author stringlengths 2 29 ⌀ | cardData null | citation stringlengths 0 9.58k ⌀ | description stringlengths 0 5.93k ⌀ | disabled bool 1
class | downloads float64 1 1M ⌀ | gated bool 2
classes | id stringlengths 2 108 | lastModified stringlengths 24 24 | paperswithcode_id stringlengths 2 45 ⌀ | private bool 2
classes | sha stringlengths 40 40 | siblings list | tags list | readme_url stringlengths 57 163 | readme stringlengths 0 977k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
MauriceV2021 | null | null | null | false | 1 | false | MauriceV2021/AuroraSDGsDataset | 2022-05-06T11:24:47.000Z | null | false | cfe049cf2184769741166b8b369798bbe3dafb70 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/MauriceV2021/AuroraSDGsDataset/resolve/main/README.md | ---
license: cc-by-4.0
---
# Aurora SDGs Dataset
This data set contains metdata of 1.4 million research papers. The abstract plus the SDG labels for the Goals and Targets. |
filwsyl | null | null | null | false | 1 | false | filwsyl/ascend | 2022-10-25T05:24:45.000Z | null | false | 9e3261d54d2c334e495dc6cb6fbd8fe99b13c2ac | [] | [
"arxiv:2112.06223",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"language:zh",
"language_bcp47:en",
"language_bcp47:zh-CN",
"license:cc-by-sa-4.0",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_cate... | https://huggingface.co/datasets/filwsyl/ascend/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- zh
language_bcp47:
- en
- zh-CN
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
pretty_name: 'ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in
Multi-turn Conversation'
size_categories:
- 10K<n<10... |
ai4bharat | null | null | null | false | 2 | false | ai4bharat/Aksharantar | 2022-10-13T06:08:38.000Z | null | false | c3a4bb03cdf39b47a16c6f931f7a7149dfe677cb | [] | [
"arxiv:2205.03018",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"language_creators:machine-generated",
"language_creators:found",
"language_creators:other",
"language:asm-IN",
"language:ben-IN",
"language:brx-IN",
"language:guj-IN",
"language:hin-IN",
"language:kan-... | https://huggingface.co/datasets/ai4bharat/Aksharantar/resolve/main/README.md | ---
annotations_creators: []
language_creators:
- crowdsourced
- expert-generated
- machine-generated
- found
- other
language:
- asm-IN
- ben-IN
- brx-IN
- guj-IN
- hin-IN
- kan-IN
- kas-IN
- kok-IN
- mai-IN
- mal-IN
- mar-IN
- mni-IN
- nep-IN
- ori-IN
- pan-IN
- san-IN
- sid-IN
- tam-IN
- tel-IN
- urd-IN
license:
- c... |
cradle-bio | null | null | null | false | 1 | false | cradle-bio/FLIP_clusters | 2022-05-06T13:29:51.000Z | null | false | 815620f1e0dbeaa8958d7101777047ed24a9cbbd | [] | [] | https://huggingface.co/datasets/cradle-bio/FLIP_clusters/resolve/main/README.md | # Full FLIP stability dataset
The stability dataset from flip, which is based on the meltome atlas, data has those columns:
```
[ 'index', 'seq_id', 'sequence', 'target', 'cluster_center',
'cluster_distance']
```
- **Index** from the original dataset
- **Seq_id** a unique sequence ID string that... |
polinaeterna | null | @inproceedings{valk2021slt,
title={{VoxLingua107}: a Dataset for Spoken Language Recognition},
author={J{\"o}rgen Valk and Tanel Alum{\"a}e},
booktitle={Proc. IEEE SLT Workshop},
year={2021},
} | This new dataset is designed to solve this great NLP task and is crafted with a lot of care. | false | 3 | false | polinaeterna/vox_lingua | 2022-05-06T15:38:01.000Z | null | false | bac95ab145db3d94fb4562ce484fcb77a42af758 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/polinaeterna/vox_lingua/resolve/main/README.md | ---
license: cc-by-4.0
---
Use it as usual:
```python
ds = load_dataset("polinaeterna/vox_lingua", "sco")
```
If you want to download all the languages, use `"all"` config:
```python
ds = load_dataset("polinaeterna/vox_lingua", "all")
``` |
Rizwan125 | null | null | null | false | 1 | false | Rizwan125/AIByRizwan | 2022-05-06T17:06:15.000Z | null | false | a5f168f935ebaebd708794c03241f07efbfdbeb1 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/Rizwan125/AIByRizwan/resolve/main/README.md | ---
license: apache-2.0
---
|
strombergnlp | null | @inproceedings{ritter2011named,
title={Named entity recognition in tweets: an experimental study},
author={Ritter, Alan and Clark, Sam and Etzioni, Oren and others},
booktitle={Proceedings of the 2011 conference on empirical methods in natural language processing},
pages={1524--1534},
year={2011}
}
@inprocee... | Part-of-speech information is basic NLP task. However, Twitter text
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style.
This dataset contains two datasets for English PoS tagging for tweets:
* Ritter, with train/dev/test
* Foster, with dev/test
Splits defined in the Derczy... | false | 14 | false | strombergnlp/twitter_pos | 2022-10-25T21:43:15.000Z | ritter-pos | false | e2fd67fea2d92b54b613fa1eb2af9023f172e91a | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:part-of-speech"
] | https://huggingface.co/datasets/strombergnlp/twitter_pos/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- part-of-speech
paperswithcode_id: ritter-pos
pretty_name: Twitter Part-... |
kimcando | null | null | null | false | 1 | false | kimcando/KOR-RE-natures-and-environments | 2022-05-06T22:11:26.000Z | null | false | c66f16a81c93184bdc7f22cfbed284e5b7c12cc7 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/kimcando/KOR-RE-natures-and-environments/resolve/main/README.md | ---
license: apache-2.0
---
# Dataset Card for [KOR-RE-natures-and-environments]
You can find relation map, guidelines(written in Korean), short technical papers in this [github repo](https://github.com/boostcampaitech3/level2-data-annotation_nlp-level2-nlp-03). This work is done by as part of project for Boostcamp A... |
nateraw | null | null | null | false | 1 | false | nateraw/background-remover-files | 2022-05-07T02:53:12.000Z | null | false | c1b3a1715af331b7834a66a4e878f5fad0a5761e | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/nateraw/background-remover-files/resolve/main/README.md | ---
license: apache-2.0
---
|
d0r1h | null | null | null | false | 7 | false | d0r1h/customer_churn | 2022-05-07T03:27:33.000Z | null | false | 7dad1ae753d14498544c4dc1e48e41e7bd633d56 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/d0r1h/customer_churn/resolve/main/README.md | ---
license: apache-2.0
---
|
NLPC-UOM | null | null | null | false | 1 | false | NLPC-UOM/Student_feedback_analysis_dataset | 2022-10-25T10:13:19.000Z | null | false | 6ed818c8ce6d452e5de3133f822c2b80cf02f8d5 | [] | [
"language:en",
"license:mit"
] | https://huggingface.co/datasets/NLPC-UOM/Student_feedback_analysis_dataset/resolve/main/README.md | # README
## Annotated Student Feedback
---
annotations_creators: []
language:
- en
license:
- mit
---
This resource contains 3000 student feedback data that have been annotated for aspect terms, opinion terms, polarities of the opinion terms towards targeted aspects, document-level opinion polarities, and sentence sep... |
Bingsu | null | null | [아카라이브 베스트 라이브 채널](https://arca.live/b/live)의 2021년 8월 16일부터 2022년 5월 6일까지의 데이터를 수집하여, 댓글만 골라낸 데이터입니다. | false | 1 | false | Bingsu/arcalive_220506 | 2022-07-02T00:09:48.000Z | null | false | e96165af1c82b5dd47b286d196f6ad6ab03ed3ff | [] | [
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:ko",
"license:cc0-1.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:fill-mask",
"task_categories:text-generation",
"task_ids:masked-language-modeling",
"... | https://huggingface.co/datasets/Bingsu/arcalive_220506/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- ko
license:
- cc0-1.0
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: arcalive_210816_220506
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- fill-mask
- text-generation
task_ids:
- mas... |
zhiguoxu | null | null | null | false | 1 | false | zhiguoxu/test_data | 2022-05-07T06:55:39.000Z | null | false | c31fd74df02439e5a085005238addab9c70dfcf6 | [] | [] | https://huggingface.co/datasets/zhiguoxu/test_data/resolve/main/README.md | readme! |
deydebasmita91 | null | null | null | false | 1 | false | deydebasmita91/Tweet | 2022-05-07T07:09:33.000Z | null | false | 9c250843ee2a24eb03085907ade3d4261916fa9c | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/deydebasmita91/Tweet/resolve/main/README.md | ---
license: afl-3.0
---
|
laion | null | null | null | false | 488 | false | laion/laion-high-resolution | 2022-05-07T12:11:38.000Z | null | false | b7e366f734f83691bc7f09641c97f7ef500a6543 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/laion/laion-high-resolution/resolve/main/README.md | ---
license: cc-by-4.0
---
Laion high resolution is a >= 1024x1024 subset of laion5B. It has 170M samples
A good use case is to train a superresolution model.
Refer to [img2dataset guide](https://github.com/rom1504/img2dataset/blob/main/dataset_examples/laion-high-resolution.md) for downloading |
nadhifikbarw | null | null | null | false | 1 | false | nadhifikbarw/id_ner_nimas | 2022-10-25T10:13:25.000Z | null | false | daab7272f119b6d223bb119da987cf10fe210ed7 | [] | [
"language:id",
"task_categories:token-classification"
] | https://huggingface.co/datasets/nadhifikbarw/id_ner_nimas/resolve/main/README.md | ---
language:
- id
task_categories:
- token-classification
---
Token classification dataset developed from dataset by Katarina Nimas Kusumawati's undergraduate thesis:
**"Identifikasi Entitas Bernama dalam Domain Medis pada Layanan Konsultasi Kesehatan Berbahasa Menggunkan Alrogritme Bidirectional-LSTM-CRF"**
Inst... |
jeremyf | null | null | null | false | 1 | false | jeremyf/fanfiction_z | 2022-05-07T20:53:30.000Z | null | false | 45afd873a3a06ec89473aee2cc4bcd0037474384 | [] | [
"language:en",
"tags:fanfiction",
"datasets:fanfiction_z"
] | https://huggingface.co/datasets/jeremyf/fanfiction_z/resolve/main/README.md | ---
language:
- en
tags:
- fanfiction
datasets:
- fanfiction_z
---
## fanfiction.net
Cleaning up https://archive.org/download/fanfictiondotnet_repack
Starting with "Z" stories to get the hang of it. |
hidude562 | null | null | null | false | 1 | false | hidude562/textsources | 2022-05-07T17:12:39.000Z | null | false | 26b54f488012d7f8fd935a4d5d85c46f05fb665d | [] | [] | https://huggingface.co/datasets/hidude562/textsources/resolve/main/README.md | Can be used for qualifying data sources |
hidude562 | null | null | null | false | 1 | false | hidude562/BadWikipedia | 2022-05-07T17:48:25.000Z | null | false | 9cdb9cd60e61788d28f341c0cd0bd6ffd2eb3eef | [] | [] | https://huggingface.co/datasets/hidude562/BadWikipedia/resolve/main/README.md | This dataset is a copy from a wikipedia dataset on kaggle |
peandrew | null | null | null | false | 13 | false | peandrew/conceptnet_en_nomalized | 2022-05-08T03:11:02.000Z | null | false | 764d16c169120835d703ec866dc9c41a6c2a7d88 | [] | [] | https://huggingface.co/datasets/peandrew/conceptnet_en_nomalized/resolve/main/README.md | This is the English part of the ConceptNet and we have removed the useless information. |
parvezmrobin | null | null | null | false | 1 | false | parvezmrobin/MCMD | 2022-05-09T07:25:40.000Z | null | false | 1925dfe6101a528f3dba572ae6aee25f49225c26 | [] | [] | https://huggingface.co/datasets/parvezmrobin/MCMD/resolve/main/README.md | This dataset is the CSV version of the original MCMD (Multi-programming-language Commit Message Dataset) provided by Tao et al. in their paper "On the Evaluation of Commit Message Generation Models: An Experimental Study".
The original version of the dataset can be found in [Zenodo](https://doi.org/10.5281/zenodo.50257... |
nateraw | null | @inproceedings{wang2019learning,
title={Learning Robust Global Representations by Penalizing Local Predictive Power},
author={Wang, Haohan and Ge, Songwei and Lipton, Zachary and Xing, Eric P},
booktitle={Advances in Neural Information Processing Systems},
pages={10506--10518},
y... | ImageNet-Sketch data set consists of 50000 images, 50 images for each of the 1000 ImageNet classes.
We construct the data set with Google Image queries "sketch of __", where __ is the standard class name.
We only search within the "black and white" color scheme. We initially query 100 images for every class,
and then m... | false | 1 | false | nateraw/imagenet-sketch | 2022-05-08T05:41:33.000Z | null | false | ab6223087bf5d6f2e81fef71cb174750266305d1 | [] | [
"license:mit"
] | https://huggingface.co/datasets/nateraw/imagenet-sketch/resolve/main/README.md | ---
license: mit
---
|
bananabot | null | null | null | false | 1 | false | bananabot/engMollywoodSummaries | 2022-05-08T15:54:28.000Z | null | false | 6a2a328e05f100eff4a63f6aec652dbb2ccb214d | [] | [
"license:wtfpl"
] | https://huggingface.co/datasets/bananabot/engMollywoodSummaries/resolve/main/README.md | ---
license: wtfpl
---
data I hand picked from https://blcklst.com/lists/ and http://cs.cmu.edu/~ark/personas/ |
ufukhaman | null | null | null | false | 1 | false | ufukhaman/uspto_balanced_200k_ipc_classification | 2022-05-08T17:43:33.000Z | null | false | f69b08be6094f10031b22ec7ba17e6968d3c33d5 | [] | [
"license:mit"
] | https://huggingface.co/datasets/ufukhaman/uspto_balanced_200k_ipc_classification/resolve/main/README.md | ---
license: mit
---
|
nguyenvulebinh | null | null | null | false | 1 | false | nguyenvulebinh/fsd50k | 2022-05-08T22:18:48.000Z | null | false | b8f1d27905d8f70f9ab5440a925e00f7bbddcb5f | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/nguyenvulebinh/fsd50k/resolve/main/README.md | ---
license: cc-by-4.0
---
|
pile-of-law | null | TODO | A living legal dataset. | false | 1 | false | pile-of-law/eoir_privacy | 2022-07-07T08:44:32.000Z | null | false | 212b8789f3958e28a961b7147be3c52b83992918 | [] | [
"arxiv:2207.00220",
"language_creators:found",
"language:en",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"task_categories:text-classification"
] | https://huggingface.co/datasets/pile-of-law/eoir_privacy/resolve/main/README.md | ---
language_creators:
- found
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: eoir_privacy
source_datasets: []
task_categories:
- text-classification
viewer: false
---
# Dataset Card for eoir_privacy
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset ... |
lilitket | null | null | null | false | 2 | false | lilitket/voxlingua107 | 2022-05-08T23:27:04.000Z | null | false | 369d3fa365afd16e699f5dfa2ff283675f637aaa | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/lilitket/voxlingua107/resolve/main/README.md | ---
license: apache-2.0
---
|
strombergnlp | null | @inproceedings{lozhnikov2018stance,
title={Stance prediction for Russian: data and analysis},
author={Lozhnikov, Nikita and Derczynski, Leon and Mazzara, Manuel},
booktitle={International Conference in Software Engineering for Defence Applications},
pages={176--186},
year={2018},
organization={Springer}
} | This is a stance prediction dataset in Russian. The dataset contains comments on news articles,
and rows are a comment, the title of the news article it responds to, and the stance of the comment
towards the article. | false | 8 | false | strombergnlp/rustance | 2022-10-25T21:46:32.000Z | rustance | false | a2a4aa7bb2f872f0164a04f198b1c875df065a8a | [] | [
"arxiv:1809.01574",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ru",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:sentiment-clas... | https://huggingface.co/datasets/strombergnlp/rustance/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ru
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
- sentiment-classification
paperswithcode_id: rustance
pretty_na... |
Fhrozen | null | null | null | false | 2 | false | Fhrozen/AudioSet2K22 | 2022-06-27T04:09:11.000Z | null | false | 4c997798430f5b17bf0ec9b325f373f4ee930149 | [] | [
"license:cc-by-sa-4.0",
"annotations_creators:unknown",
"language_creators:unknown",
"size_categories:100K<n<100M",
"source_datasets:unknown",
"task_categories:audio-classification",
"task_ids:other-audio-slot-filling"
] | https://huggingface.co/datasets/Fhrozen/AudioSet2K22/resolve/main/README.md | ---
license: cc-by-sa-4.0
annotations_creators:
- unknown
language_creators:
- unknown
size_categories:
- 100K<n<100M
source_datasets:
- unknown
task_categories:
- audio-classification
task_ids:
- other-audio-slot-filling
---
# Dataset Card for audioset2022
## Table of Contents
- [Dataset Description](#dataset-descrip... |
Maddy132 | null | null | null | false | 1 | false | Maddy132/bottles | 2022-05-09T13:13:11.000Z | null | false | 14ee3d2371f129249d64b6e9171b0fa57a8270c8 | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/Maddy132/bottles/resolve/main/README.md | ---
license: afl-3.0
---
|
ccdv | null | @article{DBLP:journals/corr/abs-2005-10070,
author = {Demian Gholipour Ghalandari and
Chris Hokamp and
Nghia The Pham and
John Glover and
Georgiana Ifrim},
title = {A Large-Scale Multi-Document Summarization Dataset from the Wikipedia
... | WCEP10 dataset for summarization.
From paper: "A Large-Scale Multi-Document Summarization Dataset from the Wikipedia
Current Events Portal" by D. Gholipour et al."
From paper: "PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document
Summarization" by W. Xiao et al." | false | 147 | false | ccdv/WCEP-10 | 2022-10-25T10:55:52.000Z | null | false | f223cad3fce49e4490733772610a0cbdb7fbcb9d | [] | [
"arxiv:2005.10070",
"arxiv:2110.08499",
"language:en",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"task_categories:summarization",
"task_categories:text2text-generation",
"tags:conditional-text-generation"
] | https://huggingface.co/datasets/ccdv/WCEP-10/resolve/main/README.md | ---
language:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
task_categories:
- summarization
- text2text-generation
task_ids: []
tags:
- conditional-text-generation
---
# WCEP10 dataset for summarization
Summarization dataset copied from [PRIMERA](https://github.com/allenai/PRIMER)
This dataset is ... |
IljaSamoilov | null | null | null | false | 1 | false | IljaSamoilov/ERR-transcription-to-subtitles | 2022-05-09T18:29:16.000Z | null | false | bc70f671fe1762dc8b9822701c05fcca2ac6169d | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/IljaSamoilov/ERR-transcription-to-subtitles/resolve/main/README.md | ---
license: afl-3.0
---
This dataset is created by Ilja Samoilov. In dataset is tv show subtitles from ERR and transcriptions of those shows created with TalTech ASR.
```
from datasets import load_dataset, load_metric
dataset = load_dataset('csv', data_files={'train': "train.tsv", \
... |
mmillet | null | null | null | false | 1 | false | mmillet/copy | 2022-05-10T09:53:27.000Z | null | false | feb713097480947041997b09537353df3632e1bd | [] | [
"license:other"
] | https://huggingface.co/datasets/mmillet/copy/resolve/main/README.md | ---
license: other
---
emotion datset |
theangrybuddhas | null | null | null | false | 1 | false | theangrybuddhas/code | 2022-05-09T17:13:17.000Z | null | false | d9c5be9a7315c640a3562b12fa5406d15221e6e2 | [] | [] | https://huggingface.co/datasets/theangrybuddhas/code/resolve/main/README.md | |
Pengfei | null | null | null | false | 1 | false | Pengfei/test22 | 2022-05-09T20:21:40.000Z | null | false | aa54aa83ba43c62484e0bba3bc3f50edd3c6d238 | [] | [] | https://huggingface.co/datasets/Pengfei/test22/resolve/main/README.md | |
Eigen | null | null | null | false | 1 | false | Eigen/twttone | 2022-05-09T21:45:39.000Z | null | false | d3e892e10158b2a84a8a9f7ad689c5db4fde444b | [] | [] | https://huggingface.co/datasets/Eigen/twttone/resolve/main/README.md | |
milesbutler | null | null | null | false | 19 | false | milesbutler/consumer_complaints | 2022-05-09T21:27:44.000Z | null | false | ebe8f93c58bbd2a506df86b82d5f4375abf28bae | [] | [
"license:mit"
] | https://huggingface.co/datasets/milesbutler/consumer_complaints/resolve/main/README.md | ---
license: mit
---
This Dataset is from Kaggle. It originally comes from the US Consumer Finance Complaints. This is great dataset for NLP multi-class classification.
|
domenicrosati | null | null | null | false | 1 | false | domenicrosati/QA2D | 2022-10-25T10:13:31.000Z | null | false | d38d3f42978e72c8c3ccc5dca0d3a2ac745f1fcf | [] | [
"arxiv:1809.02922",
"annotations_creators:machine-generated",
"annotations_creators:crowdsourced",
"annotations_creators:found",
"language_creators:machine-generated",
"language_creators:crowdsourced",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:ori... | https://huggingface.co/datasets/domenicrosati/QA2D/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- crowdsourced
- found
language_creators:
- machine-generated
- crowdsourced
language: []
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
- extended|squad
- extended|race
- extended|newsqa
- extended|qamr
- extended|mo... |
mdroth | null | null | null | false | 1 | false | mdroth/github_issues_300 | 2022-05-23T13:35:05.000Z | null | false | 3423bfa905e50c43ba4e21cc7ec07671a0c3ef69 | [] | [] | https://huggingface.co/datasets/mdroth/github_issues_300/resolve/main/README.md | annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
languages:
- en-US
- ''
licenses:
- osl-2.0
multilinguality:
- monolingual
pretty_name: github_issues_300
size_categories:
- n<1K
source_datasets: []
task_categories:
- text-classification
task_ids:
- acceptability-classification
- topic-classificat... |
DFKI-SLT | null | null | null | false | 2 | false | DFKI-SLT/brat | 2022-10-25T06:38:30.000Z | null | false | d921d5bba0c9924ca0774d6d4662f19c310f264c | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"task_categories:token-classification",
"task_ids:parsing"
] | https://huggingface.co/datasets/DFKI-SLT/brat/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
license: []
task_categories:
- token-classification
task_ids:
- parsing
---
# Information Card for Brat
## Table of Contents
- [Description](#description)
- [Summary](#summary)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#da... |
kejian | null | null | null | false | 1 | false | kejian/pile-severetoxic-balanced2 | 2022-05-10T14:34:07.000Z | null | false | 5bb1a071177dc778c2e9818d75a84bc70f4c1338 | [] | [] | https://huggingface.co/datasets/kejian/pile-severetoxic-balanced2/resolve/main/README.md |
# Dataset Card for [kejian/pile-severetoxic-balanced2]
## Generation Procedures
The dataset was constructed using documents from the Pile scored using Perspective API SEVERE-TOXICITY scores.
The procedure was the following:
- The first half of this dataset is kejian/pile-severetoxic-chunk-0, 100k most toxic docume... |
SberDevices | null | null | null | false | 1 | false | SberDevices/Golos | 2022-05-10T08:37:58.000Z | null | false | cd95c2b7bda1e61b32ffde9ed59df0aec56f42d3 | [] | [
"arxiv:1910.10261",
"arxiv:2106.10161"
] | https://huggingface.co/datasets/SberDevices/Golos/resolve/main/README.md | # Golos dataset
Golos is a Russian corpus suitable for speech research. The dataset mainly consists of recorded audio files manually annotated on the crowd-sourcing platform. The total duration of the audio is about 1240 hours.
We have made the corpus freely available for downloading, along with the acoustic model pr... |
drAbreu | null | @Unpublished{
huggingface: dataset,
title = {SourceData NLP},
authors={Thomas Lemberger, EMBO},
year={2021}
} | This dataset is based on the SourceData database and is intented to facilitate training of NLP tasks in the cell and molecualr biology domain. | false | 1 | false | drAbreu/sd-nlp-2 | 2022-10-23T05:47:12.000Z | null | false | cd381fce6249bb2426681b006c7d833a6d48905e | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:named-entity-recognition",
"task_i... | https://huggingface.co/datasets/drAbreu/sd-nlp-2/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets: []
task_categories:
- text-classification
- structure-prediction
task_ids:
- multi-class-classification
- named-entity-reco... |
laugustyniak | null | @inproceedings{augustyniak-etal-2020-political,
title = "Political Advertising Dataset: the use case of the Polish 2020 Presidential Elections",
author = "Augustyniak, Lukasz and
Rajda, Krzysztof and
Kajdanowicz, Tomasz and
Bernaczyk, Micha{\l}",
booktitle = "Proceedings of the The Four... | null | false | 2 | false | laugustyniak/political-advertising-pl | 2022-08-30T08:33:00.000Z | null | false | 6835dd2899e580191ca9973177707d32fef19a13 | [] | [
"annotations_creators:hired_annotators",
"language_creators:found",
"language:pl",
"license:other",
"multilinguality:monolingual",
"size_categories:10<n<10K",
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech-tagging"
] | https://huggingface.co/datasets/laugustyniak/political-advertising-pl/resolve/main/README.md | ---
annotations_creators:
- hired_annotators
language_creators:
- found
language:
- pl
license:
- other
multilinguality:
- monolingual
size_categories:
- 10<n<10K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
- part-of-speech-tagging
pretty_name: Polish-Political-Adverti... |
mteb | null | null | null | false | 1 | false | mteb/raw_arxiv | 2022-09-27T19:12:40.000Z | null | false | b3d2e2bb154eae638f61999224f9ec1f7aff6c53 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/raw_arxiv/resolve/main/README.md | ---
language:
- en
--- |
MilaNLProc | null | @inproceedings{nozza-etal-2021-honest,
title = {"{HONEST}: Measuring Hurtful Sentence Completion in Language Models"},
author = "Nozza, Debora and Bianchi, Federico and Hovy, Dirk",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computat... | HONEST dataset comprises a set of templates for measuring hurtful sentence completions in language models. The templates are provided in six languages (English, Italian, French, Portuguese, Romanian, and Spanish) for binary gender and in English for LGBTQAI+ individuals. WARNING: This dataset contains content that are ... | false | 104 | false | MilaNLProc/honest | 2022-09-28T15:45:09.000Z | honest-en | false | e10910c64b77382d127ec3d957b3b1cc2524d04d | [] | [
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"language_bcp47:en-US",
"language_bcp47:it-IT",
"language_bcp47:fr-FR",
"language_bcp47:pt-PT",
"language_bcp47:ro-RO",
"language_bcp47:es-ES",
"license:mit",
"multilinguality:multilingual",
"size_categories:n<1K",
"so... | https://huggingface.co/datasets/MilaNLProc/honest/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language_bcp47:
- en-US
- it-IT
- fr-FR
- pt-PT
- ro-RO
- es-ES
license:
- mit
multilinguality:
- multilingual
paperswithcode_id: honest-en
pretty_name: HONEST
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-clas... |
mteb | null | null | null | false | 112 | false | mteb/arxiv-clustering-s2s | 2022-09-27T19:12:49.000Z | null | false | b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/arxiv-clustering-s2s/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 124 | false | mteb/arxiv-clustering-p2p | 2022-09-27T19:15:11.000Z | null | false | 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/arxiv-clustering-p2p/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 1 | false | mteb/raw_biorxiv | 2022-09-27T19:15:43.000Z | null | false | 7bf300a139a090f467fd09edea4d481bb2beb5b6 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/raw_biorxiv/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 1 | false | mteb/raw_medrxiv | 2022-09-27T19:15:18.000Z | null | false | 75abecaa8174b06f2056ca6cd3616c79e09897b4 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/raw_medrxiv/resolve/main/README.md | ---
language:
- en
--- |
facebook | null | @inproceedings{wang-etal-2021-voxpopuli,
title = "{V}ox{P}opuli: A Large-Scale Multilingual Speech Corpus for Representation Learning,
Semi-Supervised Learning and Interpretation",
author = "Wang, Changhan and
Riviere, Morgane and
Lee, Ann and
Wu, Anne and
Talnikar, Chaitanya a... | A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. | false | 348 | false | facebook/voxpopuli | 2022-10-14T13:43:12.000Z | null | false | 719aaef8225945c0d80b277de6c79aa42ab053d5 | [] | [
"arxiv:2101.00390",
"language:en",
"language:de",
"language:fr",
"language:es",
"language:pl",
"language:it",
"language:ro",
"language:hu",
"language:cs",
"language:nl",
"language:fi",
"language:hr",
"language:sk",
"language:sl",
"language:et",
"language:lt",
"license:cc0-1.0",
"... | https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/README.md | ---
annotations_creators: []
language:
- en
- de
- fr
- es
- pl
- it
- ro
- hu
- cs
- nl
- fi
- hr
- sk
- sl
- et
- lt
language_creators: []
license:
- cc0-1.0
- other
multilinguality:
- multilingual
pretty_name: VoxPopuli
size_categories: []
source_datasets: []
tags: []
task_categories:
- automatic-speech-recognition
... |
leo19941227 | null | null | null | false | 1 | false | leo19941227/g2p | 2022-05-10T14:50:25.000Z | null | false | fb2b19807e739fb299e4d317244760db86de6b01 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/leo19941227/g2p/resolve/main/README.md | ---
license: apache-2.0
---
|
allenai | null | null | null | false | 228 | false | allenai/mup | 2022-10-25T10:16:52.000Z | null | false | 5223d88b84fbeab9a7004678591ea9d8bb8fdcf4 | [] | [
"license:odc-by"
] | https://huggingface.co/datasets/allenai/mup/resolve/main/README.md | ---
license:
- odc-by
---
# MuP - Multi Perspective Scientific Document Summarization
Generating summaries of scientific documents is known to be a challenging task. Majority of existing work in summarization assumes only one single best gold summary for each given document. Having only one gold summary negatively im... |
s3prl | null | null | null | false | 1 | false | s3prl/g2p | 2022-05-10T15:00:40.000Z | null | false | 805873cb40ef5eb9b3156f47adc3e55454422cde | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/s3prl/g2p/resolve/main/README.md | ---
license: apache-2.0
---
|
Leyo | null | @InProceedings{tgif-cvpr2016,
author = {Li, Yuncheng and Song, Yale and Cao, Liangliang and Tetreault, Joel and Goldberg, Larry and Jaimes, Alejandro and Luo, Jiebo},
title = "{TGIF: A New Dataset and Benchmark on Animated GIF Description}",
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognit... | The Tumblr GIF (TGIF) dataset contains 100K animated GIFs and 120K sentences describing visual content of the animated GIFs.
The animated GIFs have been collected from Tumblr, from randomly selected posts published between May and June of 2015.
We provide the URLs of animated GIFs in this release. The sentences are c... | false | 1 | false | Leyo/TGIF | 2022-10-25T10:24:15.000Z | null | false | 9ce73be4a2e2cd37e6f10480d30370b520754023 | [] | [
"arxiv:1604.02748",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:question-answering",
"task_categories:visual-question-answering",
... | https://huggingface.co/datasets/Leyo/TGIF/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
license:
- other
multilinguality:
- monolingual
pretty_name: TGIF
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
- visual-question-answering
task_ids:
- closed-domain-qa
---
# ... |
strombergnlp | null | @inproceedings{haas-derczynski-2021-discriminating,
title = "Discriminating Between Similar Nordic Languages",
author = "Haas, Ren{\'e} and
Derczynski, Leon",
booktitle = "Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects",
month = apr,
year = "2021",
... | Automatic language identification is a challenging problem. Discriminating
between closely related languages is especially difficult. This paper presents
a machine learning approach for automatic language identification for the
Nordic languages, which often suffer miscategorisation by existing
state-of-the-art tools. ... | false | 1 | false | strombergnlp/nordic_langid | 2022-10-25T21:42:02.000Z | nordic-langid | false | e254179d18ab0165fdb6dbef91178266222bee2a | [] | [
"annotations_creators:found",
"language_creators:found",
"language:da",
"language:nn",
"language:nb",
"language:fo",
"language:is",
"language:sv",
"license:cc-by-sa-3.0",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:text-classifica... | https://huggingface.co/datasets/strombergnlp/nordic_langid/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- da
- nn
- nb
- fo
- is
- sv
license:
- cc-by-sa-3.0
multilinguality:
- multilingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
paperswithcode_id: nordic-langid
pretty_name: Nordic L... |
HuggingFaceM4 | null | @inproceedings{miech19howto100m,
title={How{T}o100{M}: {L}earning a {T}ext-{V}ideo {E}mbedding by {W}atching {H}undred {M}illion {N}arrated {V}ideo {C}lips},
author={Miech, Antoine and Zhukov, Dimitri and Alayrac, Jean-Baptiste and Tapaswi, Makarand and Laptev, Ivan and Sivic, Josef},
booktitle={ICCV},
year... | HowTo100M is a large-scale dataset of narrated videos with an emphasis on instructional videos where content creators teach complex tasks with an explicit intention of explaining the visual content on screen. HowTo100M features a total of
- 136M video clips with captions sourced from 1.2M YouTube videos (15 years of vi... | false | 4 | false | HuggingFaceM4/howto100m | 2022-05-18T23:19:55.000Z | null | false | f17c6abefe91af59763b317b875ee127a725aa40 | [] | [] | https://huggingface.co/datasets/HuggingFaceM4/howto100m/resolve/main/README.md | # Dataset Card for HowTo100M
## Table of Contents
[Table of Contents](#table-of-contents)
[Dataset Description](#dataset-description)
[Dataset Summary](#dataset-summary)
[Dataset Preprocessing](#dataset-preprocessing)
[Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
[Languages](#languages)... |
bigscience | null | null | null | false | 674 | false | bigscience/collaborative_catalog | 2022-05-10T20:24:47.000Z | null | false | 2deceddb7c3f2f4b76c152dc402afbd502272a32 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/bigscience/collaborative_catalog/resolve/main/README.md | ---
license: cc-by-4.0
---
|
lk2 | null | null | null | false | 1 | false | lk2/lk3 | 2022-05-10T19:40:17.000Z | null | false | 4a8f569bef53f68427ed75f3a23c8715477ae31a | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/lk2/lk3/resolve/main/README.md | ---
license: afl-3.0
---
|
FollishBoi | null | null | null | false | 1 | false | FollishBoi/autotrain-data-tpsmay22 | 2022-05-10T20:51:35.000Z | null | false | 564a409bb4cef7a1d08a3a27982968fa5fc1f4d3 | [] | [] | https://huggingface.co/datasets/FollishBoi/autotrain-data-tpsmay22/resolve/main/README.md | ---
{}
---
# AutoTrain Dataset for project: tpsmay22
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project tpsmay22.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```j... |
HuggingFaceM4 | null | @ARTICLE{Damen2021RESCALING,
title={Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100},
author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria and and Furnari, Antonino
and Ma, Jian and Kazakos, Evangelos and Moltisanti, Davide and Mun... | EPIC-KITCHENS-100 is a large-scale dataset in first-person (egocentric) vision; multi-faceted, audio-visual,
non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities
in the kitchen over multiple days. Annotations are collected using a novel 'Pause-and-Talk' narration inte... | false | 1 | false | HuggingFaceM4/epic_kitchens_100 | 2022-05-12T20:00:33.000Z | null | false | 7fc7add5aa633ef9ccddc0c0ff9dc1dcb8f7d7fe | [] | [
"license:cc-by-nc-4.0"
] | https://huggingface.co/datasets/HuggingFaceM4/epic_kitchens_100/resolve/main/README.md | ---
license: cc-by-nc-4.0
---
|
YYan | null | null | null | false | 1 | false | YYan/csnc_retrieval | 2022-05-11T02:14:57.000Z | null | false | 472a69d24d369d880b94b32c6931f00774c4a0c9 | [] | [
"license:other"
] | https://huggingface.co/datasets/YYan/csnc_retrieval/resolve/main/README.md | ---
license: other
---
|
manirai91 | null | null | null | false | 57 | false | manirai91/yt-nepali-movie-reviews | 2022-05-11T07:08:14.000Z | null | false | ca55bbebc24b96a837d635c0e2fcedd36f7e966d | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/manirai91/yt-nepali-movie-reviews/resolve/main/README.md | ---
license: apache-2.0
---
|
NbAiLab | null | @inproceedings{,
title={},
author={},
booktitle={},
year={2022},
url={https://arxiv.org/abs/}
} | This database was created by Nordic Language Technology for the development of automatic speech recognition and dictation in Norwegian. In this version, the organization of the data have been altered to improve the usefulness of the database.
The acoustic databases described below were developed by the firm Nordisk sp... | false | 1 | false | NbAiLab/NST_hesitate | 2022-05-12T11:07:38.000Z | null | false | bb4129311e369a36730eb2597648b51fb43ea5f7 | [] | [] | https://huggingface.co/datasets/NbAiLab/NST_hesitate/resolve/main/README.md | |
mteb | null | null | null | false | 339 | false | mteb/biorxiv-clustering-s2s | 2022-09-27T19:15:35.000Z | null | false | c0fab014e1bcb8d3a5e31b2088972a1e01547dc1 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/biorxiv-clustering-s2s/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 85 | false | mteb/biorxiv-clustering-p2p | 2022-09-27T19:15:27.000Z | null | false | 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/biorxiv-clustering-p2p/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 303 | false | mteb/medrxiv-clustering-s2s | 2022-09-27T19:10:50.000Z | null | false | 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/medrxiv-clustering-s2s/resolve/main/README.md | ---
language:
- en
--- |
mteb | null | null | null | false | 88 | false | mteb/medrxiv-clustering-p2p | 2022-09-27T19:10:43.000Z | null | false | dcefc037ef84348e49b0d29109e891c01067226b | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/medrxiv-clustering-p2p/resolve/main/README.md | ---
language:
- en
--- |
HuggingFaceM4 | null | @article{sigurdsson2016hollywood,
author = {Gunnar A. Sigurdsson and G{\"u}l Varol and Xiaolong Wang and Ivan Laptev and Ali Farhadi and Abhinav Gupta},
title = {Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding},
journal = {ArXiv e-prints},
eprint = {1604.01753},
year = {... | Charades is dataset composed of 9848 videos of daily indoors activities collected through Amazon Mechanical Turk. 267 different users were presented with a sentence, that includes objects and actions from a fixed vocabulary, and they recorded a video acting out the sentence (like in a game of Charades). The dataset con... | false | 1 | false | HuggingFaceM4/charades | 2022-10-20T21:35:42.000Z | charades | false | a9a9e7a8a2dc35bdb905b3df9d7a44cd60dfa2de | [] | [
"arxiv:1604.01753",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:other"
] | https://huggingface.co/datasets/HuggingFaceM4/charades/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: charades
pretty_name: Charades
tags: []
---
# Dataset Card for Chara... |
RuiqianLi | null | @misc{RuiqianLi,
author = {Ruiqian LI},
title = {The Singlish Speech Dataset},
year = 2022
} | This is a public domain speech dataset consisting of 3579 short audio clips of singlish | false | 1 | false | RuiqianLi/Li_singlish | 2022-05-23T05:34:24.000Z | null | false | 8f40b728cd8f0ab9f8b85674b40f7a252f115497 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/RuiqianLi/Li_singlish/resolve/main/README.md | ---
license: apache-2.0
---
training dataset:
Dataset({
features: ['id', 'audio', 'file', 'text'],
num_rows: 2700
})
{'id': '0',
'audio': {'path': '/root/.cache/huggingface/datasets/downloads/extracted/73016598ed29609d09a2c3c087d4e70e73dc549331efa2117aa6ec012d1ace35/singlish/train/0.wav', 'array': array([-9.1... |
mteb | null | null | null | false | 140 | false | mteb/stackexchange-clustering-p2p | 2022-09-27T19:14:52.000Z | null | false | d88009ab563dd0b16cfaf4436abaf97fa3550cf0 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/stackexchange-clustering-p2p/resolve/main/README.md | ---
language:
- en
--- |
pere | null | null | \\nItalian tweets. | false | 1 | false | pere/italian_tweets_500k | 2022-05-11T14:32:46.000Z | null | false | 19759411acfa124c36137d182b9f0fac22566eee | [] | [] | https://huggingface.co/datasets/pere/italian_tweets_500k/resolve/main/README.md | # Italian Tweets Test Dataset
This is a test dataset that is available for debugging reasons only. It contains errors. Please do not use.
## How to Use
```python
from datasets import load_dataset
data = load_dataset("pere/italian_tweets_1M")
``` |
strombergnlp | null | @inproceedings{derczynski-kjeldsen-2019-bornholmsk,
title = "Bornholmsk Natural Language Processing: Resources and Tools",
author = "Derczynski, Leon and
Kjeldsen, Alex Speed",
booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
month = sep # "{--}" # oct,
ye... | This dataset is parallel text for Bornholmsk and Danish.
For more details, see the paper [Bornholmsk Natural Language Processing: Resources and Tools](https://aclanthology.org/W19-6138/). | false | 1 | false | strombergnlp/bornholmsk_parallel | 2022-07-01T15:45:35.000Z | bornholmsk-parallel | false | 3bc5cfb4ec514264fe2db5615fac9016f7251552 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"language:da-bornholm",
"license:cc-by-4.0",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:translation"
] | https://huggingface.co/datasets/strombergnlp/bornholmsk_parallel/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
- da-bornholm
license:
- cc-by-4.0
multilinguality:
- translation
pretty_name: Bornholmsk/Danish Parallel Texts
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: bo... |
mteb | null | null | null | false | 97 | false | mteb/reddit-clustering-p2p | 2022-09-27T19:13:59.000Z | null | false | 385e3cb46b4cfa89021f56c4380204149d0efe33 | [] | [
"language:en"
] | https://huggingface.co/datasets/mteb/reddit-clustering-p2p/resolve/main/README.md | ---
language:
- en
---
10 sets with the following stats:
1. 91 labels & 15592 samples
2. 64 labels & 79172 samples
3. 38 labels & 1942 samples
4. 11 labels & 13224 samples
5. 64 labels & 92303 samples
6. 87 labels & 28607 samples
7. 10 labels & 69146 samples
8. 48 labels & 67469 samples
9. 64 labels & 29683 samples
1... |
lmqg | null | @inproceedings{ushio-etal-2022-generative,
title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
author = "Ushio, Asahi and
Alva-Manchego, Fernando and
Camacho-Collados, Jose",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Nat... | [SubjQA](https://github.com/megagonlabs/SubjQA) dataset for question generation (QG) task. | false | 1 | false | lmqg/qg_subjqa | 2022-11-05T03:06:47.000Z | null | false | 5362bd42f6b22be6cacfae5787d7988227b7fb2a | [] | [
"arxiv:2210.03992",
"license:cc-by-4.0",
"language:en",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:subjqa",
"task_categories:text-generation",
"task_ids:language-modeling",
"tags:question-generation"
] | https://huggingface.co/datasets/lmqg/qg_subjqa/resolve/main/README.md | ---
license: cc-by-4.0
pretty_name: SubjQA for question generation
language: en
multilinguality: monolingual
size_categories: 10K<n<100K
source_datasets: subjqa
task_categories:
- text-generation
task_ids:
- language-modeling
tags:
- question-generation
---
# Dataset Card for "lmqg/qg_subjqa"
## Dataset Description
-... |
mox | null | null | null | false | 1 | false | mox/german_politicians_twitter_sentiment | 2022-05-11T12:24:56.000Z | null | false | f1c298ec28e0ddaca8952ceeaa8d9a26e2896616 | [] | [] | https://huggingface.co/datasets/mox/german_politicians_twitter_sentiment/resolve/main/README.md | ## Information
This dataset shows 1785 manually annotated tweets from German politicians during the election year 2021 (01.01.2021 - 31.12.2021).
The tweets were annotated by 6 academics which were separated into two different groups. So every group of 3 people annotated the sentiment of ~900 tweets. For every tweet, t... |
LIUM | null | null | null | false | 39 | false | LIUM/tedlium | 2022-10-25T17:38:40.000Z | null | false | 53920e52200cd930d7540683f8bee73264b333ce | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:automatic-speech-recognition"
] | https://huggingface.co/datasets/LIUM/tedlium/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license: []
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: TED-LIUM
---
# Dataset Card for tedlium
## Ta... |
MLRS | null | @inproceedings{BERTu,
title = "Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and {BERT} Models for {M}altese",
author = "Micallef, Kurt and
Gatt, Albert and
Tanti, Marc and
van der Plas, Lonneke and
Borg, Claudia",
... | General Corpora for the Maltese language. | false | 16 | false | MLRS/korpus_malti | 2022-08-30T08:59:09.000Z | null | false | 9952199b44b097e67e007ed0d256066cce7ee8ad | [] | [
"language:mt",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"annotations_creators:no-annotation",
"language_creators:found",
"source_datasets:original",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling"... | https://huggingface.co/datasets/MLRS/korpus_malti/resolve/main/README.md | ---
pretty_name: Korpus Malti
language:
- mt
multilinguality:
- monolingual
size_categories:
- 10M<n<100M
annotations_creators:
- no-annotation
language_creators:
- found
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
license:
- cc-by-... |
elmurod1202 | null | null | null | false | 1 | false | elmurod1202/uzbek-sentiment-analysis | 2022-05-11T13:43:59.000Z | null | false | 91af10276d261f28809abb8ea1b5f2363e66d8fa | [] | [] | https://huggingface.co/datasets/elmurod1202/uzbek-sentiment-analysis/resolve/main/README.md | # uzbek-sentiment-analysis
Sentiment analysis in the Uzbek language and new Datasets of Uzbek App reviews for Sentiment Classification
Feel free to use the dataset and the tools presented in this project, a paper about more details on creation and usage [here](http://www.grupolys.org/biblioteca/KurMatAloGom2019a.pdf).... |
DDSC | null | null | null | false | 31 | false | DDSC/dagw_reddit_filtered_v1.0.0 | 2022-11-06T15:30:56.000Z | null | false | 23ef21cc436a7163f63f1eafee3cde5636c598a0 | [] | [
"arxiv:2005.03521",
"arxiv:2112.11446",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:DDSC/partial-danish-gigaword-no-twitter",
"source_datasets:DDSC/reddit-da",... | https://huggingface.co/datasets/DDSC/dagw_reddit_filtered_v1.0.0/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- DDSC/partial-danish-gigaword-no-twitter
- DDSC/reddit-da
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_na... |
selfishark | null | null | null | false | 1 | false | selfishark/hf-issues-dataset-with-comments | 2022-05-11T15:18:40.000Z | null | false | 70bc074d61b6fd3d933b0c94b4983f01e226b820 | [] | [] | https://huggingface.co/datasets/selfishark/hf-issues-dataset-with-comments/resolve/main/README.md | ### Dataset Summary
GitHub Issues is a dataset consisting of GitHub issues and pull requests associated with the 🤗 Datasets [repository](https://github.com/huggingface/datasets). It is intended for educational purposes and can be used for semantic search or multilabel text classification. The contents of each GitHub ... |
Team-PIXEL | null | null | null | false | 7 | false | Team-PIXEL/rendered-bookcorpus | 2022-08-03T12:03:32.000Z | bookcorpus | false | a17263cdc77c46cecb979e5b997bc23853065c29 | [] | [
"arxiv:1506.06724",
"arxiv:2207.06991",
"arxiv:2105.05241",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:rendered|BookCorpusOpen",
"task_ids:masked-auto-encoding",
... | https://huggingface.co/datasets/Team-PIXEL/rendered-bookcorpus/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: Team-PIXEL/rendered-bookcorpus
size_categories:
- 1M<n<10M
source_datasets:
- rendered|BookCorpusOpen
task_categories:
- masked-auto-encoding
- rendered-language-modelling
t... |
Team-PIXEL | null | null | null | false | 15 | false | Team-PIXEL/rendered-wikipedia-english | 2022-08-02T14:01:21.000Z | null | false | 504638a427b89c21bd99c1d1307e726f746e8231 | [] | [
"arxiv:2207.06991",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-sa-3.0",
"license:gfdl",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"task_ids:masked-auto-encoding",
"task_ids:rendered-language... | https://huggingface.co/datasets/Team-PIXEL/rendered-wikipedia-english/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-3.0
- gfdl
multilinguality:
- monolingual
pretty_name: Team-PIXEL/rendered-wikipedia-english
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- masked-auto-encoding
- rendered-languag... |
yjernite | null | null | null | false | 1 | false | yjernite/DataMeasurementsClusterCache | 2022-05-11T15:37:19.000Z | null | false | fc0fcf14689a97ef73e9090d29b2d89321bb0af8 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/yjernite/DataMeasurementsClusterCache/resolve/main/README.md | ---
license: apache-2.0
---
|
strombergnlp | null | @inproceedings{brucato-etal-2013-recognising,
title = "Recognising and Interpreting Named Temporal Expressions",
author = "Brucato, Matteo and
Derczynski, Leon and
Llorens, Hector and
Bontcheva, Kalina and
Jensen, Christian S.",
booktitle = "Proceedings of the International Confe... | This is a dataset annotated for _named temporal expression_ chunks.
The
commonest temporal expressions typically
contain date and time words, like April or
hours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is
a class of expressions that are less typ... | false | 1 | false | strombergnlp/named_timexes | 2022-07-01T15:44:08.000Z | null | false | 524f2a4c3f16309bbb070c29823c2e52599247a9 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:token-classification"
] | https://huggingface.co/datasets/strombergnlp/named_timexes/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Named Temporal Expressions dataset
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids: []
---
# Dataset Card for... |
strombergnlp | null | \ | \ | false | 16 | false | strombergnlp/itu_faroese_danish | 2022-07-01T15:43:48.000Z | null | false | b656a4039a247e7c063c53c9b7bf354807944c5b | [] | [
"arxiv:2206.08727",
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"language:fo",
"license:cc-by-4.0",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:translation"
] | https://huggingface.co/datasets/strombergnlp/itu_faroese_danish/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
- fo
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: ITU Faroese Danish parallel text
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
---
## Table of Contents
- ... |
jontooy | null | null | null | false | 1 | false | jontooy/Flickr8k-Image-Features | 2022-06-06T18:25:44.000Z | null | false | a78a6d10920ec12d9ec69564eb3b6ce0753b5977 | [] | [
"language:ar",
"datasets:flickr8k"
] | https://huggingface.co/datasets/jontooy/Flickr8k-Image-Features/resolve/main/README.md | ---
language: ar
datasets: flickr8k
---
# Flickr8k Image Features
Flickr8k image features are extracted using the ResNeXt-152 C4 architecture ([found here](https://github.com/microsoft/scene_graph_benchmark)) and can be used as input for the [OSCAR](https://github.com/microsoft/Oscar) learning method. Arabic captions... |
najoungkim | null | null | null | false | 1 | false | najoungkim/edge_probing_dep_ewt_line_by_line | 2022-05-11T19:40:17.000Z | null | false | 27938ee8b5d858b0f98a08d773f3dec398370e56 | [] | [] | https://huggingface.co/datasets/najoungkim/edge_probing_dep_ewt_line_by_line/resolve/main/README.md | |
domenicrosati | null | null | null | false | 14 | false | domenicrosati/TruthfulQA | 2022-07-01T15:41:54.000Z | null | false | 6a037f8d9403bbf12fb4cf6d0e91956df6a64e50 | [] | [
"arxiv:2109.07958",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:ope... | https://huggingface.co/datasets/domenicrosati/TruthfulQA/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: TruthfulQA
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
- open-domain-qa
- closed-dom... |
nateraw | null | null | null | false | 1 | false | nateraw/hf-hub-walkthrough-assets | 2022-05-12T04:40:07.000Z | null | false | 90882e4382225a75dd66e0bcae1de2c5926f2fbd | [] | [
"license:mit"
] | https://huggingface.co/datasets/nateraw/hf-hub-walkthrough-assets/resolve/main/README.md | ---
license: mit
---
|
ncats | null | *REDO*
@inproceedings{wang2019crossweigh,
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Proc... | **REWRITE*
EpiSet4NER-2 is a dataset generated from 620 rare disease abstracts labeled using statistical and rule-base methods.
For more details see *INSERT PAPER* and https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard | false | 2 | false | ncats/EpiSet4NER-v2 | 2022-09-20T15:25:56.000Z | null | false | c2745ea380ea553b9d0d146d1e0869d29da6a73a | [] | [
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language:en",
"language_creators:found",
"language_creators:expert-generated",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"tags:epidemiology",
"tags:r... | https://huggingface.co/datasets/ncats/EpiSet4NER-v2/resolve/main/README.md | ---
annotations_creators:
- machine-generated
- expert-generated
language:
- en
language_creators:
- found
- expert-generated
license:
- other
multilinguality:
- monolingual
pretty_name: EpiSet4NER-v2
size_categories:
- 100K<n<1M
source_datasets:
- original
tags:
- epidemiology
- rare disease
- named entity recognition... |
strombergnlp | null | @inproceedings{gorrell-etal-2019-semeval,
title = "{S}em{E}val-2019 Task 7: {R}umour{E}val, Determining Rumour Veracity and Support for Rumours",
author = "Gorrell, Genevieve and
Kochkina, Elena and
Liakata, Maria and
Aker, Ahmet and
Zubiaga, Arkaitz and
Bontcheva, Kalina and... |
Stance prediction task in English. The goal is to predict whether a given reply to a claim either supports, denies, questions, or simply comments on the claim. Ran as a SemEval task in 2019. | false | 1 | false | strombergnlp/rumoureval_2019 | 2022-10-25T21:43:58.000Z | null | false | c9c0c7279d591d2fa4d692501d85f4e46d4b0572 | [] | [
"arxiv:1809.06683",
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:text-classification",
"task_ids:fact-checking",
"tags:stance-detection"
] | https://huggingface.co/datasets/strombergnlp/rumoureval_2019/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets: []
task_categories:
- text-classification
task_ids:
- fact-checking
pretty_name: RumourEval 2019
tags:
- stance-detection
---
# Dataset... |
met | null | null | null | false | 1 | false | met/customAmhTig | 2022-05-12T11:56:15.000Z | null | false | 959a1d865980e5b78990da0a70df30c1ddb855e9 | [] | [] | https://huggingface.co/datasets/met/customAmhTig/resolve/main/README.md | |
beery | null | null | null | false | 1 | false | beery/Dutch-SQuAD | 2022-05-12T12:47:21.000Z | null | false | 49f71f31afcb99f777973bb5916cde35ad6aaba1 | [] | [] | https://huggingface.co/datasets/beery/Dutch-SQuAD/resolve/main/README.md | <h1>Dutch SQuAD v2.0</h1>
Machine translated version of the SQuAD v2.0 dataset in Dutch.
<em>Note:</em> This dataset is machine translated. |
Roh | null | @inproceedings{Zandie2021RyanSpeechAC,
title={RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis},
author={Rohola Zandie and Mohammad H. Mahoor and Julia Madsen and Eshrat S. Emamian},
booktitle={Interspeech},
year={2021}
} | RyanSpeech is a new speech corpus for research on automated text-to-speech (TTS) systems.
Publicly available TTS corpora are often noisy, recorded with multiple speakers, or do not have quality male speech data.
In order to meet the need for a high-quality, publicly available male speech corpus within the field of spe... | false | 14 | false | Roh/ryanspeech | 2022-10-23T05:48:41.000Z | null | false | cd9341299b39a015a5528085f8b8fd7d43ddb601 | [] | [
"arxiv:2106.08468",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:cc-by-nc-4.0",
"multilinguality:monolingual",
"source_datasets:original",
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification"
] | https://huggingface.co/datasets/Roh/ryanspeech/resolve/main/README.md | ---
pretty_name: RyanSpeech
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- audio-classification
- speech-synthesis
---
# Dataset Card for l... |
thomagram | null | null | null | false | 1 | false | thomagram/StyleNeRF_Datasets | 2022-05-13T17:57:32.000Z | null | false | f0f195f86e8caddeec352dc945e2e6f01dd9e00a | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/thomagram/StyleNeRF_Datasets/resolve/main/README.md | ---
license: cc-by-4.0
---
This is the zipped datasets for training StyleNeRF models on AFHQ, MetFaces and Compcars |
HuggingFaceM4 | null | @inproceedings{goyal2017something,
title={The" something something" video database for learning and evaluating visual common sense},
author={Goyal, Raghav and Ebrahimi Kahou, Samira and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos... | The Something-Something dataset (version 2) is a collection of 220,847 labeled video clips of humans performing pre-defined, basic actions with everyday objects. It is designed to train machine learning models in fine-grained understanding of human hand gestures like putting something into something, turning something ... | false | 1 | false | HuggingFaceM4/something_something_v2 | 2022-10-20T21:35:22.000Z | something-something | false | 130db220f301e31219875231983a9827c8370aa1 | [] | [
"arxiv:1706.04261",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:other"
] | https://huggingface.co/datasets/HuggingFaceM4/something_something_v2/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: something-something
pretty_name: Something Something v2
tags: []
---... |
SetFit | null | null | null | false | 1 | false | SetFit/toxic_conversations_50k | 2022-05-13T07:56:41.000Z | null | false | ef2009a5444b8a278c4d0782bcc549a01fd0163d | [] | [] | https://huggingface.co/datasets/SetFit/toxic_conversations_50k/resolve/main/README.md | # Toxic Conversation
This is a version of the [Jigsaw Unintended Bias in Toxicity Classification dataset](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/overview). It contains comments from the Civil Comments platform together with annotations if the comment is toxic or not.
This datase... |
pensieves | null | @inproceedings{Lang95,
author = {Ken Lang},
title = {Newsweeder: Learning to filter netnews}
year = {1995}
booktitle = {Proceedings of the Twelfth International Conference on Machine Learning}
pages = {331-339}
} | null | false | 1 | false | pensieves/newsgroups | 2022-05-13T15:08:13.000Z | null | false | a317f23efaef8b12a6744c0cf6634bc6093aabad | [] | [
"license:mit"
] | https://huggingface.co/datasets/pensieves/newsgroups/resolve/main/README.md | ---
license: mit
pretty_name: 20-Newsgroups
---
# Dataset Card for "20-Newsgroups" |
Leyo | null | @inproceedings{krishna2017dense,
title={Dense-Captioning Events in Videos},
author={Krishna, Ranjay and Hata, Kenji and Ren, Frederic and Fei-Fei, Li and Niebles, Juan Carlos},
booktitle={International Conference on Computer Vision (ICCV)},
year={2017}
} | The ActivityNet Captions dataset connects videos to a series of temporally annotated sentence descriptions.
Each sentence covers an unique segment of the video, describing multiple events that occur. These events
may occur over very long or short periods of time and are not limited in any capacity, allowing them to
co... | false | 1 | false | Leyo/ActivityNet_Captions | 2022-07-01T15:57:56.000Z | null | false | 780b46b0862f109dbaf63bc9d3779a9ca711506c | [] | [
"arxiv:1705.00754",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:10k<n<100K",
"source_datasets:original",
"task_ids:closed-domain-qa"
] | https://huggingface.co/datasets/Leyo/ActivityNet_Captions/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
license:
- other
multilinguality:
- monolingual
pretty_name: ActivityNet Captions
size_categories:
- 10k<n<100K
source_datasets:
- original
task_categories:
- video-captionning
task_ids:
- closed-domain-qa
---
# Dataset Card... |
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