/dataset.zip) |  |  |  |  |  |  |  |  |
| 41 | 10 | [Download](41/dataset.zip) |  |  |  |  |  |  |  |  |
| 42 | 9 | [Download](42/dataset.zip) |  |  |  |  |  |  |  |  |
| 43 | 11 | [Download](43/dataset.zip) |  |  |  |  |  |  |  |  |
| 44 | 16 | [Download](44/dataset.zip) |  |  |  |  |  |  |  |  |
| 45 | 12 | [Download](45/dataset.zip) |  |  |  |  |  |  |  |  |
| 46 | 32 | [Download](46/dataset.zip) |  |  |  |  |  |  |  |  |
| 47 | 8 | [Download](47/dataset.zip) |  |  |  |  |  |  |  |  |
| 48 | 6 | [Download](48/dataset.zip) |  |  |  |  |  |  | N/A | N/A |
| noise | 267 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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BangumiBase/shinsekaiyori
|
BangumiBase
| 2023-11-27T21:35:09Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T20:16:23Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Shinsekai Yori
This is the image base of bangumi Shinsekai Yori, we detected 31 characters, 1618 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 | 431 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 90 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 66 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 19 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 24 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 18 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 13 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 19 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 21 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 14 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 45 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 14 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 119 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 29 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 21 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 69 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 198 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 33 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 46 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 15 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 12 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 12 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 25 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 40 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 34 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 12 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 25 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 8 | [Download](27/dataset.zip) |  |  |  |  |  |  |  |  |
| 28 | 8 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 5 | [Download](29/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| noise | 133 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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breno30/PauloCarvalhoVoice
|
breno30
| 2023-11-27T20:26:41Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T20:26:13Z |
---
license: openrail
---
|
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] |
hsienchen/CORD2
|
hsienchen
| 2023-11-27T20:46:57Z | 0 | 0 |
[
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:ab",
"license:mit",
"biology",
"region:us"
] |
[
"text-generation"
] | 2023-11-27T20:34:15Z |
---
license: mit
task_categories:
- text-generation
language:
- ab
tags:
- biology
pretty_name: CORD2
size_categories:
- 1K<n<10K
---
|
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BangumiBase/vanitasnokarte
|
BangumiBase
| 2023-11-27T22:15:06Z | 0 | 0 |
[
"size_categories:1K<n<10K",
"license:mit",
"art",
"region:us"
] | null | 2023-11-27T20:36:56Z |
---
license: mit
tags:
- art
size_categories:
- 1K<n<10K
---
# Bangumi Image Base of Vanitas No Karte
This is the image base of bangumi Vanitas no Karte, we detected 31 characters, 2212 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 | 446 | [Download](0/dataset.zip) |  |  |  |  |  |  |  |  |
| 1 | 58 | [Download](1/dataset.zip) |  |  |  |  |  |  |  |  |
| 2 | 47 | [Download](2/dataset.zip) |  |  |  |  |  |  |  |  |
| 3 | 21 | [Download](3/dataset.zip) |  |  |  |  |  |  |  |  |
| 4 | 20 | [Download](4/dataset.zip) |  |  |  |  |  |  |  |  |
| 5 | 31 | [Download](5/dataset.zip) |  |  |  |  |  |  |  |  |
| 6 | 102 | [Download](6/dataset.zip) |  |  |  |  |  |  |  |  |
| 7 | 14 | [Download](7/dataset.zip) |  |  |  |  |  |  |  |  |
| 8 | 13 | [Download](8/dataset.zip) |  |  |  |  |  |  |  |  |
| 9 | 42 | [Download](9/dataset.zip) |  |  |  |  |  |  |  |  |
| 10 | 16 | [Download](10/dataset.zip) |  |  |  |  |  |  |  |  |
| 11 | 11 | [Download](11/dataset.zip) |  |  |  |  |  |  |  |  |
| 12 | 46 | [Download](12/dataset.zip) |  |  |  |  |  |  |  |  |
| 13 | 38 | [Download](13/dataset.zip) |  |  |  |  |  |  |  |  |
| 14 | 12 | [Download](14/dataset.zip) |  |  |  |  |  |  |  |  |
| 15 | 481 | [Download](15/dataset.zip) |  |  |  |  |  |  |  |  |
| 16 | 67 | [Download](16/dataset.zip) |  |  |  |  |  |  |  |  |
| 17 | 94 | [Download](17/dataset.zip) |  |  |  |  |  |  |  |  |
| 18 | 40 | [Download](18/dataset.zip) |  |  |  |  |  |  |  |  |
| 19 | 64 | [Download](19/dataset.zip) |  |  |  |  |  |  |  |  |
| 20 | 19 | [Download](20/dataset.zip) |  |  |  |  |  |  |  |  |
| 21 | 9 | [Download](21/dataset.zip) |  |  |  |  |  |  |  |  |
| 22 | 40 | [Download](22/dataset.zip) |  |  |  |  |  |  |  |  |
| 23 | 55 | [Download](23/dataset.zip) |  |  |  |  |  |  |  |  |
| 24 | 39 | [Download](24/dataset.zip) |  |  |  |  |  |  |  |  |
| 25 | 55 | [Download](25/dataset.zip) |  |  |  |  |  |  |  |  |
| 26 | 32 | [Download](26/dataset.zip) |  |  |  |  |  |  |  |  |
| 27 | 5 | [Download](27/dataset.zip) |  |  |  |  |  | N/A | N/A | N/A |
| 28 | 8 | [Download](28/dataset.zip) |  |  |  |  |  |  |  |  |
| 29 | 10 | [Download](29/dataset.zip) |  |  |  |  |  |  |  |  |
| noise | 277 | [Download](-1/dataset.zip) |  |  |  |  |  |  |  |  |
|
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] |
Lam-ia/Wikipedia-Euskera
|
Lam-ia
| 2023-11-27T20:46:31Z | 0 | 0 |
[
"task_categories:text-generation",
"size_categories:n<1K",
"language:eu",
"license:apache-2.0",
"region:us"
] |
[
"text-generation"
] | 2023-11-27T20:41:21Z |
---
license: apache-2.0
task_categories:
- text-generation
language:
- eu
pretty_name: tiny-basque-demo
size_categories:
- n<1K
---
|
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Carlosgg14/Boruto
|
Carlosgg14
| 2023-11-28T16:00:05Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T22:09:29Z |
---
license: openrail
---
|
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YumemiTheBunny/ochakkuraraka
|
YumemiTheBunny
| 2023-11-27T22:23:36Z | 0 | 0 |
[
"license:openrail",
"region:us"
] | null | 2023-11-27T22:20:33Z |
---
license: openrail
---
|
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