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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
khalidalt | null | @book{book,
author = {Misra, Rishabh and Grover, Jigyasa},
year = {2021},
month = {01},
pages = {},
title = {Sculpting Data for ML: The first act of Machine Learning},
isbn = {978-0-578-83125-1}
}
@dataset{dataset,
author = {Misra, Rishabh},
year = {2018},
month = {06},
pages = {},
title = {News ... | A dataset of approximately 200K news headlines from the year 2012 to 2018 collected from HuffPost. | false | 112 | false | khalidalt/HuffPost | 2022-04-29T05:13:38.000Z | null | false | e45f5ed7b3c1309b54a4b62e9003b958a1e27b20 | [] | [
"license:cc0-1.0"
] | https://huggingface.co/datasets/khalidalt/HuffPost/resolve/main/README.md | ---
license: cc0-1.0
---
# Dataset Card for HuffPost
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Str... |
blinoff | null | @article{blinov2013research,
title={Research of lexical approach and machine learning methods for sentiment analysis},
author={Blinov, PD and Klekovkina, Maria and Kotelnikov, Eugeny and Pestov, Oleg},
journal={Computational Linguistics and Intellectual Technologies},
volume={2},
number={12},
pages={48--58}... | null | false | 3 | false | blinoff/kinopoisk | 2022-10-23T16:51:58.000Z | null | false | 726a7cb5d4eab90c9035bd55b7bde3018c3bd06b | [] | [
"language:ru",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/blinoff/kinopoisk/resolve/main/README.md | ---
language:
- ru
multilinguality:
- monolingual
pretty_name: Kinopoisk
size_categories:
- 10K<n<100K
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
### Dataset Summary
Kinopoisk movie reviews dataset (TOP250 & BOTTOM100 rank lists).
In total it contains 36,591 reviews from July 200... |
hady | null | null | null | false | 2 | false | hady/kurdiabadulhady | 2022-04-26T10:31:42.000Z | null | false | 485c67807d91e92466571c44279eacd217042b76 | [] | [] | https://huggingface.co/datasets/hady/kurdiabadulhady/resolve/main/README.md | |
sxu | null | null | null | false | 2 | false | sxu/CANLI | 2022-10-11T12:53:46.000Z | null | false | 1ef455d5237f4d2c61719194e015a2d41e77073e | [] | [
"license:afl-3.0",
"annotations_creators:expert-generated",
"language:cn",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K"
] | https://huggingface.co/datasets/sxu/CANLI/resolve/main/README.md | ---
license: afl-3.0
annotations_creators:
- expert-generated
language:
- cn
language_creators:
- expert-generated
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
---
# Dataset Card for CANLI
### Dataset Summary
[CANLI: The Chinese Causative-Passive Homonymy Disambiguation: an Adversarial Dataset for NLI... |
ENM | null | null | null | false | 1 | false | ENM/dataset-prueba | 2022-10-25T10:12:20.000Z | null | false | 7455d89e3da5e569b49d6ae1005fd52e89eb5087 | [] | [
"language:en"
] | https://huggingface.co/datasets/ENM/dataset-prueba/resolve/main/README.md | ---
language:
- en
pretty_name: ScientificPapers
---
# Dataset Card for "scientific_papers"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structu... |
SocialGrep | null | null | A comprehensive dataset of Reddit's NFT discussion. | false | 2 | false | SocialGrep/the-reddit-nft-dataset | 2022-07-01T17:52:49.000Z | null | false | 5fc63ea7788cd5b4edb6aeba801cdc7083cf07e9 | [] | [
"annotations_creators:lexyr",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original"
] | https://huggingface.co/datasets/SocialGrep/the-reddit-nft-dataset/resolve/main/README.md | ---
annotations_creators:
- lexyr
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
paperswithcode_id: null
---
# Dataset Card for the-reddit-nft-dataset
## Table of Contents
- [Dataset Description](#dataset-des... |
aakanksha | null | @inproceedings{nivre-etal-2020-universal,
title = "{U}niversal {D}ependencies v2: An Evergrowing Multilingual Treebank Collection",
author = "Nivre, Joakim and
de Marneffe, Marie-Catherine and
Ginter, Filip and
Haji{\v{c}}, Jan and
Manning, Christopher D. and
Pyysalo, Sampo a... | Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework. The annotation consists in a linguistically motivated word segmentation; a morphological layer comprising lemmas, universal part-of-speech t... | false | 1 | false | aakanksha/udpos | 2022-04-27T19:21:57.000Z | null | false | 739825f9dbb674e44f71019730d403f626aac4be | [] | [] | https://huggingface.co/datasets/aakanksha/udpos/resolve/main/README.md | POS tagging on the Universal Dependencies dataset
|
fut501 | null | null | null | false | 1 | false | fut501/ds1 | 2022-05-10T01:23:18.000Z | null | false | a4ce90c2d3cd20978a678e6a108119716f235310 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/fut501/ds1/resolve/main/README.md | ---
license: apache-2.0
---
|
zaraTahhhir | null | null | null | false | 1 | false | zaraTahhhir/urduprusdataset | 2022-04-27T07:18:05.000Z | null | false | eb634bef6c528fb9df2acf63b56fdf82f0d41684 | [] | [
"license:mit"
] | https://huggingface.co/datasets/zaraTahhhir/urduprusdataset/resolve/main/README.md | ---
license: mit
---
|
Zaratahir123 | null | null | null | false | 1 | false | Zaratahir123/urduprusdataset | 2022-04-27T07:52:02.000Z | null | false | c340865212e37f0f37823ffb6cc4ed1c8a960c0e | [] | [
"license:mit"
] | https://huggingface.co/datasets/Zaratahir123/urduprusdataset/resolve/main/README.md | ---
license: mit
---
|
junliang | null | null | null | false | 1 | false | junliang/symptom | 2022-05-11T12:57:22.000Z | null | false | 578d877dd50601749b406d53805a4bd332b63091 | [] | [] | https://huggingface.co/datasets/junliang/symptom/resolve/main/README.md | annotations_creators:
- found
language_creators:
- found
languages:
- zh
licenses:
- other-my-license
multilinguality:
- monolingual
pretty_name: symptom
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- word-sense-disambiguation |
janck | null | null | null | false | 1 | false | janck/bigscience-lama | 2022-10-21T08:16:23.000Z | lama | false | a3fc132b1a1b550f82e0801e9ded2ae475b659ea | [] | [
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:fact-checking-retrieval",
"task_ids:tex... | https://huggingface.co/datasets/janck/bigscience-lama/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
trex:
- 1M<n<10M
task_categories:
- text-retrieval
- text-classification
task_ids:
- fact-checking-retrieval
- text-scoring
paperswithcode_id: lama... |
Zaratahir123 | null | null | null | false | 1 | false | Zaratahir123/groupData | 2022-04-28T16:33:38.000Z | null | false | 60f3c3a4a3340dd7f3e8e7895e064c4790d38239 | [] | [
"license:mit"
] | https://huggingface.co/datasets/Zaratahir123/groupData/resolve/main/README.md | ---
license: mit
---
|
Zaratahir123 | null | null | null | false | 1 | false | Zaratahir123/test | 2022-04-27T10:45:17.000Z | null | false | b3413a70bbc5e925ec9a604338eb4ffab031b9a0 | [] | [
"license:mit"
] | https://huggingface.co/datasets/Zaratahir123/test/resolve/main/README.md | ---
license: mit
---
|
shreyasmani | null | null | null | false | 1 | false | shreyasmani/whrdata2021 | 2022-04-27T11:11:59.000Z | null | false | d3f7c9ee72dd91ddcb840a8585d248deffa0e5a0 | [] | [
"license:other"
] | https://huggingface.co/datasets/shreyasmani/whrdata2021/resolve/main/README.md | ---
license: other
---
|
PolyAI | null | @inproceedings{Casanueva2020,
author = {I{\~{n}}igo Casanueva and Tadas Temcinas and Daniela Gerz and Matthew Henderson and Ivan Vulic},
title = {Efficient Intent Detection with Dual Sentence Encoders},
year = {2020},
month = {mar},
note = {Data available at https://gi... | BANKING77 dataset provides a very fine-grained set of intents in a banking domain.
It comprises 13,083 customer service queries labeled with 77 intents.
It focuses on fine-grained single-domain intent detection. | false | 20 | false | PolyAI/banking77 | 2022-10-25T10:12:22.000Z | null | false | 96a234bd25c04939c4a79213eb764ae90e4d0d81 | [] | [
"arxiv:2003.04807",
"annotations_creators:expert-generated",
"extended:original",
"language_creators:expert-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:in... | https://huggingface.co/datasets/PolyAI/banking77/resolve/main/README.md | ---
annotations_creators:
- expert-generated
extended:
- original
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- intent-classification
- multi-class-clas... |
EAST | null | null | null | false | 1 | false | EAST/autotrain-data-Rule | 2022-10-25T10:12:41.000Z | null | false | e504e76976d00dbe5d2ee3945bf6d42c65e2bd1d | [] | [
"language:zh",
"task_categories:text-classification"
] | https://huggingface.co/datasets/EAST/autotrain-data-Rule/resolve/main/README.md | ---
language:
- zh
task_categories:
- text-classification
---
# AutoTrain Dataset for project: Rule
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project Rule.
### Languages
The BCP-47 code for the dataset's language is zh.
## Dataset Structure
### Data Instances
A sample ... |
osyvokon | null | null | null | false | 1 | false | osyvokon/pavlick-formality-scores | 2022-10-25T10:12:43.000Z | null | false | 90e53b922d4e6574623b352a4be4ae4ae6cdff61 | [] | [
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en-US",
"license:cc-by-3.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:text-scoring"
] | https://huggingface.co/datasets/osyvokon/pavlick-formality-scores/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en-US
license:
- cc-by-3.0
multilinguality:
- monolingual
pretty_name: 'Sentence-level formality annotations for news, blogs, email and QA forums.
Published in "An Empirical Analysis of Formality in Online Communication" (Pavlick
and ... |
NLPC-UOM | null | null | null | false | 1 | false | NLPC-UOM/Writing-style-classification | 2022-10-25T10:12:46.000Z | null | false | 2d04a4fde26d92fbed2ae7604677736e6b901a4d | [] | [
"language_creators:crowdsourced",
"language:si",
"license:mit",
"multilinguality:monolingual",
"task_categories:text-classification"
] | https://huggingface.co/datasets/NLPC-UOM/Writing-style-classification/resolve/main/README.md | ---
annotations_creators: []
language_creators:
- crowdsourced
language:
- si
license:
- mit
multilinguality:
- monolingual
pretty_name: sinhala-writing-style-classification
size_categories: []
source_datasets: []
task_categories:
- text-classification
task_ids: []
---
This file contains news texts (sentences) belongin... |
bigscience-catalogue-data | null | """
# TODO: Add description of the dataset here
# You can copy an official description
_DESCRIPTION = | This is a preliminary version of the bias SHADES dataset for evaluating LMs for social biases. | false | 65 | true | bigscience-catalogue-data/bias-shades | 2022-05-01T15:18:02.000Z | null | false | e220d18727665580a083db6162dd78f9e0f61438 | [] | [
"arxiv:2010.00133",
"license:cc-by-sa-4.0"
] | https://huggingface.co/datasets/bigscience-catalogue-data/bias-shades/resolve/main/README.md | |
mrm8488 | null | null | null | false | 211 | false | mrm8488/ImageNet1K-val | 2022-04-27T19:16:51.000Z | null | false | f004a913f9170e5ff39e63f6172ee3ae918197c9 | [] | [] | https://huggingface.co/datasets/mrm8488/ImageNet1K-val/resolve/main/README.md | mapping:
```
n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
n01491361 tiger shark, Galeocerdo cuvieri
n01494475 hammerhead, hammerhead shark
n01496331 electric ray, crampfish, numbfish, torpedo
n01498041 st... |
mrm8488 | null | null | null | false | 28 | false | mrm8488/ImageNet1K-train | 2022-04-28T11:06:11.000Z | null | false | 006c4bc87abe217e728bbd7bfcd76f9f828c11e2 | [] | [] | https://huggingface.co/datasets/mrm8488/ImageNet1K-train/resolve/main/README.md | mapping:
```
n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias
n01491361 tiger shark, Galeocerdo cuvieri
n01494475 hammerhead, hammerhead shark
n01496331 electric ray, crampfish, numbfish, torpedo
n01498041 st... |
AmazonScience | null | @misc{fitzgerald2022massive,
title={MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages},
author={Jack FitzGerald and Christopher Hench and Charith Peris and Scott Mackie and Kay Rottmann and Ana Sanchez and Aaron Nash and... | MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations
for the Natural Language Understanding tasks of intent prediction and slot annotation.
Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing
the SLURP dataset, composed... | false | 2,014 | false | AmazonScience/massive | 2022-11-16T15:44:51.000Z | massive | false | ff6bd8e4b27c3543e4f8fe2108f32bb95a6f8740 | [] | [
"arxiv:2204.08582",
"annotations_creators:expert-generated",
"language_creators:found",
"license:cc-by-4.0",
"multilinguality:af-ZA",
"multilinguality:am-ET",
"multilinguality:ar-SA",
"multilinguality:az-AZ",
"multilinguality:bn-BD",
"multilinguality:ca-ES",
"multilinguality:cy-GB",
"multiling... | https://huggingface.co/datasets/AmazonScience/massive/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- af-ZA
- am-ET
- ar-SA
- az-AZ
- bn-BD
- ca-ES
- cy-GB
- da-DK
- de-DE
- el-GR
- en-US
- es-ES
- fa-IR
- fi-FI
- fr-FR
- he-IL
- hi-IN
- hu-HU
- hy-AM
- id-ID
- is-IS
- it-IT
- ja-JP
- jv-ID
- ka-GE
- km-KH
- ... |
odellus | null | null | null | false | 1 | false | odellus/beerqa | 2022-04-27T21:31:18.000Z | null | false | 91d0a0d7cccfff341a3a2806aede1988e9b907c0 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/odellus/beerqa/resolve/main/README.md | ---
license: cc-by-4.0
---
|
codeparrot | null | null | null | false | 19 | false | codeparrot/codeparrot-valid-more-filtering | 2022-06-21T17:56:02.000Z | null | false | 3a14d4d277b7ad97c668740aa9d0affadbf3fe8d | [] | [] | https://huggingface.co/datasets/codeparrot/codeparrot-valid-more-filtering/resolve/main/README.md | # CodeParrot 🦜 Dataset Cleaned and filtered (validation)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the validation split [codeparrot-clean-valid](https://huggingface.co/datasets/codeparrot/codeparrot-clean-valid) of [codeparrot-clean](https://huggingface.co/dataset... |
codeparrot | null | null | null | false | 7 | false | codeparrot/codeparrot-train-more-filtering | 2022-06-21T17:54:51.000Z | null | false | f6e726786732dbdb82a970091bb6d7ffe2251c80 | [] | [] | https://huggingface.co/datasets/codeparrot/codeparrot-train-more-filtering/resolve/main/README.md | # CodeParrot 🦜 Dataset Cleaned and filtered (train)
## Dataset Description
A dataset of Python files from Github. It is a more filtered version of the train split [codeparrot-clean-train](https://huggingface.co/datasets/codeparrot/codeparrot-clean-train) of [codeparrot-clean](https://huggingface.co/datasets/codeparr... |
mathigatti | null | null | null | false | 5 | false | mathigatti/spanish_imdb_synopsis | 2022-10-25T10:12:53.000Z | null | false | c8e9269cd96a600bb340ee83ae45f46a02787a12 | [] | [
"annotations_creators:no-annotation",
"language:es",
"license:apache-2.0",
"multilinguality:monolingual",
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:text2text-generation"
] | https://huggingface.co/datasets/mathigatti/spanish_imdb_synopsis/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language:
- es
license:
- apache-2.0
multilinguality:
- monolingual
task_categories:
- summarization
- text-generation
- text2text-generation
---
# Dataset Card for Spanish IMDb Synopsis
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#d... |
TalTechNLP | null | null | null | false | 7 | false | TalTechNLP/VoxLingua107 | 2022-05-05T10:52:37.000Z | null | false | 8ef331f75ebced42eceb7c5f53c47a3dafd8ef20 | [] | [
"license:cc-by-nc-4.0"
] | https://huggingface.co/datasets/TalTechNLP/VoxLingua107/resolve/main/README.md | ---
license: cc-by-nc-4.0
---
hello
|
strombergnlp | null | @inproceedings{norregaard-derczynski-2021-danfever,
title = "{D}an{FEVER}: claim verification dataset for {D}anish",
author = "N{\o}rregaard, Jeppe and
Derczynski, Leon",
booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)",
month = may # " 31--2 " # jun... | \ | false | 1 | false | strombergnlp/danfever | 2022-10-25T21:42:40.000Z | danfever | false | 5d01e3f6a661d48e127ab5d7e3aaa0dc8331438a | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:natural-language-inference",
"... | https://huggingface.co/datasets/strombergnlp/danfever/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
- natural-language-inference
paperswithcode_id: danfever
pre... |
JbIPS | null | null | null | false | 1 | false | JbIPS/stanford-dogs | 2022-04-28T09:56:39.000Z | null | false | dad84ecc9f47c2d0701018018903a158bad71867 | [] | [
"license:mit"
] | https://huggingface.co/datasets/JbIPS/stanford-dogs/resolve/main/README.md | ---
license: mit
---
|
strombergnlp | null | @inproceedings{derczynski2016broad,
title={Broad twitter corpus: A diverse named entity recognition resource},
author={Derczynski, Leon and Bontcheva, Kalina and Roberts, Ian},
booktitle={Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
pages={1169--... | This is the Broad Twitter corpus, a dataset of tweets collected over stratified times, places and social uses.
The goal is to represent a broad range of activities, giving a dataset more representative of the language used
in this hardest of social media formats to process. Further, the BTC is annotated for named ent... | false | 213 | false | strombergnlp/broad_twitter_corpus | 2022-07-01T15:46:36.000Z | broad-twitter-corpus | false | d766cb8a7497d0d507d81f5f681a8d58deedf495 | [] | [
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/strombergnlp/broad_twitter_corpus/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: broad-twitter-corpus
pretty_name... |
strombergnlp | null | @article{derczynski2015analysis,
title={Analysis of named entity recognition and linking for tweets},
author={Derczynski, Leon and Maynard, Diana and Rizzo, Giuseppe and Van Erp, Marieke and Gorrell, Genevieve and Troncy, Rapha{\"e}l and Petrak, Johann and Bontcheva, Kalina},
journal={Information Processing \& Ma... | This data is for the task of named entity recognition and linking/disambiguation over tweets. It comprises
the addition of an entity URI layer on top of an NER-annotated tweet dataset. The task is to detect entities
and then provide a correct link to them in DBpedia, thus disambiguating otherwise ambiguous entity surfa... | false | 5 | false | strombergnlp/ipm_nel | 2022-10-25T21:41:26.000Z | ipm-nel | false | cc150b1a28983f4796ab486f6e1ef1d1047e523a | [] | [
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"tags:named-entity-linking"
] | https://huggingface.co/datasets/strombergnlp/ipm_nel/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets: []
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: ipm-nel
pretty_name: IPM NEL (Derczynski)... |
strombergnlp | null | @inproceedings{lillie-etal-2019-joint,
title = "Joint Rumour Stance and Veracity Prediction",
author = "Lillie, Anders Edelbo and
Middelboe, Emil Refsgaard and
Derczynski, Leon",
booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
month = sep # "{--}" # oc... | This dataset presents a series of stories on Reddit and the conversation around
them, annotated for stance. Stories are also annotated for veracity.
For more details see https://aclanthology.org/W19-6122/ | false | 1 | false | strombergnlp/dkstance | 2022-10-25T21:45:42.000Z | dast | false | 1075212523ac84e51b0fe6bc41fef4cd2bf695cc | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:fact-checking",
"extra_gated_prompt:Warning: the data in t... | https://huggingface.co/datasets/strombergnlp/dkstance/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
paperswithcode_id: dast
pretty_name: DAST
extra_gated_prompt... |
strombergnlp | null | @inproceedings{lehmann2019political,
title={Political Stance in Danish},
author={Lehmann, Rasmus and Derczynski, Leon},
booktitle={Proceedings of the 22nd Nordic Conference on Computational Linguistics},
pages={197--207},
year={2019}
} | Political stance in Danish. Examples represent statements by
politicians and are annotated for, against, or neutral to a given topic/article. | false | 1 | false | strombergnlp/polstance | 2022-10-25T21:42:18.000Z | polstance | false | d617a5df1b7ec95b1b290926e2d1f20c55d2c0b9 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-analysis",
"tags:stance-detection"
] | https://huggingface.co/datasets/strombergnlp/polstance/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-analysis
paperswithcode_id: polstance
pretty_name: Political Stance ... |
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 corpus introduces language processing resources and tools for Bornholmsk, a language spoken on the island of Bornholm, with roots in Danish and closely related to Scanian.
Sammenfattnijng på borrijnholmst: Dæjnna artikkelijn introduserer natursprågsresurser å varktoi for borrijnholmst, ed språg a dær snakkes på ... | false | 1 | false | strombergnlp/bornholmsk | 2022-10-25T21:40:56.000Z | null | false | 8ad62edaaf487414e527d3f59edd6f6b52778b41 | [] | [
"annotations_creators:no-annotation",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:text-generation",
"task_ids:language-modeling",
"language_bcp47:da",
"language_bcp47:da-bo... | https://huggingface.co/datasets/strombergnlp/bornholmsk/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
language_bcp47:
- da
- da-bornholm
---
## Table of Contents
... |
strombergnlp | null | @inproceedings{derczynski2013twitter,
title={Twitter part-of-speech tagging for all: Overcoming sparse and noisy data},
author={Derczynski, Leon and Ritter, Alan and Clark, Sam and Bontcheva, Kalina},
booktitle={Proceedings of the international conference recent advances in natural language processing ranlp 2013}... | 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 data is the vote-constrained bootstrapped data generate to support state-of-the-art results.
The data is about 1.5 million English tweets annotated f... | false | 4 | false | strombergnlp/twitter_pos_vcb | 2022-10-25T21:42:56.000Z | twitter-pos-vcb | false | 12ff587afc996106440872be6b3656218fad0e82 | [] | [
"annotations_creators:machine-generated",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:part-of-speech"
] | https://huggingface.co/datasets/strombergnlp/twitter_pos_vcb/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- part-of-speech
paperswithcode_id: twitter-pos-vcb
pretty_name: Twitter P... |
strombergnlp | null | @inproceedings{dlamini_zulu_stance,
title={Bridging the Domain Gap for Stance Detection for the Zulu language},
author={Dlamini, Gcinizwe and Bekkouch, Imad Eddine Ibrahim and Khan, Adil and Derczynski, Leon},
booktitle={Proceedings of IEEE IntelliSys},
year={2022}
} | This is a stance detection dataset in the Zulu language. The data is translated to Zulu by Zulu native speakers, from English source texts.
Misinformation has become a major concern in recent last years given its
spread across our information sources. In the past years, many NLP tasks have
been introduced in this are... | false | 1 | false | strombergnlp/zulu_stance | 2022-10-25T21:46:14.000Z | zulu-stance | false | 9cd7629e8632e2bf2185a7ae2309b8333248d57e | [] | [
"arxiv:2205.03153",
"annotations_creators:expert-generated",
"language_creators:found",
"language:zu",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:sentiment-... | https://huggingface.co/datasets/strombergnlp/zulu_stance/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- zu
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
- sentiment-classification
paperswithcode_id: zulu-stance
pr... |
Elfsong | null | null | null | false | 1 | false | Elfsong/clef_data | 2022-08-29T05:41:54.000Z | null | false | 00e360ccbfa82f47287311387af1011f28f7e667 | [] | [] | https://huggingface.co/datasets/Elfsong/clef_data/resolve/main/README.md | You should know how to use it:)
Just in case, you can email me [mingzhe at nus.edu.sg] if you need any help. |
tomasmcz | null | null | null | false | 1 | false | tomasmcz/word2vec_analogy | 2022-04-28T14:07:56.000Z | null | false | 3fc0666c45d46d03a9bcd43f5e887dda2727328e | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/tomasmcz/word2vec_analogy/resolve/main/README.md | ---
license: apache-2.0
---
Adapted from https://github.com/nicholas-leonard/word2vec |
Zaratahir123 | null | null | null | false | 1 | false | Zaratahir123/23100065 | 2022-04-28T16:05:20.000Z | null | false | d4b9a7de7eeea7fe4b1e43186b2e9d2b014779b8 | [] | [
"license:mit"
] | https://huggingface.co/datasets/Zaratahir123/23100065/resolve/main/README.md | ---
license: mit
---
|
BigScienceBiasEval | null | """
# TODO: Add description of the dataset here
# You can copy an official description
_DESCRIPTION = | This is a preliminary version of the bias SHADES dataset for evaluating LMs for social biases. | false | 102 | false | BigScienceBiasEval/bias-shades | 2022-10-03T13:49:04.000Z | null | false | 788a707f7a58202e1a9dbd012ff986c935d4d113 | [] | [
"license:cc-by-sa-4.0"
] | https://huggingface.co/datasets/BigScienceBiasEval/bias-shades/resolve/main/README.md | ---
license: cc-by-sa-4.0
---
Possibly a placeholder dataset for the original here: https://huggingface.co/datasets/bigscience-catalogue-data/bias-shades
# Data Statement for SHADES
> **How to use this document:**
> Fill in each section according to the instructions. Give as much detail as you can, but there's no ne... |
smallv0221 | null | null | null | false | 1 | false | smallv0221/dd | 2022-04-29T04:34:50.000Z | null | false | a4e4877f5ae4a8df754d2da61fd9b4f71dc3b6c4 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/smallv0221/dd/resolve/main/README.md | ---
license: apache-2.0
---
|
gusevski | null | null | null | false | 4 | false | gusevski/factrueval2016 | 2022-04-29T20:34:48.000Z | null | false | 96349b9bd7536aac67f892f5cf36197cd49ea722 | [] | [
"arxiv:2005.00614"
] | https://huggingface.co/datasets/gusevski/factrueval2016/resolve/main/README.md | # Dataset Card for FactRuEval-2016
## Dataset Description
- **Point of Contact:** [Guskov Sergey](https://gusevski.com)
### Dataset Summary
Evaluation of [Named Entity Recognition](https://www.dialog-21.ru/media/3430/starostinaetal.pdf) and Fact Extraction Systems for Russian.
### Supported Tasks and Leaderboards
... |
Mim | null | null | null | false | 1 | false | Mim/autotrain-data-procell-expert | 2022-04-29T08:27:03.000Z | null | false | 30d1fddbdb897932513e5974736b46c6fe6b6ceb | [] | [
"task_categories:text-classification"
] | https://huggingface.co/datasets/Mim/autotrain-data-procell-expert/resolve/main/README.md | ---
task_categories:
- text-classification
---
# AutoTrain Dataset for project: procell-expert
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project procell-expert.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A ... |
plasticfruits | null | null | null | false | 2 | false | plasticfruits/wikihow_small | 2022-04-29T10:24:34.000Z | null | false | 474fa5e109d3675a21add2fc4cc0f201159545ec | [] | [
"language:en",
"license:mit"
] | https://huggingface.co/datasets/plasticfruits/wikihow_small/resolve/main/README.md | ---
language: en
license: mit
---
# WikiHow Entries
Contains wikiHow question, answer and summary in `.json` format. |
muibk | null | @inproceedings{freitag-etal-2021-results,
title = {Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain},
author = {Freitag, Markus and Rei, Ricardo and Mathur, Nitika and Lo, Chi-kiu and Stewart, Craig and Foster, George and Lavie, Alon an... | This shared task will examine automatic evaluation metrics for machine translation. We will
provide you with MT system outputs along with source text and the human reference translations.
We are looking for automatic metric scores for translations at the system-level, and segment-level.
We will calculate the system-... | false | 2 | false | muibk/wmt21_metrics_task | 2022-07-12T13:13:25.000Z | null | false | 0653eeaccbe5f0a9738220e0b1615f791da248b1 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:machine-generated",
"language_creators:expert-generated",
"language:bn-hi",
"language:cs-en",
"language:de-en",
"language:de-fr",
"language:en-cs",
"language:en-de",
"language:en-ha",
"language:en-is",
"la... | https://huggingface.co/datasets/muibk/wmt21_metrics_task/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
- machine-generated
- expert-generated
language:
- bn-hi
- cs-en
- de-en
- de-fr
- en-cs
- en-de
- en-ha
- en-is
- en-ja
- en-ru
- en-zh
- fr-de
- ha-en
- hi-bn
- is-en
- ja-en
- ru-en
- xh-zh
- zh-en
- zu-xh
license:
- unknown
multilinguality:
- t... |
rish16 | null | null | null | false | 1 | false | rish16/cs4243-database-dict | 2022-04-29T12:25:57.000Z | null | false | 5f2f2089d47d9d4ba9d20d7cd792703d85b554bc | [] | [
"license:mit"
] | https://huggingface.co/datasets/rish16/cs4243-database-dict/resolve/main/README.md | ---
license: mit
---
|
jamescalam | null | null | null | false | 5 | false | jamescalam/world-cities-geo | 2022-04-29T18:34:46.000Z | null | false | 8a8252c8c8e8c9a8f7ecaeb27bae1ac8b2313ab0 | [] | [] | https://huggingface.co/datasets/jamescalam/world-cities-geo/resolve/main/README.md | Dataset containing city, country, region, and continents alongside their longitude and latitude co-ordinates. Cartesian coordinates are provided in x, y, z features. |
dalle-mini | null | null | null | false | 1 | false | dalle-mini/vqgan-pairs | 2022-10-25T13:56:57.000Z | null | false | 03f4a9bf2ec961792476aee76a9fa8722ff8dc1e | [] | [
"license:cc-by-4.0",
"license:cc-by-2.0",
"license:unknown",
"source_datasets:Open Images",
"task_categories:other",
"tags:super-resolution",
"tags:image-enhancement"
] | https://huggingface.co/datasets/dalle-mini/vqgan-pairs/resolve/main/README.md | ---
license:
- cc-by-4.0
- cc-by-2.0
- unknown
source_datasets:
- Open Images
task_categories:
- other
task_ids: []
pretty_name: VQGAN Pairs
tags:
- super-resolution
- image-enhancement
---
# VQGAN Pairs
This dataset contains ~2.4 million image pairs intended for improvement of image quality in VQGAN predictions. Eac... |
Seledorn | null | null | null | false | 1 | false | Seledorn/SwissProt-EC | 2022-04-30T15:12:33.000Z | null | false | 3b03eda1bd275edf2d9caaccf07d32d2c237c0d2 | [] | [
"language:protein sequences",
"datasets:Swissprot",
"tags:Protein",
"tags:Enzyme Commission",
"tags:EC"
] | https://huggingface.co/datasets/Seledorn/SwissProt-EC/resolve/main/README.md | ---
language:
- protein sequences
datasets:
- Swissprot
tags:
- Protein
- Enzyme Commission
- EC
---
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The datase... |
Seledorn | null | null | null | false | 1 | false | Seledorn/SwissProt-Pfam | 2022-04-30T15:15:55.000Z | null | false | 0db4e0ea3153c4caa5c49e7387f65b78a8996148 | [] | [
"language:protein sequences",
"datasets:Swissprot",
"tags:Protein",
"tags:PFam"
] | https://huggingface.co/datasets/Seledorn/SwissProt-Pfam/resolve/main/README.md | ---
language:
- protein sequences
datasets:
- Swissprot
tags:
- Protein
- PFam
---
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with PFam labels.
The dataset is ported from Protinfer: http... |
Seledorn | null | null | null | false | 1 | false | Seledorn/SwissProt-GO | 2022-04-30T15:16:48.000Z | null | false | f64128a2e9e7a2756daacee8cc00e9b86142e19e | [] | [
"language:protein sequences",
"datasets:Swissprot",
"tags:Protein",
"tags:Gene Ontology",
"tags:GO"
] | https://huggingface.co/datasets/Seledorn/SwissProt-GO/resolve/main/README.md | ---
language:
- protein sequences
datasets:
- Swissprot
tags:
- Protein
- Gene Ontology
- GO
---
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Gene Ontology labels.
The dataset is port... |
samhellkill | null | null | null | false | 1 | false | samhellkill/spacekitty-v1 | 2022-04-30T06:33:09.000Z | null | false | edc48764e7faeea87dbc8b157ddae26d3fb62408 | [] | [
"license:other"
] | https://huggingface.co/datasets/samhellkill/spacekitty-v1/resolve/main/README.md | ---
license: other
---
|
charly | null | null | null | false | 1 | false | charly/test | 2022-04-30T17:17:22.000Z | null | false | d59c4caa6cd95db6dea4a389b3195404aeaf5d5d | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/charly/test/resolve/main/README.md | ---
license: apache-2.0
---
|
lightonai | null | null | null | false | 1 | false | lightonai/SwissProt-EC-leaf | 2022-05-05T09:54:42.000Z | null | false | 74c9c46cc27003593171ef289c364f42d0f4286b | [] | [
"language:protein sequences",
"datasets:Swissprot",
"tags:Protein",
"tags:Enzyme Commission"
] | https://huggingface.co/datasets/lightonai/SwissProt-EC-leaf/resolve/main/README.md | ---
language:
- protein sequences
datasets:
- Swissprot
tags:
- Protein
- Enzyme Commission
---
# Dataset
Swissprot is a high quality manually annotated protein database. The dataset contains annotations with the functional properties of the proteins. Here we extract proteins with Enzyme Commission labels.
The ... |
osyvokon | null | null | null | false | 1 | false | osyvokon/wiki-edits-uk | 2022-07-02T19:06:25.000Z | null | false | dc89ed1cc59ea92c19958c81c58070a2e95b02ab | [] | [
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:uk-UA",
"license:cc-by-3.0",
"multilinguality:monolingual",
"multilinguality:translation",
"size_categories:1M<n<10M",
"source_datasets:original",
"task_categories:other"
] | https://huggingface.co/datasets/osyvokon/wiki-edits-uk/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- uk-UA
license:
- cc-by-3.0
multilinguality:
- monolingual
- translation
pretty_name: 'Ukrainian Wikipedia edits '
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- other
task_ids: []
---
# Ukrainian Wikipedi... |
defector | null | null | null | false | 1 | false | defector/autotrain-data-company | 2022-10-25T10:12:59.000Z | null | false | c517b46f5b0574f716b9e3b173deb85d4db74236 | [] | [
"language:en"
] | https://huggingface.co/datasets/defector/autotrain-data-company/resolve/main/README.md | ---
language:
- en
---
# AutoTrain Dataset for project: company
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project company.
### Languages
The BCP-47 code for the dataset's language is en.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follow... |
Filippo | null | @dataset{osdg_2022_6393942,
author = {OSDG and
UNDP IICPSD SDG AI Lab and
PPMI},
title = {OSDG Community Dataset (OSDG-CD)},
month = apr,
year = 2022,
note = {{This CSV file uses UTF-8 character encoding. For
easy acce... | The OSDG Community Dataset (OSDG-CD) is a public dataset of thousands of text excerpts, which were validated by approximately 1,000 OSDG Community Platform (OSDG-CP) citizen scientists from over 110 countries, with respect to the Sustainable Development Goals (SDGs). | false | 1 | false | Filippo/osdg_cd | 2022-10-25T10:13:06.000Z | null | false | bc0f4e55534bfc6c52c3fd86928ccedef7aff585 | [] | [
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:text-classification",
"task_ids:natural-language-inference"
] | https://huggingface.co/datasets/Filippo/osdg_cd/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- text-classification
task_ids:
- natural-language-inference
pretty_name: OSDG Community Dataset (OSDG-CD)
---
# Dataset Card for O... |
Anon126 | null | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | false | 1 | false | Anon126/my-raft-submission | 2022-05-01T10:50:18.000Z | null | false | 4ed58453467ac729dd815696584b8fad8dac4646 | [] | [
"benchmark:raft",
"type:prediction",
"submission_name:none"
] | https://huggingface.co/datasets/Anon126/my-raft-submission/resolve/main/README.md | ---
benchmark: raft
type: prediction
submission_name: none
---
# RAFT submissions for my-raft-submission
## Submitting to the leaderboard
To make a submission to the [leaderboard](https://huggingface.co/spaces/ought/raft-leaderboard), there are three main steps:
1. Generate predictions on the unlabeled test set of ... | |
Rodion | null | null | null | false | 1 | false | Rodion/uno_sustainable_development_goals | 2022-05-01T13:54:31.000Z | null | false | 869f3ba009c4258ae2d272e664931404de6ec67d | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/Rodion/uno_sustainable_development_goals/resolve/main/README.md | ---
license: afl-3.0
---
|
NazaGara | null | @inproceedings{,
title = "",
author = "Garagiola, Nazareno",
year = "2022",
url = ""
} | Dataset used to train a NER model | false | 1 | false | NazaGara/wikiner-es | 2022-08-14T15:01:57.000Z | null | false | c3d2d2159db2fb34ca8ef05cbf96f21addeeea8b | [] | [
"license:cc"
] | https://huggingface.co/datasets/NazaGara/wikiner-es/resolve/main/README.md | annotations_creators:
- automatic
language_creators:
- found
languages:
- es-AR
licenses:
- cc0-1.0
multilinguality:
- monolingual
paperswithcode_id:
pretty_name: wikiner
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
license: c... |
hongdijk | null | null | null | false | 1 | false | hongdijk/kor_nlu_hufsice2 | 2022-05-23T16:33:29.000Z | null | false | 082b1de183522ccd43858713564b51b36ee28f93 | [] | [
"license:other"
] | https://huggingface.co/datasets/hongdijk/kor_nlu_hufsice2/resolve/main/README.md | ---
license: other
---
|
hongdijk | null | null | null | false | 1 | false | hongdijk/kor_nlu_hufs | 2022-05-20T10:25:34.000Z | null | false | 5cbdab6346ed40a167a4dca0bbd91ef7eeda736d | [] | [
"license:cc-by-sa-4.0"
] | https://huggingface.co/datasets/hongdijk/kor_nlu_hufs/resolve/main/README.md | ---
license: cc-by-sa-4.0
---
|
kimtaehyuk11 | null | @misc{park2021klue,
title={KLUE: Korean Language Understanding Evaluation},
author={Sungjoon Park and Jihyung Moon and Sungdong Kim and Won Ik Cho and Jiyoon Han and Jangwon Park and Chisung Song and Junseong Kim and Yongsook Song and Taehwan Oh and Joohong Lee and Juhyun Oh and Sungwon Lyu and Younghoon Je... | KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions.... | false | 1 | false | kimtaehyuk11/klue | 2022-05-01T19:55:19.000Z | null | false | 7f9afbbf365b4662fc8a8b677ee94f33d4073752 | [] | [
"license:cc-by-sa-4.0"
] | https://huggingface.co/datasets/kimtaehyuk11/klue/resolve/main/README.md | ---
license: cc-by-sa-4.0
---
|
Diegomejia | null | null | null | false | 1 | false | Diegomejia/ds1ucb | 2022-05-02T02:03:54.000Z | null | false | c44ea85c786b78a24aeefc0fcbe5c5c66648f720 | [] | [
"license:mit"
] | https://huggingface.co/datasets/Diegomejia/ds1ucb/resolve/main/README.md | ---
license: mit
---
|
google | null | @article{srinivasan2021wit,
title={WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning},
author={Srinivasan, Krishna and Raman, Karthik and Chen, Jiecao and Bendersky, Michael and Najork, Marc},
journal={arXiv preprint arXiv:2103.01913},
year={2021}
} | Wikipedia-based Image Text (WIT) Dataset is a large multimodal multilingual dataset.
WIT is composed of a curated set of 37.6 million entity rich image-text examples with 11.5 million unique images across 108 Wikipedia languages.
Its size enables WIT to be used as a pretraining dataset for multimodal machine learning m... | false | 27 | false | google/wit | 2022-07-04T10:47:07.000Z | wit | false | b52b6486b38d74ddaf95626b15e0f0c50fa5e959 | [] | [
"arxiv:2103.01913",
"annotations_creators:machine-generated",
"language_creators:found",
"language:af",
"language:ar",
"language:ast",
"language:azb",
"language:be",
"language:bg",
"language:bn",
"language:br",
"language:ca",
"language:cs",
"language:cy",
"language:da",
"language:de",
... | https://huggingface.co/datasets/google/wit/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- af
- ar
- ast
- azb
- be
- bg
- bn
- br
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gl
- hr
- hu
- hy
- id
- it
- iw
- ja
- ka
- ko
- la
- lt
- lv
- mk
- ml
- ms
- nl
- nn
- 'no'
- pl
- pt
- ro
- r... |
Davincilee | null | null | null | false | 1 | false | Davincilee/door_inner_with_SAE | 2022-05-02T14:16:14.000Z | null | false | 4f517807d7ecf96e4686674ead3a445b22f4b9b1 | [] | [
"license:other"
] | https://huggingface.co/datasets/Davincilee/door_inner_with_SAE/resolve/main/README.md | ---
license: other
---
|
shanya | null | @inproceedings{
title = {Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset},
author = {Rameshkumar, Revanth and Bailey, Peter},
year = {2020},
publisher = {Association for Computational Linguistics},
conference = {ACL}
} | Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset.
Critical Role is an unscripted, live-streamed show where a fixed group of people play Dungeons and Dragons, an open-ended role-playing game.
The dataset is collected from 159 Critical Role episodes transcribed to text dialogues, consisting of 398... | false | 130 | false | shanya/crd3 | 2022-10-25T10:13:08.000Z | crd3 | false | d9a3cfd6830ce040b34c1169d564227de87d5bf8 | [] | [
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"source_datasets:original",
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
... | https://huggingface.co/datasets/shanya/crd3/resolve/main/README.md | ---
pretty_name: CRD3 (Critical Role Dungeons and Dragons Dataset)
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- summarization
- text-generation
- fill-mask
task_ids:
- dialogue... |
wikimedia | null | null | null | false | 85 | false | wikimedia/wit_base | 2022-11-04T15:09:33.000Z | wit | false | ff6d4fb32fd566d3a1fa20e946cba3234179465e | [] | [
"arxiv:2103.01913",
"arxiv:1512.03385",
"arxiv:1905.00641",
"annotations_creators:machine-generated",
"language_creators:found",
"language:af",
"language:an",
"language:ar",
"language:arz",
"language:ast",
"language:az",
"language:azb",
"language:ba",
"language:bar",
"language:be",
"la... | https://huggingface.co/datasets/wikimedia/wit_base/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- af
- an
- ar
- arz
- ast
- az
- azb
- ba
- bar
- be
- bg
- bn
- br
- bs
- ca
- ce
- ceb
- ckb
- cs
- cv
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- fy
- ga
- gl
- hi
- hr
- hsb
- ht
- hu
- hy
- ia
- id
- io
- is... |
pauli31 | null | null | null | false | 1 | false | pauli31/czech-subjectivity-dataset | 2022-07-01T15:31:40.000Z | null | false | e1ad894c08c0c58d19d0ca4467dce6b96df042aa | [] | [
"arxiv:2204.13915",
"language:cs-CZ",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/pauli31/czech-subjectivity-dataset/resolve/main/README.md | ---
annotations_creators: []
language_creators: []
language:
- cs-CZ
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: Czech Subjectivity Dataset
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card f... |
arbml | null | @misc{alyafeai2021masader,
title={Masader: Metadata Sourcing for Arabic Text and Speech Data Resources},
author={Zaid Alyafeai and Maraim Masoud and Mustafa Ghaleb and Maged S. Al-shaibani},
year={2021},
eprint={2110.06744},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | Masader is the largest public catalogue for Arabic NLP datasets, which consists of more than 200 datasets annotated with 25 attributes. | false | 4,422 | false | arbml/masader | 2022-07-08T14:45:05.000Z | null | false | d2d59a4ccf942da4f70948219362271f14efc5c8 | [] | [
"license:mit"
] | https://huggingface.co/datasets/arbml/masader/resolve/main/README.md | ---
license: mit
---
|
Apo | null | null | null | false | 1 | false | Apo/ADE20K_sky_13labels | 2022-05-03T07:24:40.000Z | null | false | 143c5879a8ddd8a45a5ed7c7f429c89b430a80c6 | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/Apo/ADE20K_sky_13labels/resolve/main/README.md | ---
license: afl-3.0
---
|
Erwin | null | null | null | false | 2 | false | Erwin/coffee_reviews_corpus | 2022-05-03T08:22:38.000Z | null | false | 0d01b67c73ed0a50d03a46e8283b37dab58fe3bc | [] | [
"license:mit"
] | https://huggingface.co/datasets/Erwin/coffee_reviews_corpus/resolve/main/README.md | ---
license: mit
---
|
null | null | @article{tne,
author = {Elazar, Yanai and Basmov, Victoria and Goldberg, Yoav and Tsarfaty, Reut},
title = "{Text-based NP Enrichment}",
journal = {Transactions of the Association for Computational Linguistics},
year = {2022},
} | TNE is an NLU task, which focus on relations between noun phrases (NPs) that can be mediated via prepositions.
The dataset contains 5,497 documents, annotated exhaustively with all possible links between the NPs in each document. | false | 440 | false | tne | 2022-11-03T16:15:29.000Z | null | false | 051084916ead68ba57c14143bac8a94f7a94d069 | [] | [
"arxiv:2109.12085",
"annotations_creators:crowdsourced",
"language_creators:found",
"language:en",
"license:mit",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-retrieval",
"task_ids:document-retrieval"
] | https://huggingface.co/datasets/tne/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: Text-based NP Enrichment
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-retrieval
task_ids:
- document-retrieval
dataset_info:
features:
- na... |
farazeftekhar | null | null | null | false | 1 | false | farazeftekhar/geojson | 2022-05-03T19:15:48.000Z | null | false | e874dfff456d716a0700c244c36baebd58581ebd | [] | [
"license:other"
] | https://huggingface.co/datasets/farazeftekhar/geojson/resolve/main/README.md | ---
license: other
---
|
orieg | null | @article{Kershaw2020ElsevierOC,
title = {Elsevier OA CC-By Corpus},
author = {Daniel James Kershaw and R. Koeling},
journal = {ArXiv},
year = {2020},
volume = {abs/2008.00774},
doi = {https://doi.org/10.48550/arXiv.2008.00774},
url = {https://elsevier.digitalcommonsdata.com/da... | Elsevier OA CC-By is a corpus of 40k (40, 091) open access (OA) CC-BY articles
from across Elsevier’s journals and include the full text of the article, the metadata,
the bibliographic information for each reference, and author highlights. | false | 3 | false | orieg/elsevier-oa-cc-by | 2022-07-01T15:59:58.000Z | elsevier-oa-cc-by | false | 77840f2f84038fdf4b608fff764b21b7ef18eb34 | [] | [
"arxiv:2008.00774",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:fill-mask",
"task_categories:summarization",
"task_cate... | https://huggingface.co/datasets/orieg/elsevier-oa-cc-by/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Elsevier OA CC-By
paperswithcode_id: elsevier-oa-cc-by
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- fill-mask
- summarization... |
allenai | null | null | null | false | 3 | false | allenai/drug-combo-extraction | 2022-05-04T04:12:53.000Z | null | false | 8092b28c4f8490d234c1385bb385575ec7408330 | [] | [
"license:mit"
] | https://huggingface.co/datasets/allenai/drug-combo-extraction/resolve/main/README.md | ---
license: mit
---
|
Ukhushn | null | null | null | false | 1 | false | Ukhushn/home-depot | 2022-10-25T10:20:53.000Z | null | false | aee7fea371b991a01db75877fd23e37d381379c0 | [] | [
"language:en",
"language_bcp47:en-US",
"license:afl-3.0",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"task_categories:sentence-similarity"
] | https://huggingface.co/datasets/Ukhushn/home-depot/resolve/main/README.md | ---
language:
- en
language_bcp47:
- en-US
license:
- afl-3.0
annotations_creators:
- no-annotation
language_creators:
- found
multilinguality:
- monolingual
pretty_name: Ukhushn/home-depot
size_categories:
- 10K<n<100K
source_datasets: []
task_categories:
- sentence-similarity
task_ids: []
---
# Dataset Card for Ukhu... |
nielsr | null | null | null | false | 1 | false | nielsr/test | 2022-05-04T12:09:13.000Z | null | false | ad1898d0b872d98ab4747b07315385a1736ce36b | [] | [] | https://huggingface.co/datasets/nielsr/test/resolve/main/README.md | This is used for the pix2seq model. It contains the preprocessed pixel values of the cats image, useful for converting. |
nlpconnect | null | null | null | false | 3 | false | nlpconnect/DocVQA | 2022-05-04T14:24:06.000Z | null | false | fc36ebb3fa15bdf8731049b609e61d1fb5e696a5 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/nlpconnect/DocVQA/resolve/main/README.md | ---
license: apache-2.0
---
|
null | null | @inproceedings{singh2019towards,
title={Towards VQA Models That Can Read},
author={Singh, Amanpreet and Natarjan, Vivek and Shah, Meet and Jiang, Yu and Chen, Xinlei and Batra, Dhruv and Parikh, Devi and Rohrbach, Marcus},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognit... | TextVQA requires models to read and reason about text in images to answer questions about them.
Specifically, models need to incorporate a new modality of text present in the images and reason
over it to answer TextVQA questions. TextVQA dataset contains 45,336 questions over 28,408 images
from the OpenImages dataset. | false | 153 | false | textvqa | 2022-11-03T16:07:43.000Z | null | false | 383e2193a964bc1eae55ab17fab772d5fad6bb6a | [] | [
"arxiv:1904.08920",
"arxiv:2007.00398",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:visual-question-answering",
"task_ids:visua... | https://huggingface.co/datasets/textvqa/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: TextVQA
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- visual-question-answering
task_ids:
- visual-question-answering
dataset_info:
- ... |
jordane95 | null | null | null | false | 1 | false | jordane95/msmarco-passage-corpus-10-query-0.4 | 2022-05-05T09:56:37.000Z | null | false | d8ee804686c79825f75e57849b3c28ddad83715f | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/jordane95/msmarco-passage-corpus-10-query-0.4/resolve/main/README.md | ---
license: afl-3.0
---
|
00data00 | null | null | null | false | 1 | false | 00data00/data | 2022-05-05T10:48:22.000Z | null | false | 42ea7b9b5daa33cc0509a6213c48da0ce8ae13aa | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/00data00/data/resolve/main/README.md | ---
license: afl-3.0
---
|
null | null | @inproceedings{haoyietal-informer-2021,
author = {Haoyi Zhou and
Shanghang Zhang and
Jieqi Peng and
Shuai Zhang and
Jianxin Li and
Hui Xiong and
Wancai Zhang},
title = {Informer: Beyond Efficient Transformer for Long Se... | The data of Electricity Transformers from two separated counties
in China collected for two years at hourly and 15-min frequencies.
Each data point consists of the target value "oil temperature" and
6 power load features. The train/val/test is 12/4/4 months. | false | 58 | false | ett | 2022-11-03T15:59:15.000Z | null | false | e7fe05d403bfb7cfe5b90e3ad73dec1369667eff | [] | [
"arxiv:2012.07436",
"annotations_creators:no-annotation",
"language_creators:found",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:time-series-forecasting",
"task_ids:univariate-time-series-forecasting",
"task_ids:multi... | https://huggingface.co/datasets/ett/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language: []
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Electricity Transformer Temperature
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- time-series-forecasting
task_ids:
- univariate-time-series-for... |
ghomasHudson | null | null | null | false | 1 | false | ghomasHudson/hotpotExtendedAnoLM | 2022-05-05T14:09:26.000Z | null | false | 7d5a48f50f02568d74fb4d0ca4c333684addc26d | [] | [] | https://huggingface.co/datasets/ghomasHudson/hotpotExtendedAnoLM/resolve/main/README.md | # hotpotExtendedAno-LM
Version of hotpotExtended-Annotated formatted for Language Modelling. |
truthisneverlinear | null | null | null | false | 1 | false | truthisneverlinear/eleventh-doctor-scripts | 2022-05-05T14:39:18.000Z | null | false | 7d23ca7e27a34288f7083619602a7a902938ead9 | [] | [
"language:en",
"tags:NLP",
"tags:conservation",
"tags:dialogue"
] | https://huggingface.co/datasets/truthisneverlinear/eleventh-doctor-scripts/resolve/main/README.md | ---
language: en
tags:
- NLP
- conservation
- dialogue
---
# Doctor Who Dialogues
This dataset contains all the script lines of Eleventh Doctor from Doctor Who which is a popular TV series. It can be processed and used for chatbots or relevant stuff. |
boli-ai-admin | null | null | null | false | 1 | false | boli-ai-admin/vishal | 2022-05-05T14:59:54.000Z | null | false | bd758693b05d8405157aa662564a93edc53c6be7 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/boli-ai-admin/vishal/resolve/main/README.md | ---
license: apache-2.0
---
|
ablam | null | null | null | false | 3 | false | ablam/gcode | 2022-05-05T19:14:30.000Z | null | false | aa413c82b227dd25308df571e8b9d26e034cf2f7 | [] | [] | https://huggingface.co/datasets/ablam/gcode/resolve/main/README.md | # Gcode (Geometric code)
## Details
**Usage:** 3D printing <br>
**Source:** Printables.com <br>
**Slicer:** Prusa <br>
**Category:** Art & Design <br>
**Subcategory:** Sculptures <br>
**Models:** 400 <br>
**Sliced files:** 740 (some models have many) <br>
**Data format:** txt <br>
**Train-test split:** 90/10 <br>
**S... |
adsabs | null | null | null | false | 36 | false | adsabs/WIESP2022-NER | 2022-11-03T14:49:38.000Z | null | false | 5a1e54edeb5345cad0cd899f7b188b9337e16413 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/adsabs/WIESP2022-NER/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'WIESP2022-NER'
size_categories:
- 1K<n<10K
source_datasets: []
task_categories:
- token-classification
task_ids:
- named-entity-recognition
---
# Dataset for the first... |
nateraw | null | null | null | false | 1 | false | nateraw/gradio-guides-files | 2022-05-05T21:07:09.000Z | null | false | 6ef57a87aea2fddaa26e86f7f3eda48ba3171a8b | [] | [
"license:mit"
] | https://huggingface.co/datasets/nateraw/gradio-guides-files/resolve/main/README.md | ---
license: mit
---
|
BennoKrojer | null | null | null | false | 1 | false | BennoKrojer/ImageCoDe | 2022-05-13T21:26:08.000Z | null | false | b7b7a73dbc74b681b384048716232b243ad25a99 | [] | [
"arxiv:2203.15867",
"license:afl-3.0"
] | https://huggingface.co/datasets/BennoKrojer/ImageCoDe/resolve/main/README.md | ---
license: afl-3.0
---
# Dataset Card for ImageCoDe
To get started quickly, load descriptions via:
```
from datasets import load_dataset
examples = load_dataset('BennoKrojer/ImageCoDe')
```
And download `image_sets.zip` for all images sets (each directory consisting of 10 images).
## Dataset Description
- **Homep... |
nateraw | null | null | null | false | 1 | false | nateraw/test-imagefolder-metadata | 2022-05-06T01:51:57.000Z | null | false | 3adb85380e4645c1fcf914a21ba4013410c0fa2b | [] | [] | https://huggingface.co/datasets/nateraw/test-imagefolder-metadata/resolve/main/README.md | # test-imagefolder-metadata |
ntt123 | null | null | null | false | 2 | false | ntt123/viet-tts-dataset | 2022-05-06T09:03:02.000Z | null | false | e1623289640e76fe2209e753a1b78a2200edc34e | [] | [
"license:cc-by-nc-4.0"
] | https://huggingface.co/datasets/ntt123/viet-tts-dataset/resolve/main/README.md | ---
license: cc-by-nc-4.0
---
# Vietnamese Text-To-Speech dataset (VietTTS-v1.1)
🔔🔔🔔 visit https://github.com/NTT123/vietTTS for a vietnamese TTS library (included pretrained models). 🔔🔔🔔
The text is from a collection of novels and short stories from the author "Vu Trong Phung." The text is in public domain.
Th... |
searle-j | null | @article{jeon2022user,
title={User Guide for KOTE: Korean Online Comments Emotions Dataset},
author={Jeon, Duyoung and Lee, Junho and Kim, Cheongtag},
journal={arXiv preprint arXiv:2205.05300},
year={2022}
} | 50k Korean online comments labeled for 44 emotion categories. | false | 32 | false | searle-j/kote | 2022-10-20T19:16:24.000Z | null | false | 66f0eefe4b675a5d5411c7aa08e2c97fc9a9b17f | [] | [
"annotations_creators:crowdsourced",
"language:kor",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:multi-label-classification",
"task_ids:text-classific... | https://huggingface.co/datasets/searle-j/kote/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language:
- kor
license:
- mit
multilinguality:
- monolingual
pretty_name: kote
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
- multi-label-classification
- text-classification-other-emotio... |
null | null | @InProceedings{pmlr-v174-pal22a,
title = {MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering},
author = {Pal, Ankit and Umapathi, Logesh Kumar and Sankarasubbu, Malaikannan},
booktitle = {Proceedings of the Conference on Health, Inference, and Learning},
pa... | MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.... | false | 273 | false | medmcqa | 2022-11-03T16:07:43.000Z | medmcqa | false | 6f73325ca5f480a097a7201187b7ec7e8620a899 | [] | [
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:question-answering",
"task_categories:multiple-choice",
"task_ids:multiple-choic... | https://huggingface.co/datasets/medmcqa/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
- multiple-choice
task_ids:
- multiple-choice-qa
- open-domain-qa
paperswithc... |
Fhrozen | null | null | null | false | 35 | false | Fhrozen/FSD50k | 2022-05-27T08:50:25.000Z | null | false | 67e4d8c2570caef0f90d48fdb756b337875d91db | [] | [
"arxiv:2010.00475",
"license:cc-by-4.0",
"annotations_creators:unknown",
"language_creators:unknown",
"size_categories:10K<n<100K",
"source_datasets:unknown",
"task_categories:audio-classification",
"task_ids:other-audio-slot-filling"
] | https://huggingface.co/datasets/Fhrozen/FSD50k/resolve/main/README.md | ---
license: cc-by-4.0
annotations_creators:
- unknown
language_creators:
- unknown
size_categories:
- 10K<n<100K
source_datasets:
- unknown
task_categories:
- audio-classification
task_ids:
- other-audio-slot-filling
---
# Freesound Dataset 50k (FSD50K)
## Important
**This data set is a copy from the original one l... |
filwsyl | null | @article{lecun2010mnist,
title={MNIST handwritten digit database},
author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
volume={2},
year={2010}
} | The MNIST dataset consists of 70,000 28x28 black-and-white images in 10 classes (one for each digits), with 7,000
images per class. There are 60,000 training images and 10,000 test images. | false | 1 | false | filwsyl/video_tags | 2022-10-25T10:13:17.000Z | mnist | false | a9d58d45d5363ececbe0485f26350fff6835f611 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:enx",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-nist",
"task_categories:image-classification",
"task_ids:multi-class-image-classification"
] | https://huggingface.co/datasets/filwsyl/video_tags/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- enx
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-nist
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
paperswithcode_id: mnist
pretty_... |
taln-ls2n | null | @inproceedings{gallina-etal-2019-kptimes,
title = "{KPT}imes: A Large-Scale Dataset for Keyphrase Generation on News Documents",
author = "Gallina, Ygor and
Boudin, Florian and
Daille, Beatrice",
booktitle = "Proceedings of the 12th International Conference on Natural Language Generation",
... | KPTimes benchmark dataset for keyphrase extraction an generation. | false | 14 | false | taln-ls2n/kptimes | 2022-09-23T07:38:28.000Z | null | false | 36d51f10c05d1598552a0374b04d7b8e58efddbc | [] | [
"annotations_creators:unknown",
"language_creators:unknown",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"task_categories:text-generation",
"task_ids:keyphrase-generation",
"task_ids:keyphrase-extraction",
"size_categories:100K<n<1M"
] | https://huggingface.co/datasets/taln-ls2n/kptimes/resolve/main/README.md | ---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
task_categories:
- text-mining
- text-generation
task_ids:
- keyphrase-generation
- keyphrase-extraction
size_categories:
- 100K<n<1M
pretty_name: KPTimes
---
# KPTimes Benchmark Dataset ... |
swcrazyfan | null | null | null | false | 1 | false | swcrazyfan/net-kjv | 2022-05-06T10:05:48.000Z | null | false | da97033c65ab45c0f6735cfa5b9c18ff8e9f1bde | [] | [] | https://huggingface.co/datasets/swcrazyfan/net-kjv/resolve/main/README.md | languages:
- en
task_categories:
- translation
licenses:
- unknown
# Dataset Card for [Needs More Information]
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Stru... |
vehnem | null | null | null | false | 1 | false | vehnem/DBpedia | 2022-05-06T11:01:55.000Z | null | false | b603503ce82cf503a03ffa407feb2c17d4f4c27a | [] | [
"license:cc-by-sa-3.0"
] | https://huggingface.co/datasets/vehnem/DBpedia/resolve/main/README.md | ---
license: cc-by-sa-3.0
---
|
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