id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
stas/wmt14-en-de-pre-processed | 2021-02-16T04:41:04.000Z | [
"region:us"
] | stas | null | @InProceedings{huggingface:dataset,
title = {WMT14 English-German Translation Data with further preprocessing},
authors={},
year={2016}
} | 1 | 173 | 2022-03-02T23:29:22 | # WMT14 English-German Translation Data w/ further preprocessing
The original pre-processing script is [here](https://github.com/pytorch/fairseq/blob/master/examples/translation/prepare-wmt14en2de.sh).
This pre-processed dataset was created by running:
```
git clone https://github.com/pytorch/fairseq
cd fairseq
cd e... | 654 | [
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0.0... |
Fsoft-AIC/the-vault-function | 2023-07-04T02:33:36.000Z | [
"task_categories:text-generation",
"multilinguality:multiprogramming languages",
"language:code",
"language:en",
"license:mit",
"arxiv:2305.06156",
"region:us"
] | Fsoft-AIC | The Vault is a multilingual code-text dataset with over 40 million pairs covering 10 popular programming languages.
It is the largest corpus containing parallel code-text data. By building upon The Stack, a massive raw code sample collection,
the Vault offers a comprehensive and clean resource for advancing research ... | @article{manh2023vault,
title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation},
author={Manh, Dung Nguyen and Hai, Nam Le and Dau, Anh TV and Nguyen, Anh Minh and Nghiem, Khanh and Guo, Jin and Bui, Nghi DQ},
journal={arXiv preprint arXiv:2305.06156},
year={2023}... | 8 | 173 | 2023-05-05T14:25:47 | ---
language:
- code
- en
multilinguality:
- multiprogramming languages
task_categories:
- text-generation
license: mit
dataset_info:
features:
- name: identifier
dtype: string
- name: return_type
dtype: string
- name: repo
dtype: string
- name: path
dtype: string
- name: language
dtype:... | 11,327 | [
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explodinggradients/ragas-wikiqa | 2023-07-27T07:13:14.000Z | [
"region:us"
] | explodinggradients | null | null | 2 | 173 | 2023-05-31T19:33:37 | ---
dataset_info:
features:
- name: question
dtype: string
- name: correct_answer
dtype: string
- name: incorrect_answer
dtype: string
- name: question_id
dtype: string
- name: generated_with_rag
dtype: string
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sequence: string
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dty... | 621 | [
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GATE-engine/automated_cardiac_diagnosis_competition.ACDC | 2023-06-28T08:56:08.000Z | [
"region:us"
] | GATE-engine | null | null | 0 | 173 | 2023-06-28T08:26:44 | ---
dataset_info:
features:
- name: four_d_img
sequence:
sequence:
sequence:
sequence: float32
- name: frame_data
list:
- name: img
sequence:
sequence:
sequence: float32
- name: label
sequence:
sequence:
sequence: int64
spli... | 707 | [
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0.... |
euclaise/MiniCoT | 2023-10-22T13:13:55.000Z | [
"task_categories:question-answering",
"size_categories:10K<n<100K",
"chain-of-thought",
"cot",
"region:us"
] | euclaise | null | null | 0 | 173 | 2023-09-25T01:09:54 | ---
size_categories:
- 10K<n<100K
task_categories:
- question-answering
pretty_name: MiniCoT
dataset_info:
features:
- name: rationale
dtype: string
- name: target
dtype: string
- name: source
dtype: string
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 23484941
num_... | 1,011 | [
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0.0331... |
persian_ner | 2023-01-25T14:42:29.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fa",
"license:cc-by-4.0",
"region:us"
] | null | The dataset includes 250,015 tokens and 7,682 Persian sentences in total. It is available in 3 folds to be used in turn as training and test sets. The NER tags are in IOB format. | @inproceedings{poostchi-etal-2016-personer,
title = "{P}erso{NER}: {P}ersian Named-Entity Recognition",
author = "Poostchi, Hanieh and
Zare Borzeshi, Ehsan and
Abdous, Mohammad and
Piccardi, Massimo",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Comput... | 0 | 172 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: Persian NER
dataset_info... | 6,616 | [
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0.024200439453125,
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-0.06085205078125,
-0.039642333984375,
0.0258... |
BeIR/beir | 2022-10-21T15:30:43.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | 3 | 172 | 2022-03-02T23:29:22 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... | 13,988 | [
[
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0.005954742431640625,
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GEM/schema_guided_dialog | 2022-10-24T15:30:26.000Z | [
"task_categories:conversational",
"annotations_creators:crowd-sourced",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"dialog-response-generation",
"arxiv:1909.05855",
"arxiv:2004.15006",
"a... | GEM | The Schema-Guided Dialogue (SGD) dataset contains 18K multi-domain task-oriented
dialogues between a human and a virtual assistant, which covers 17 domains
ranging from banks and events to media, calendar, travel, and weather. The
language presents in the datset is only English. The SGD dataset provides a
challenging t... | @inproceedings{rastogi2020towards,
title={Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset},
author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
... | 3 | 172 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowd-sourced
language_creators:
- unknown
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: schema_guided_dialog
tags:
- dialog-response-generation
---
# Datas... | 29,513 | [
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0.05767822265625,
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-0.045074462890625,
-0.02867126464... |
bigbio/tmvar_v2 | 2022-12-22T15:47:06.000Z | [
"multilinguality:monolingual",
"language:en",
"license:unknown",
"region:us"
] | bigbio | This dataset contains 158 PubMed articles manually annotated with mutation mentions of various kinds and dbsnp normalizations for each of them.
It can be used for NER tasks and NED tasks, This dataset has a single split | @article{wei2018tmvar,
title={tmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine},
author={Wei, Chih-Hsuan and Phan, Lon and Feltz, Juliana and Maiti, Rama and Hefferon, Tim and Lu, Zhiyong},
journal={Bioinformatics},
volume={34},
number={1},
pages={80--87},... | 1 | 172 | 2022-11-13T22:12:31 |
---
language:
- en
bigbio_language:
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: tmVar v2
homepage: https://www.ncbi.nlm.nih.gov/research/bionlp/Tools/tmvar/
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISA... | 1,153 | [
[
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0.0183258056640625,
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... |
squarelike/sharegpt_deepl_ko_translation | 2023-10-12T17:11:05.000Z | [
"region:us"
] | squarelike | null | null | 3 | 172 | 2023-07-14T04:28:43 | [https://github.com/jwj7140/Gugugo](https://github.com/jwj7140/Gugugo)
[sharegpt_deepl_ko](https://huggingface.co/datasets/junelee/sharegpt_deepl_ko)를 한-영 번역데이터로 변환한 데이터입니다.
- translation_data_sharegpt.json: 최대 약 1300자 분량의 번역 데이터 모음
- translation_data_sharegpt_long.json: 1300자~7000자 분량의 번역 데이터 모음
sharegpt_deepl_ko에서... | 343 | [
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0.0112762451171875,
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-0.0020122... |
OrdalieTech/baby-ordalie | 2023-08-23T07:18:15.000Z | [
"task_categories:summarization",
"size_categories:1K<n<10K",
"language:fr",
"license:apache-2.0",
"legal",
"region:us"
] | OrdalieTech | null | null | 0 | 172 | 2023-07-21T18:14:33 | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 1375639.2
num_examples: 1200
- name: test
num_bytes: 343909.8
num_examples: 300
download_size: 951948
dataset_size: 1719549.0
license: apache-2.0
task_categories:... | 616 | [
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-0... |
bigcode/oasst-octopack | 2023-08-17T10:33:37.000Z | [
"arxiv:2308.07124",
"region:us"
] | bigcode | null | null | 4 | 172 | 2023-07-26T20:52:07 | This is a filtered version of OASST to focus only on high-quality conversation trees as used in the [OctoPack](https://arxiv.org/abs/2308.07124) paper.
```python
from datasets import load_dataset
d = load_dataset("bigcode/oasst-octopack")["train"]
``` | 252 | [
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CATIE-AQ/DFP | 2023-10-17T15:39:12.000Z | [
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:text2text-generation",
"task_categories:fill-mask",
"t... | CATIE-AQ | null | null | 2 | 172 | 2023-08-22T07:56:20 | ---
task_categories:
- text-classification
- token-classification
- question-answering
- zero-shot-classification
- summarization
- text-generation
- text2text-generation
- fill-mask
- sentence-similarity
language:
- fr
size_categories:
- 100M<n<1B
tags:
- DFP
- french prompts
annotations_creators:
- found
language_cre... | 166,205 | [
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0.0390625,
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0.0334777832... |
stockmark/ner-wikipedia-dataset | 2023-09-02T14:42:18.000Z | [
"task_categories:token-classification",
"language:ja",
"license:cc-by-sa-3.0",
"Named Entity Recognition",
"NER",
"region:us"
] | stockmark | null | null | 1 | 172 | 2023-09-02T14:38:55 | ---
license: cc-by-sa-3.0
language:
- ja
tags:
- Named Entity Recognition
- NER
task_categories:
- token-classification
---
# Wikipediaを用いた日本語の固有表現抽出データセット
- GitHub: https://github.com/stockmarkteam/ner-wikipedia-dataset/
- LICENSE: CC-BY-SA 3.0
Developed by Stockmark Inc. | 276 | [
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taishi-i/awesome-japanese-nlp-classification-dataset | 2023-09-09T11:09:04.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"language:ja",
"license:other",
"code",
"region:us"
] | taishi-i | This dataset determines whether a GitHub repository description relates to Japanese natural language processing (NLP). The labels are categorized as "Relevant (1)" and "Not Relevant (0)". | null | 3 | 172 | 2023-09-09T06:37:36 | ---
license: other
task_categories:
- text-classification
language:
- en
- ja
tags:
- code
size_categories:
- 1K<n<10K
---
# Dataset overview
This dataset identifies whether a GitHub repository description pertains to Japanese natural language processing (NLP).
The labels are categorized as **"Relevant (1)" and "Not... | 4,748 | [
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kewu93/pixel_500 | 2023-10-06T09:31:47.000Z | [
"region:us"
] | kewu93 | null | null | 0 | 172 | 2023-10-06T09:31:40 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 5863021.833333333
num_examples: 500
- name: val
num... | 587 | [
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Spiral-AI/cc100_debug | 2023-10-17T04:27:52.000Z | [
"region:us"
] | Spiral-AI | null | null | 0 | 172 | 2023-10-17T04:27:47 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 12282688
num_examples: 129838
download_size: 6976030
dataset_size: 12282688
---
# Dataset Card for "cc100_debug"
[More In... | 443 | [
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tlc | 2022-11-03T16:31:06.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:expert-generated",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:n<1K... | null | Thai Literature Corpora (TLC): Corpora of machine-ingestible Thai classical literature texts.
Release: 6/25/19
It consists of two datasets:
## TLC set
It is texts from [Vajirayana Digital Library](https://vajirayana.org/), stored by chapters and stanzas (non-tokenized).
tlc v.2.0 (6/17/19 : a total of 34 documents,... | @misc{
author={Sawatphol, Jitkapat},
title={Thai Literature Corpora},
year={2019},
howpublished={\\url{https://attapol.github.io/tlc.html}}
} | 0 | 171 | 2022-03-02T23:29:22 | ---
pretty_name: Thai Literature Corpora (TLC)
annotations_creators:
- expert-generated
- no-annotation
language_creators:
- expert-generated
language:
- th
license:
- unknown
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- la... | 6,055 | [
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-0.07080078125,
-0.03558349609375,
0.03427124023... |
namespace-Pt/msmarco | 2023-10-16T15:10:08.000Z | [
"region:us"
] | namespace-Pt | null | null | 0 | 171 | 2023-10-16T15:10:02 | ---
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
dataset_info:
features:
- name: query
dtype: string
- name: positive
sequence: string
splits:
- name: dev
num_bytes: 2962960
num_examples: 6980
download_size: 1925216
dataset_size: 2962960
---
# Dataset C... | 470 | [
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CJWeiss/billsum | 2023-10-26T20:40:16.000Z | [
"region:us"
] | CJWeiss | null | null | 0 | 171 | 2023-10-26T20:40:03 | ---
dataset_info:
features:
- name: text
dtype: string
- name: summary
dtype: string
- name: title
dtype: string
splits:
- name: train
num_bytes: 193223866
num_examples: 16664
- name: test
num_bytes: 38326645
num_examples: 3332
- name: valid
num_bytes: 25911836
num_ex... | 551 | [
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disaster_response_messages | 2023-01-25T14:29:29.000Z | [
"task_categories:text2text-generation",
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:sentiment-classification",
"task_ids:text-simplification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categ... | null | This dataset contains 30,000 messages drawn from events including an earthquake in Haiti in 2010, an earthquake in Chile in 2010, floods in Pakistan in 2010, super-storm Sandy in the U.S.A. in 2012, and news articles spanning a large number of years and 100s of different disasters.
The data has been encoded with 36 dif... | @inproceedings{title={Multilingual Disaster Response Messages}
} | 3 | 170 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- es
- fr
- ht
- ur
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text2text-generation
- text-classification
task_ids:
- intent-classification
-... | 13,308 | [
[
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-0.03521728515625,
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0.051971435546875,
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-0.064453125,
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0.0288391... |
cakiki/args_me | 2022-10-25T09:07:25.000Z | [
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:'en-US'",
"license:cc-by-4.0",
"region:us"
] | cakiki | The args.me corpus (version 1.0, cleaned) comprises 382 545 arguments crawled from four debate portals in the middle of 2019. The debate portals are Debatewise, IDebate.org, Debatepedia, and Debate.org. The arguments are extracted using heuristics that are designed for each debate portal. | @dataset{yamen_ajjour_2020_4139439,
author = {Yamen Ajjour and
Henning Wachsmuth and
Johannes Kiesel and
Martin Potthast and
Matthias Hagen and
Benno Stein},
title = {args.me corpus},
month = oct,
year ... | 1 | 170 | 2022-03-02T23:29:22 | ---
annotations_creators:
- machine-generated
language_creators:
- crowdsourced
language:
- '''en-US'''
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Webis args.me argument corpus
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-retrieval
task_ids:
- document-retrieval... | 4,852 | [
[
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0.... |
joelniklaus/MultiLegalPileWikipediaFiltered | 2023-03-28T19:23:38.000Z | [
"task_categories:fill-mask",
"annotations_creators:other",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language... | joelniklaus | A filtered version of the MultiLegalPile dataset, together with wikipedia articles. | 2 | 170 | 2023-01-31T21:51:25 | ---
annotations_creators:
- other
language_creators:
- found
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- ga
- hr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
license:
- cc-by-4.0
multilinguality:
- multilingual
paperswithcode_id: null
pretty_name: "MultiLegalPileWiki... | 54,209 | [
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... | |
LeoLM/ArcChallenge_de | 2023-08-29T13:32:23.000Z | [
"region:us"
] | LeoLM | null | null | 0 | 170 | 2023-08-10T22:22:09 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: choices
struct:
- name: text
sequence: string
- name: label
... | 804 | [
[
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-0.041717529296875,
0.02149... |
distil-whisper/tedlium-timestamped | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-nc-nd-3.0",
"region:us"
] | distil-whisper | The TED-LIUM corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech. | null | 0 | 170 | 2023-09-22T09:05:11 | ---
license: cc-by-nc-nd-3.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: TEDLIUM
---
# Distil Whisper: TEDLIUM With Timestamps
This is a variant of the [TEDLIUM](https://huggingface.co/datasets/LIUM/tedlium) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions alon... | 2,051 | [
[
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saahith/EMSAssist-2 | 2023-10-07T04:11:54.000Z | [
"region:us"
] | saahith | null | null | 0 | 170 | 2023-10-07T04:00:11 | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: transcript
dtype: string
- name: duration
dtype: float64
splits:
- name: train
num_bytes: 617788659.262
num_examples: 1122
- name: test
num_bytes: 1197091986.0
num_examples: 600
download_size: 1350447521
dataset... | 511 | [
[
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fiveflow/passage_report | 2023-10-26T13:24:32.000Z | [
"region:us"
] | fiveflow | null | null | 0 | 170 | 2023-10-19T03:25:30 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 9522212
num_examples: 1190
download_size: 4789024
dataset_size: 9522212
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "passage_report"
[More Inf... | 442 | [
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code_x_glue_cc_code_refinement | 2023-07-27T14:09:03.000Z | [
"task_categories:text2text-generation",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:other-programming-languages",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:code",
"license:c-uda",
"debugging",
"arxiv:2102.04664",
"arxiv:1812.0869... | null | We use the dataset released by this paper(https://arxiv.org/pdf/1812.08693.pdf). The source side is a Java function with bugs and the target side is the refined one. All the function and variable names are normalized. Their dataset contains two subsets ( i.e.small and medium) based on the function length. | @article{10.1145/3340544,
author = {Tufano, Michele and Watson, Cody and Bavota, Gabriele and Penta, Massimiliano Di and White, Martin and Poshyvanyk, Denys},
title = {An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation},
year = {2019},
issue_date = {October 2019},
publisher = {... | 2 | 169 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- code
license:
- c-uda
multilinguality:
- other-programming-languages
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
pretty_name: CodeXGlueCcCodeRefinement
tags:
- debugging... | 7,597 | [
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spc | 2023-06-01T14:59:49.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:af",
"language:el",
"language:en",
"language:zh",
"license:unknown",
"region:us"
] | null | This is a collection of parallel corpora collected by Hercules Dalianis and his research group for bilingual dictionary construction.
More information in: Hercules Dalianis, Hao-chun Xing, Xin Zhang: Creating a Reusable English-Chinese Parallel Corpus for Bilingual Dictionary Construction, In Proceedings of LREC2010 (s... | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 0 | 169 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- af
- el
- en
- zh
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: spc
dataset_info:
- config_name: af-en
... | 3,817 | [
[
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0.0095062... |
tuple_ie | 2022-11-03T16:31:04.000Z | [
"task_categories:other",
"annotations_creators:found",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:unknown",
"open-information-extraction",
"region:us"
] | null | The TupleInf Open IE dataset contains Open IE tuples extracted from 263K sentences that were used by the solver in “Answering Complex Questions Using Open Information Extraction” (referred as Tuple KB, T). These sentences were collected from a large Web corpus using training questions from 4th and 8th grade as queries.... | @article{Khot2017AnsweringCQ,
title={Answering Complex Questions Using Open Information Extraction},
author={Tushar Khot and A. Sabharwal and Peter Clark},
journal={ArXiv},
year={2017},
volume={abs/1704.05572}
} | 1 | 169 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- machine-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: tupleinf-open-ie-dataset
pretty_name: TupleInf Open IE
tags:
- open-... | 6,483 | [
[
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-0.040435791015625... |
NeelNanda/c4-code-20k | 2022-12-26T23:25:12.000Z | [
"region:us"
] | NeelNanda | null | null | 1 | 169 | 2022-12-26T23:22:53 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 101351288
num_examples: 20000
download_size: 42778874
dataset_size: 101351288
---
# Dataset Card for "c4-code-10k"
10K elements of C4 and 10K elements of code parrot clean (Python code).
Note that these are... | 754 | [
[
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... |
TigerResearch/pretrain_zh | 2023-06-14T13:50:32.000Z | [
"region:us"
] | TigerResearch | null | null | 85 | 169 | 2023-06-01T01:45:01 | ---
dataset_info:
features:
- name: dataType
dtype: string
- name: title
dtype: string
- name: content
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dtype: string
- name: titleUkey
dtype: string
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dtype: int64
splits:
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num_bytes: 58043923125
num_examples: 169050... | 797 | [
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pankajmathur/dolly-v2_orca | 2023-06-26T14:39:23.000Z | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | pankajmathur | null | null | 16 | 169 | 2023-06-24T18:30:01 | ---
license: cc-by-nc-sa-4.0
task_categories:
- text-generation
language:
- en
size_categories:
- 10K<n<100K
---
Explain tuned Dolly-V2 dataset ~15K created using approaches from Orca Research Paper.
We leverage all of the 15 system instructions provided in Orca Research Paper to generate explain tuned datasets, in c... | 631 | [
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distil-whisper/gigaspeech-l-timestamped | 2023-09-25T10:28:51.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:other",
"region:us"
] | distil-whisper | GigaSpeech is an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality
labeled audio suitable for supervised training, and 40,000 hours of total audio suitable for semi-supervised
and unsupervised training. Around 40,000 hours of transcribed audio is first collected from audiobooks,... | @article{DBLP:journals/corr/abs-2106-06909,
author = {Guoguo Chen and
Shuzhou Chai and
Guanbo Wang and
Jiayu Du and
Wei{-}Qiang Zhang and
Chao Weng and
Dan Su and
Daniel Povey and
Jan Trmal and
... | 0 | 169 | 2023-09-22T09:05:06 | ---
license: other
task_categories:
- automatic-speech-recognition
language:
- en
extra_gated_prompt: |-
SpeechColab does not own the copyright of the audio files. For researchers and educators who wish to use the audio files for non-commercial research and/or educational purposes, we can provide access through the... | 4,332 | [
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distil-whisper/peoples_speech-clean-timestamped | 2023-09-25T10:30:12.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | The People's Speech is a free-to-download 30,000-hour and growing supervised
conversational English speech recognition dataset licensed for academic and
commercial usage under CC-BY-SA (with a CC-BY subset). | @article{DBLP:journals/corr/abs-2111-09344,
author = {Daniel Galvez and
Greg Diamos and
Juan Ciro and
Juan Felipe Ceron and
Keith Achorn and
Anjali Gopi and
David Kanter and
Maximilian Lam and
Ma... | 0 | 169 | 2023-09-22T09:05:09 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: People's Speech Clean
---
# Distil Whisper: People's Speech Clean With Timestamps
This is a variant of the [People's Speech Clean](https://huggingface.co/datasets/MLCommons/peoples_speech) dataset, augmented to return ... | 2,125 | [
[
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0.0042381... |
distil-whisper/voxpopuli-timestamped | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc0-1.0",
"region:us"
] | distil-whisper | A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. | @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... | 0 | 169 | 2023-09-22T09:05:12 | ---
license: cc0-1.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: VoxPopuli
---
# Distil Whisper: VoxPopuli With Timestamps
This is a variant of the [VoxPopuli](https://huggingface.co/datasets/facebook/voxpopuli) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions ... | 2,045 | [
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bobbybelajar/AmazonMixedLength | 2023-10-15T07:19:36.000Z | [
"region:us"
] | bobbybelajar | null | null | 0 | 169 | 2023-10-15T07:19:12 | Entry not found | 15 | [
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alexrs/alpaca-cleaned-5-clusters | 2023-10-16T14:42:10.000Z | [
"region:us"
] | alexrs | null | null | 0 | 169 | 2023-10-16T14:42:06 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
- name: input
dtype: string
- name: cluster
dtype: int32
splits:
- name: train
num_bytes: 40490946
num_examples: 51760
download_size: 24177437
dataset_size: 40490946
configs:
- config_nam... | 568 | [
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SetFit/amazon_reviews_multi_de | 2022-03-23T15:34:53.000Z | [
"region:us"
] | SetFit | null | null | 0 | 168 | 2022-03-13T02:45:18 | #amazon reviews multi german
This dataset is a port of the official ['amazon_reviews_multi' dataset] (https://huggingface.co/datasets/amazon_reviews_multi) on the Hub. It has just the German language version. It has been reduced to just 3 columns (and 4th "label_text") that are relevant to the SetFit task. | 308 | [
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ashraq/ott-qa-20k | 2022-10-21T09:06:25.000Z | [
"region:us"
] | ashraq | null | null | 3 | 168 | 2022-10-18T19:30:29 | ---
dataset_info:
features:
- name: url
dtype: string
- name: title
dtype: string
- name: header
sequence: string
- name: data
sequence:
sequence: string
- name: section_title
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- name: uid
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- name: intro
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llm-book/jsnli | 2023-10-25T15:22:46.000Z | [
"size_categories:100K<n<1M",
"language:ja",
"license:cc-by-sa-4.0",
"region:us"
] | llm-book | null | null | 0 | 168 | 2023-06-19T12:31:46 | ---
language:
- ja
size_categories:
- 100K<n<1M
license:
- cc-by-sa-4.0
dataset_info:
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
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splits:
- name: train
num_bytes: 97491392
num_examples: 533005
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num_bytes: 71... | 646 | [
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reciprocate/megasynth | 2023-07-03T09:37:26.000Z | [
"region:us"
] | reciprocate | null | null | 0 | 168 | 2023-07-03T09:37:10 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: selected
dtype: string
- name: rejected
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- name: source
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splits:
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download_... | 526 | [
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C-MTEB/AFQMC | 2023-07-28T13:39:01.000Z | [
"region:us"
] | C-MTEB | null | null | 0 | 168 | 2023-07-28T13:38:46 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype:
class_l... | 821 | [
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LeoLM/TruthfulQA_de | 2023-08-29T13:30:32.000Z | [
"task_categories:multiple-choice",
"size_categories:n<1K",
"language:de",
"language:en",
"license:apache-2.0",
"arxiv:2109.07958",
"region:us"
] | LeoLM | null | null | 0 | 168 | 2023-08-10T12:17:15 | ---
dataset_info:
features:
- name: question
dtype: string
- name: mc1_targets
struct:
- name: choices
sequence: string
- name: labels
sequence: int64
- name: mc2_targets
struct:
- name: choices
sequence: string
- name: labels
sequence: int64
- name: questio... | 7,348 | [
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distil-whisper/ami-ihm-timestamped | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,... | @inproceedings{10.1007/11677482_3,
author = {Carletta, Jean and Ashby, Simone and Bourban, Sebastien and Flynn, Mike and Guillemot, Mael and Hain, Thomas and Kadlec, Jaroslav and Karaiskos, Vasilis and Kraaij, Wessel and Kronenthal, Melissa and Lathoud, Guillaume and Lincoln, Mike and Lisowska, Agnes and McCowan, Iain ... | 0 | 168 | 2023-09-22T09:05:01 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: AMI IHM
---
# Distil Whisper: AMI IHM With Timestamps
This is a variant of the [AMI IHM](https://huggingface.co/datasets/edinburghcstr/ami) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions along... | 2,039 | [
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distil-whisper/ami-sdm-timestamped | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,... | @inproceedings{10.1007/11677482_3,
author = {Carletta, Jean and Ashby, Simone and Bourban, Sebastien and Flynn, Mike and Guillemot, Mael and Hain, Thomas and Kadlec, Jaroslav and Karaiskos, Vasilis and Kraaij, Wessel and Kronenthal, Melissa and Lathoud, Guillaume and Lincoln, Mike and Lisowska, Agnes and McCowan, Iain ... | 0 | 168 | 2023-09-22T09:05:02 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: AMI SDM
---
# Distil Whisper: AMI SDM With Timestamps
This is a variant of the [AMI SDM](https://huggingface.co/datasets/edinburghstr/ami) dataset, augmented to return the pseudo-labelled Whisper
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FinGPT/fingpt-fiqa_qa | 2023-10-10T06:51:12.000Z | [
"region:us"
] | FinGPT | null | null | 0 | 168 | 2023-10-10T06:37:38 | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
- name: instruction
dtype: string
splits:
- name: train
num_bytes: 20914549
num_examples: 17110
download_size: 10813846
dataset_size: 20914549
configs:
- config_name: default
data_files:
- split:... | 522 | [
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classla/ssj500k | 2022-10-28T05:37:22.000Z | [
"task_categories:token-classification",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:parsing",
"task_ids:part-of-speech",
"language:sl",
"license:cc-by-sa-4.0",
"structure-prediction",
"tokenization",
"dependency-parsing",
"region:us"
] | classla | The dataset contains 7432 training samples, 1164 validation samples and 893 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent_id'),
list of tokens ('tokens'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos_tags), list of UPOS tags ('upos_tags'), list... | null | 0 | 167 | 2022-03-02T23:29:22 | ---
language:
- sl
license:
- cc-by-sa-4.0
task_categories:
- token-classification
task_ids:
- lemmatization
- named-entity-recognition
- parsing
- part-of-speech
tags:
- structure-prediction
- tokenization
- dependency-parsing
---
The dataset contains 7432 training samples, 1164 validation samples and 893 test samples... | 803 | [
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0.050628662109375,
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0.03421... |
codeparrot/codeparrot-clean-train | 2022-10-10T15:27:50.000Z | [
"region:us"
] | codeparrot | null | null | 10 | 167 | 2022-03-02T23:29:22 | # CodeParrot 🦜 Dataset Cleaned (train)
Train split of [CodeParrot 🦜 Dataset Cleaned](https://huggingface.co/datasets/lvwerra/codeparrot-clean).
## Dataset structure
```python
DatasetDict({
train: Dataset({
features: ['repo_name', 'path', 'copies', 'size', 'content', 'license', 'hash', 'line_mean', 'line... | 396 | [
[
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0.01811218... |
jonathan-roberts1/PatternNet | 2023-03-31T17:06:42.000Z | [
"task_categories:image-classification",
"task_categories:zero-shot-image-classification",
"license:other",
"region:us"
] | jonathan-roberts1 | null | null | 0 | 167 | 2023-01-27T12:46:23 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': airplane
'1': baseball field
'2': basketball court
'3': beach
'4': bridge
'5': cemetery
'6': chaparral
'7': chr... | 2,314 | [
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cesarali/test_ipp50 | 2023-08-28T17:28:36.000Z | [
"region:us"
] | cesarali | null | null | 0 | 167 | 2023-08-28T17:28:33 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: question
dtype: string
- name: choices
sequence: string
- name: value
dtype: float64
splits:
- name: train
num_bytes: 8439
num_examples: 50
download_size: 4060
dataset_size: 8439
---
# Dataset Card for "test_ipp50"
[M... | 449 | [
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distil-whisper/tedlium-prompted | 2023-09-18T13:21:11.000Z | [
"region:us"
] | distil-whisper | null | null | 0 | 167 | 2023-09-18T12:41:46 | ---
dataset_info:
config_name: release3
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: string
- name: gender
dtype:
class_label:
names:
'0': unknown
'1': female
'2': mal... | 1,131 | [
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codymlewis/HAR | 2023-10-13T03:23:34.000Z | [
"size_categories:n<1K",
"license:cc-by-4.0",
"region:us"
] | codymlewis | The Human Activity Recognition dataset. | @misc{misc_smartphone-based_recognition_of_human_activities_and_postural_transitions_341,
author = {Reyes-Ortiz,Jorge, Anguita,Davide, Oneto,Luca, and Parra,Xavier},
title = {{Smartphone-Based Recognition of Human Activities and Postural Transitions}},
year = {2015},
howpublished = {UCI Mac... | 0 | 167 | 2023-09-19T05:19:13 | ---
dataset_info:
features:
- name: features
sequence: float32
length: 561
- name: labels
dtype:
class_label:
names:
'0': WALKING
'1': WALKING_UPSTAIRS
'2': WALKING_DOWNSTAIRS
'3': SITTING
'4': STANDING
'5': LAYING
'6'... | 4,557 | [
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distil-whisper/common_voice_13_0-timestamped | 2023-09-25T10:30:12.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc0-1.0",
"region:us"
] | distil-whisper | null | @inproceedings{commonvoice:2020,
author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
title = {Common Voice: A Massively-Multilingual Speech Corpus},
booktitle = {Proceedings of the 12th Conference on Lang... | 0 | 167 | 2023-09-22T09:05:04 | ---
license: cc0-1.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: Common Voice 13
---
# Distil Whisper: Common Voice 13 With Timestamps
This is a variant of the [Common Voice 13](https://huggingface.co/datasets/mozilla_foundation/common_voice_13) dataset, augmented to return the pseudo... | 2,111 | [
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0... |
llmware/rag_instruct_test_dataset_0.1 | 2023-10-15T16:33:13.000Z | [
"license:apache-2.0",
"finance",
"legal",
"region:us"
] | llmware | null | null | 3 | 167 | 2023-10-08T11:55:59 | ---
license: apache-2.0
tags:
- finance
- legal
pretty_name: RAG Instruct Test Dataset - Basic - v0.1
---
# Dataset Card for RAG-Instruct-Test-Dataset
### Dataset Summary
This is a test dataset for basic "retrieval augmented generation" (RAG) use cases in the enterprise, especially for finance and legal. This test d... | 3,521 | [
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classla/hr500k | 2022-10-25T07:32:05.000Z | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:hr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | classla | The hr500k training corpus contains about 500,000 tokens manually annotated on the levels of
tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation and named entities.
On the sentence level, the dataset contains 20159 training samples, 1963 validation samples and 2672 test samples
across the re... | null | 0 | 166 | 2022-03-02T23:29:22 | ---
language:
- hr
license:
- cc-by-sa-4.0
task_categories:
- other
task_ids:
- lemmatization
- named-entity-recognition
- part-of-speech
tags:
- structure-prediction
- normalization
- tokenization
---
The hr500k training corpus contains 506,457 Croatian tokens manually annotated on the levels of tokenisation, sentenc... | 2,160 | [
[
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classla/setimes_sr | 2022-10-25T07:30:04.000Z | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:sr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | classla | SETimes_sr is a Serbian dataset annotated for morphosyntactic information and named entities.
The dataset contains 3177 training samples, 395 validation samples and 319 test samples
across the respective data splits. Each sample represents a sentence and includes the following features:
sentence ID ('sent_id'), sente... | null | 0 | 166 | 2022-03-02T23:29:22 | ---
language:
- sr
license:
- cc-by-sa-4.0
task_categories:
- other
task_ids:
- lemmatization
- named-entity-recognition
- part-of-speech
tags:
- structure-prediction
- normalization
- tokenization
---
The SETimes\_sr training corpus contains 86,726 Serbian tokens manually annotated on the levels of tokenisation, sent... | 1,834 | [
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LawalAfeez/science-dataset | 2022-08-17T11:38:40.000Z | [
"region:us"
] | LawalAfeez | null | null | 3 | 166 | 2022-08-17T11:29:41 | Entry not found | 15 | [
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zeroshot/twitter-financial-news-topic | 2022-12-04T16:50:10.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"twitter",
"finance",
"markets",
"stoc... | zeroshot | null | null | 16 | 166 | 2022-09-07T18:43:21 | ---
annotations_creators:
- other
language:
- en
language_creators:
- other
license:
- mit
multilinguality:
- monolingual
pretty_name: twitter financial news
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- twitter
- finance
- markets
- stocks
- wallstreet
- quant
- hedgefunds
- markets
task_categories... | 2,147 | [
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ywchoi/pubmed_abstract_1 | 2022-09-13T00:56:17.000Z | [
"region:us"
] | ywchoi | null | null | 1 | 166 | 2022-09-13T00:54:32 | Entry not found | 15 | [
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TheGreatRambler/mm2_level | 2022-11-11T08:07:34.000Z | [
"task_categories:other",
"task_categories:object-detection",
"task_categories:text-retrieval",
"task_categories:token-classification",
"task_categories:text-generation",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:multilingual",
"license:cc-b... | TheGreatRambler | null | null | 5 | 166 | 2022-09-18T20:15:00 | ---
language:
- multilingual
license:
- cc-by-nc-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- other
- object-detection
- text-retrieval
- token-classification
- text-generation
task_ids: []
pretty_name: Mario Maker 2 levels
tags:
- text-mining
---
... | 15,031 | [
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trpakov/chest-xray-classification | 2023-03-13T07:23:48.000Z | [
"task_categories:image-classification",
"roboflow",
"roboflow2huggingface",
"Biology",
"region:us"
] | trpakov | null | \ | 1 | 166 | 2023-03-13T07:23:40 | ---
task_categories:
- image-classification
tags:
- roboflow
- roboflow2huggingface
- Biology
---
<div align="center">
<img width="640" alt="trpakov/chest-xray-classification" src="https://huggingface.co/datasets/trpakov/chest-xray-classification/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['PNEUMON... | 1,558 | [
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jordyvl/rvl_cdip_easyocr | 2023-10-20T18:43:34.000Z | [
"task_categories:image-classification",
"task_ids:multi-class-image-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|iit_cdip",
"language:en",
"license:other",
"arxiv:1502.07058",
"regi... | jordyvl | The RVL-CDIP (Ryerson Vision Lab Complex Document Information Processing) dataset consists of 400,000 grayscale images in 16 classes, with 25,000 images per class. There are 320,000 training images, 40,000 validation images, and 40,000 test images. | @inproceedings{harley2015icdar,
title = {Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval},
author = {Adam W Harley and Alex Ufkes and Konstantinos G Derpanis},
booktitle = {International Conference on Document Analysis and Recognition ({ICDAR})}},
year = {2015}
} | 0 | 166 | 2023-04-19T10:51:31 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- extended|iit_cdip
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
paperswithcode_id: rvl-cdip
pretty_name: RVL-... | 6,709 | [
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GATE-engine/fungi | 2023-06-05T16:36:25.000Z | [
"region:us"
] | GATE-engine | null | null | 1 | 166 | 2023-06-05T00:42:00 | ---
dataset_info:
features:
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dtype: image
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splits:
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num_bytes: 6188400790.875
num_examples: 64449
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eduagarcia/cc100-pt | 2023-08-29T00:58:52.000Z | [
"region:us"
] | eduagarcia | null | null | 0 | 166 | 2023-08-28T21:24:32 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
splits:
- name: train
num_bytes: 53151660927
num_examples: 38999388
download_size: 16147647964
dataset_size: 53151660927
---
# Dataset Card for "cc100-pt"
[More Information needed](https://github.com/huggingfac... | 396 | [
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tuanio/book_corpus-input_ids-valid-len256 | 2023-10-26T08:47:25.000Z | [
"region:us"
] | tuanio | null | null | 0 | 166 | 2023-10-25T11:18:04 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
splits:
- name: train
num_bytes: 6319319328
num_examples: 6156107
download_size: 2939435774
dataset_size: 6319319328
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "book_co... | 481 | [
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msr_sqa | 2022-11-18T21:30:23.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:ms-pl",
"region:us"
] | null | Recent work in semantic parsing for question answering has focused on long and complicated questions, many of which would seem unnatural if asked in a normal conversation between two humans. In an effort to explore a conversational QA setting, we present a more realistic task: answering sequences of simple but inter-re... | @inproceedings{iyyer2017search,
title={Search-based neural structured learning for sequential question answering},
author={Iyyer, Mohit and Yih, Wen-tau and Chang, Ming-Wei},
booktitle={Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
pages={1821-... | 1 | 165 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- ms-pl
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: null
pretty_name: Microsoft Research Sequential ... | 10,056 | [
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orange_sum | 2022-11-18T21:36:52.000Z | [
"task_categories:summarization",
"task_ids:news-articles-headline-generation",
"task_ids:news-articles-summarization",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:fr",
"license:unknown",... | null | The OrangeSum dataset was inspired by the XSum dataset. It was created by scraping the "Orange Actu" website: https://actu.orange.fr/. Orange S.A. is a large French multinational telecommunications corporation, with 266M customers worldwide. Scraped pages cover almost a decade from Feb 2011 to Sep 2020. They belong to ... | @article{eddine2020barthez,
title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},
author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},
journal={arXiv preprint arXiv:2010.12321},
year={2020}
} | 3 | 165 | 2022-03-02T23:29:22 | ---
pretty_name: OrangeSum
annotations_creators:
- found
language_creators:
- found
language:
- fr
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
task_ids:
- news-articles-headline-generation
- news-articles-summarization
pape... | 7,835 | [
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biu-nlp/qa_srl2020 | 2022-10-17T20:49:01.000Z | [
"region:us"
] | biu-nlp | The dataset contains question-answer pairs to model verbal predicate-argument structure.
The questions start with wh-words (Who, What, Where, What, etc.) and contain a verb predicate in the sentence; the answers are phrases in the sentence.
This dataset, a.k.a "QASRL-GS" (Gold Standard) or "QASRL-2020", was constructe... | @inproceedings{roit2020controlled,
title={Controlled Crowdsourcing for High-Quality QA-SRL Annotation},
author={Roit, Paul and Klein, Ayal and Stepanov, Daniela and Mamou, Jonathan and Michael, Julian and Stanovsky, Gabriel and Zettlemoyer, Luke and Dagan, Ido},
booktitle={Proceedings of the 58th Annual Meeting o... | 1 | 165 | 2022-03-02T23:29:22 | # QA-SRL 2020 (Gold Standard)
The dataset contains question-answer pairs to model verbal predicate-argument structure.
The questions start with wh-words (Who, What, Where, What, etc.) and contain a verb predicate in the sentence; the answers are phrases in the sentence.
This dataset, a.k.a "QASRL-GS" (Gold Standard) ... | 967 | [
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okite97/news-data | 2022-08-25T10:36:01.000Z | [
"task_categories:text-classification",
"task_ids:topic-classification",
"task_ids:multi-class-classification",
"annotations_creators:other",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:afl-3.0",
"region... | okite97 | null | null | 2 | 165 | 2022-07-28T09:10:22 | ---
annotations_creators:
- other
language:
- 'en'
language_creators:
- found
license:
- afl-3.0
multilinguality:
- monolingual
pretty_name: News Dataset
size_categories:
- 1K<n<10K
source_datasets:
- original
tags: []
task_categories:
- text-classification
task_ids:
- topic-classification
- multi-class-classification
... | 3,508 | [
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ywchoi/pubmed_abstract_2 | 2022-09-13T00:58:59.000Z | [
"region:us"
] | ywchoi | null | null | 0 | 165 | 2022-09-13T00:57:10 | Entry not found | 15 | [
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eduagarcia/brwac_dedup | 2023-08-27T20:24:16.000Z | [
"region:us"
] | eduagarcia | null | null | 0 | 165 | 2023-08-27T18:56:05 | ---
dataset_info:
features:
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splits:
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num_bytes: 17503358516
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download_size: 10720096897
dataset_size: 17503358516
---
# Dataset Card for "brwac_dedup"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIB... | 368 | [
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namespace-Pt/msmarco-corpus | 2023-10-16T15:07:39.000Z | [
"region:us"
] | namespace-Pt | null | null | 0 | 165 | 2023-10-16T15:00:23 | ---
dataset_info:
features:
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dataset_size: 3243246889
configs:
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data_files:
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path: data/train-*
---
# Dataset Card for "msmarco-cor... | 457 | [
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bigbio/euadr | 2022-12-22T15:44:36.000Z | [
"multilinguality:monolingual",
"language:en",
"license:unknown",
"region:us"
] | bigbio | Corpora with specific entities and relationships annotated are essential to train and evaluate text-mining systems that are developed to extract specific structured information from a large corpus. In this paper we describe an approach where a named-entity recognition system produces a first annotation and annotators r... | @article{VANMULLIGEN2012879,
title = {The EU-ADR corpus: Annotated drugs, diseases, targets, and their relationships},
journal = {Journal of Biomedical Informatics},
volume = {45},
number = {5},
pages = {879-884},
year = {2012},
note = {Text Mining and Natural Language Processing in Pharmacogenomics},
issn = {1532-0464... | 2 | 164 | 2022-11-13T22:08:25 |
---
language:
- en
bigbio_language:
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: EU-ADR
homepage: https://www.sciencedirect.com/science/article/pii/S1532046412000573
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- RELATION_... | 3,011 | [
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RuyuanWan/SBIC_Disagreement | 2022-12-26T22:07:09.000Z | [
"task_categories:text-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:extended|social_bias_frames",
"language:en",
"region:us"
] | RuyuanWan | null | null | 0 | 164 | 2022-12-26T18:46:23 | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license: []
multilinguality:
- monolingual
pretty_name: RuyuanWan/SBIC_Disagreement
size_categories: []
source_datasets:
- extended|social_bias_frames
tags: []
task_categories:
- text-classification
task_ids: []
---
This dataset is proc... | 712 | [
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EMBO/SourceData | 2023-11-01T20:26:35.000Z | [
"task_categories:token-classification",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-4.0",
"biology",
"medical",
"NER",
"NEL",
"arxiv:2310.20440",
"doi:10.57967/hf/0495",
"region:us"
] | EMBO | This dataset is based on the SourceData database and is intented to facilitate training of NLP tasks in the cell and molecualr biology domain. | @Unpublished{
huggingface: dataset,
title = {SourceData NLP},
authors={Thomas Lemberger & Jorge Abreu-Vicente, EMBO},
year={2023}
} | 2 | 164 | 2023-03-27T11:19:24 | ---
license: cc-by-4.0
task_categories:
- token-classification
language:
- en
tags:
- biology
- medical
- NER
- NEL
size_categories:
- 10K<n<100K
pretty_name: SODA-NLP
---
# SourceData Dataset
> The largest annotated biomedical corpus for machine learning and AI in the publishing context.
SourceData is the largest a... | 10,799 | [
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lca0503/GPTspeech_encodec_v2 | 2023-06-15T06:54:51.000Z | [
"region:us"
] | lca0503 | null | null | 0 | 164 | 2023-06-14T16:48:10 | ---
dataset_info:
features:
- name: file_id
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sequence: int64
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sequence: in... | 1,298 | [
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martinsinnona/visdecode | 2023-10-19T02:20:30.000Z | [
"region:us"
] | martinsinnona | null | null | 0 | 164 | 2023-06-30T14:39:33 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
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splits:
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num_bytes: 14473249.0
num_examples: 800
- name: test
num_bytes: 1030647.0
num_examples: 58
download_size: 15241605
dataset_size: 15503896.0
---
# Dataset Card for "ploty"
[Mor... | 447 | [
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C-MTEB/PAWSX | 2023-07-28T13:43:08.000Z | [
"region:us"
] | C-MTEB | null | null | 0 | 164 | 2023-07-28T13:42:34 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
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- name: score
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split... | 726 | [
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FudanSELab/ClassEval | 2023-09-04T06:35:53.000Z | [
"task_categories:text2text-generation",
"size_categories:n<1K",
"language:en",
"license:mit",
"code-generation",
"arxiv:2308.01861",
"region:us"
] | FudanSELab | FudanSELab ClassEval | @misc{du2023classeval,
title={ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation},
author={Xueying Du and Mingwei Liu and Kaixin Wang and Hanlin Wang and Junwei Liu and Yixuan Chen and Jiayi Feng and Chaofeng Sha and Xin Peng and Yiling Lou},
year={2023},
... | 1 | 164 | 2023-09-02T09:28:37 | ---
license: mit
language:
- en
size_categories:
- n<1K
tags:
- code-generation
task_categories:
- text2text-generation
pretty_name: ClassEval
configs:
- config_name: default
data_files:
- split: test
path: "ClassEval_data.json"
---
# Dataset Card for FudanSELab ClassEval
## Dataset Description
- **Repos... | 4,260 | [
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... |
totally-not-an-llm/EverythingLM-data-V3 | 2023-09-11T02:54:38.000Z | [
"license:mit",
"region:us"
] | totally-not-an-llm | null | null | 13 | 164 | 2023-09-08T01:52:43 | ---
license: mit
---
# EverythingLM V3 Dataset
**EverythingLM V3** is a diverse instruct dataset consisting of roughly 1.1k of sysprompt-user-assistant triads. These were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions.
### Diferences from ... | 816 | [
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0.00471115112... |
minh21/cpgQA-v1.0-unique-context-test-10-percent-validation-10-percent | 2023-09-09T11:37:51.000Z | [
"region:us"
] | minh21 | null | null | 0 | 164 | 2023-09-09T11:37:47 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: title
dtype: string
- name: id
dtype: int64
- name: question
dtype: string
- name: answe... | 885 | [
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danish_political_comments | 2023-01-25T14:29:08.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:da",
"license:unknown",
"region:us"
] | null | The dataset consists of 9008 sentences that are labelled with fine-grained polarity in the range from -2 to 2 (negative to postive). The quality of the fine-grained is not cross validated and is therefore subject to uncertainties; however, the simple polarity has been cross validated and therefore is considered to be m... | null | 0 | 163 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- da
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
pretty_name: DanishPoliticalComments
dataset_info... | 3,393 | [
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GEM/turku_paraphrase_corpus | 2022-10-24T15:29:45.000Z | [
"task_categories:other",
"annotations_creators:expert-created",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:fi",
"license:cc-by-sa-4.0",
"paraphrasing",
"region:us"
] | GEM | Turku Paraphrase Corpus is a dataset of 104,645 manually annotated Finnish paraphrases. The vast majority of the data is classified as a paraphrase either in the given context, or universally. | @inproceedings{kanerva-etal-2021-finnish,
title = {Finnish Paraphrase Corpus},
author = {Kanerva, Jenna and Ginter, Filip and Chang, Li-Hsin and Rastas, Iiro and Skantsi, Valtteri and Kilpeläinen, Jemina and Kupari, Hanna-Mari and Saarni, Jenna and Sevón, Maija and Tarkka, Otto},
booktitle = {Proceedings of the 2... | 0 | 163 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-created
language_creators:
- unknown
language:
- fi
license:
- cc-by-sa-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids: []
pretty_name: turku_paraphrase_corpus
tags:
- paraphrasing
---
# Dataset Card for GEM/tur... | 22,125 | [
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bigscience-historical-texts/HIPE2020_sent-split | 2022-04-07T10:12:42.000Z | [
"region:us"
] | bigscience-historical-texts | TODO | TODO | 0 | 163 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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stepp1/tweet_emotion_intensity | 2022-04-18T20:49:56.000Z | [
"region:us"
] | stepp1 | null | null | 4 | 163 | 2022-04-18T17:32:33 | # Tweet Emotion Intensity Dataset
## Papers:
* Emotion Intensities in Tweets. Saif M. Mohammad and Felipe Bravo-Marquez. In Proceedings of the sixth joint conference on lexical and computational semantics (*Sem), August 2017, Vancouver, Canada.
* WASSA-2017 Shared Task on Emotion Intensity. Saif M. Mohammad and Fe... | 501 | [
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0.004871... |
bigcode/commitpack | 2023-08-20T07:13:13.000Z | [
"language:code",
"license:mit",
"arxiv:2308.07124",
"region:us"
] | bigcode | CommitPack is is a 4TB dataset of commits scraped from GitHub repositories that are permissively licensed. | @article{muennighoff2023octopack,
title={OctoPack: Instruction Tuning Code Large Language Models},
author={Niklas Muennighoff and Qian Liu and Armel Zebaze and Qinkai Zheng and Binyuan Hui and Terry Yue Zhuo and Swayam Singh and Xiangru Tang and Leandro von Werra and Shayne Longpre},
journal={arXiv p... | 36 | 163 | 2023-01-17T11:53:28 | ---
license: mit
pretty_name: CommitPack
language:
- code
---
# Dataset Card for CommitPack
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-descri... | 21,376 | [
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Multimodal-Fatima/VQAv2_sample_validation | 2023-06-09T00:06:10.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 163 | 2023-02-10T17:59:57 | ---
dataset_info:
features:
- name: question_type
dtype: string
- name: multiple_choice_answer
dtype: string
- name: answers
sequence: string
- name: answers_original
list:
- name: answer
dtype: string
- name: answer_confidence
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- name: answer_id
dtyp... | 6,589 | [
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-0.018417358398437... |
vietgpt/opus100_envi | 2023-07-03T17:56:58.000Z | [
"task_categories:translation",
"size_categories:1M<n<10M",
"language:en",
"language:vi",
"LM",
"region:us"
] | vietgpt | null | null | 0 | 163 | 2023-02-22T09:11:25 | ---
dataset_info:
features:
- name: en
dtype: string
- name: vi
dtype: string
splits:
- name: test
num_bytes: 192744
num_examples: 2000
- name: train
num_bytes: 82614470
num_examples: 1000000
- name: validation
num_bytes: 194721
num_examples: 2000
download_size: 59201490
... | 2,413 | [
[
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MultiCoNER/multiconer_v2 | 2023-07-06T18:37:15.000Z | [
"task_categories:token-classification",
"size_categories:100K<n<1M",
"language:bn",
"language:zh",
"language:de",
"language:en",
"language:es",
"language:fa",
"language:fr",
"language:hi",
"language:it",
"language:pt",
"language:sv",
"language:uk",
"license:cc-by-4.0",
"multiconer",
... | MultiCoNER | Complex named entities (NE), like the titles of creative works, are not simple nouns and pose challenges for NER systems (Ashwini and Choi, 2014). They can take the form of any linguistic constituent, like an imperative clause (“Dial M for Murder”), and do not look like traditional NEs (Persons, Locations, etc.). This ... | @inproceedings{multiconer2-report,
title={{SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)}},
author={Fetahu, Besnik and Kar, Sudipta and Chen, Zhiyu and Rokhlenko, Oleg and Malmasi, Shervin},
booktitle={Proceedings of the 17th International Workshop on Semantic Evalua... | 7 | 163 | 2023-03-01T00:57:16 | ---
license: cc-by-4.0
task_categories:
- token-classification
language:
- bn
- zh
- de
- en
- es
- fa
- fr
- hi
- it
- pt
- sv
- uk
tags:
- multiconer
- ner
- multilingual
- named entity recognition
- fine-grained ner
size_categories:
- 100K<n<1M
---
# Dataset Card for Multilingual Complex Named Entity Recognition (Mu... | 4,067 | [
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0.0147705078125,
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-0.06475830078125,
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0.02249145... |
HuggingFaceH4/databricks_dolly_15k | 2023-04-12T17:11:41.000Z | [
"license:cc-by-3.0",
"arxiv:2203.02155",
"region:us"
] | HuggingFaceH4 | null | null | 17 | 163 | 2023-04-12T16:51:27 | ---
license: cc-by-3.0
dataset_info:
features:
- name: category
dtype: string
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 12326332
num_examples: 15015
download_size: 0
dataset_size: 12326332
---
# ... | 7,884 | [
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emozilla/govreport-test-tokenized | 2023-08-09T02:35:24.000Z | [
"region:us"
] | emozilla | null | null | 0 | 163 | 2023-08-09T02:35:14 | ---
dataset_info:
features:
- name: id
dtype: string
- name: pid
dtype: string
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dtype: string
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sequence: int32
- name: attention_mask
sequence: int8
- name: tokenized_len
dtype: int64
splits:
- name: test
num_... | 593 | [
[
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-0.0443115234375,
-0.0161743... |
result-kand2-sdxl-wuerst-karlo/7b7794aa | 2023-10-10T14:58:52.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | 0 | 163 | 2023-10-10T14:58:50 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 166
num_examples: 10
download_size: 1306
dataset_size: 166
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "7b7794a... | 455 | [
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gyr66/privacy_detection | 2023-10-17T10:41:59.000Z | [
"task_categories:token-classification",
"language:zh",
"region:us"
] | gyr66 | privacy detection dataset, which includes the following categories of privacy information: [position, name, movie, organization, company, book, address, scene, mobile, email, game, government, QQ, vx].
The dataset consists of 3 columns. The first column is id, the second column is the list of text characters, and the t... | null | 0 | 163 | 2023-10-15T13:19:47 | ---
language:
- zh
task_categories:
- token-classification
dataset_info:
config_name: privacy_detection
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-position
'2': I-positi... | 1,395 | [
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eli5_category | 2022-11-18T20:00:33.000Z | [
"task_categories:text2text-generation",
"task_ids:abstractive-qa",
"task_ids:open-domain-abstractive-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|eli5",
"language:en",
"license:unknown",
"regio... | null | The ELI5-Category dataset is a smaller but newer and categorized version of the original ELI5 dataset. After 2017, a tagging system was introduced to this subreddit so that the questions can be categorized into different topics according to their tags. Since the training and validation set is built by questions in diff... | @inproceedings{eli5-category,
author = {Jingsong Gao and
Qingren Zhou and
Rui Qiu},
title = {{ELI5-Category:} A categorized open-domain QA dataset},
year = {2021}
} | 4 | 162 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: ELI5-Category
size_categories:
- 100K<n<1M
source_datasets:
- extended|eli5
task_categories:
- text2text-generation
task_ids:
- abstractive-qa
- open-domain-... | 12,581 | [
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recipe_nlg | 2023-01-25T14:43:04.000Z | [
"task_categories:text2text-generation",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:text-retrieval",
"task_categories:summarization",
"task_ids:document-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:explanation-generation",
"task_ids:language-modelin... | null | The dataset contains 2231142 cooking recipes (>2 millions). It's processed in more careful way and provides more samples than any other dataset in the area. | @inproceedings{bien-etal-2020-recipenlg,
title = "{R}ecipe{NLG}: A Cooking Recipes Dataset for Semi-Structured Text Generation",
author = "Bie{'n}, Micha{l} and
Gilski, Micha{l} and
Maciejewska, Martyna and
Taisner, Wojciech and
Wisniewski, Dawid and
Lawrynowicz, Agnieszka",
booktitle = "Proceedings of t... | 23 | 162 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text2text-generation
- text-generation
- fill-mask
- text-retrieval
- summarization
task_ids:
- document-retrieval
- en... | 7,111 | [
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Blaise-g/SumPubmed | 2022-07-28T19:53:40.000Z | [
"language:en",
"region:us"
] | Blaise-g | null | null | 0 | 162 | 2022-07-16T15:09:11 | ---
language:
- en
paperswithcode_id:
pretty_name: SumPubmed
train-eval-index:
- config: Blaise-g--SumPubmed
task: summarization
task_id: summarization
splits:
eval_split: test
col_mapping:
text: text
abstract: target
---
# Dataset Card for "SumPubmed"
## Original Dataset Description
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Multimodal-Fatima/COCO_captions_test | 2023-03-17T21:23:22.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 162 | 2023-03-17T21:22:46 | ---
dataset_info:
features:
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dtype: image
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dtype: string
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list: int32
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dtype: string
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dtype: int32
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howard-hou/COCO-Text | 2023-05-12T05:22:01.000Z | [
"region:us"
] | howard-hou | null | null | 0 | 162 | 2023-05-12T04:17:56 | ---
dataset_info:
features:
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EleutherAI/race | 2023-07-03T21:27:18.000Z | [
"task_categories:multiple-choice",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:other",
"arxiv:1704.04683",
"region:us"
] | EleutherAI | Race is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
dataset is collected from English examinations in China, which are designed for middle school and high school students.
The dataset can be served as the training and test sets for machine comprehension. | @article{lai2017large,
title={RACE: Large-scale ReAding Comprehension Dataset From Examinations},
author={Lai, Guokun and Xie, Qizhe and Liu, Hanxiao and Yang, Yiming and Hovy, Eduard},
journal={arXiv preprint arXiv:1704.04683},
year={2017}
} | 0 | 162 | 2023-07-03T13:20:38 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- other
multilinguality:
- monolingual
pretty_name: RACE
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- multiple-choice
task_ids:
- multiple-choice-qa
paperswithcode_id: race
dataset_info:
---
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