id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 68.7k ⌀ | citation stringlengths 0 10.7k ⌀ | cardData null | likes int64 0 3.55k | downloads int64 0 10.1M | card stringlengths 0 1.01M |
|---|---|---|---|---|---|---|---|---|---|
qazisaad/news_recommendations_base | 2023-10-09T13:53:49.000Z | [
"region:us"
] | qazisaad | null | null | null | 0 | 3 | ---
dataset_info:
features:
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dtype: string
- name: sub-category
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dtype: timestamp[ns]
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splits:
- name: train
num_bytes: 1561817
num_examples: 3981
download_size: 742112
dataset... |
W1lson/testt | 2023-10-09T14:55:31.000Z | [
"region:us"
] | W1lson | null | null | null | 0 | 3 | ---
dataset_info:
features:
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dtype: string
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num_bytes: 4499
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dataset_size: 4499
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Ca... |
micklerj/comp-com | 2023-10-09T19:30:37.000Z | [
"license:other",
"region:us"
] | micklerj | null | null | null | 0 | 3 | ---
license: other
license_name: license
license_link: LICENSE
---
|
owanr/gpt-vs-human-annots | 2023-10-10T02:31:36.000Z | [
"license:apache-2.0",
"region:us"
] | owanr | null | null | null | 0 | 3 | ---
license: apache-2.0
---
|
ilyas3141/ilias_test5 | 2023-10-09T17:53:13.000Z | [
"region:us"
] | ilyas3141 | null | null | null | 0 | 3 | Entry not found |
ilyas3141/ilias_test12 | 2023-10-09T19:18:41.000Z | [
"region:us"
] | ilyas3141 | null | null | null | 0 | 3 | Entry not found |
ariesta/forensic-datasets-tuning | 2023-10-09T23:22:20.000Z | [
"region:us"
] | ariesta | null | null | null | 0 | 3 | Entry not found |
xinei/my_dataset | 2023-10-10T06:01:19.000Z | [
"license:lgpl-3.0",
"region:us"
] | xinei | null | null | null | 0 | 3 | ---
license: lgpl-3.0
---
|
JzJd/post-flink | 2023-10-10T08:38:46.000Z | [
"license:afl-3.0",
"region:us"
] | JzJd | null | null | null | 0 | 3 | ---
license: afl-3.0
---
|
code_x_glue_cc_cloze_testing_all | 2023-06-01T14:59:51.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:slot-filling",
"annotations_creators:found",
"language_creators:found",
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"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:code",
"license:c-uda",... | null | Cloze tests are widely adopted in Natural Languages Processing to evaluate the performance of the trained language models. The task is aimed to predict the answers for the blank with the context of the blank, which can be formulated as a multi-choice classification problem.
Here we present the two cloze testing dataset... | @article{CodeXGLUE,
title={CodeXGLUE: An Open Challenge for Code Intelligence},
journal={arXiv},
year={2020},
}
@article{feng2020codebert,
title={CodeBERT: A Pre-Trained Model for Programming and Natural Languages},
author={Feng, Zhangyin and Guo, Daya and Tang, Duyu and Duan, Nan and Feng, Xiaocheng and Gong, Ming and... | null | 3 | 2 | ---
annotations_creators:
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- code
license:
- c-uda
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source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- slot-filling
pretty_name: CodeXGlueCcClozeTestingAll
dataset_info:... |
code_x_glue_cc_cloze_testing_maxmin | 2023-06-01T14:59:51.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:slot-filling",
"annotations_creators:found",
"language_creators:found",
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"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:code",
"license:c-uda",... | null | Cloze tests are widely adopted in Natural Languages Processing to evaluate the performance of the trained language models. The task is aimed to predict the answers for the blank with the context of the blank, which can be formulated as a multi-choice classification problem.
Here we present the two cloze testing dataset... | @article{CodeXGLUE,
title={CodeXGLUE: An Open Challenge for Code Intelligence},
journal={arXiv},
year={2020},
}
@article{feng2020codebert,
title={CodeBERT: A Pre-Trained Model for Programming and Natural Languages},
author={Feng, Zhangyin and Guo, Daya and Tang, Duyu and Duan, Nan and Feng, Xiaocheng and Gong, Ming and... | null | 1 | 2 | ---
annotations_creators:
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- found
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- code
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- c-uda
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size_categories:
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source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- slot-filling
pretty_name: CodeXGlueCcClozeTestingMaxmin
dataset_in... |
eu_regulatory_ir | 2022-11-18T20:01:28.000Z | [
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"document-to-document-retrieval",
"arxiv:21... | null | EURegIR: Regulatory Compliance IR (EU/UK) | @inproceedings{chalkidis-etal-2021-regir,
title = "Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations",
author = "Chalkidis, Ilias and Fergadiotis, Emmanouil and Manginas, Nikos and Katakalou, Eva, and Malakasiotis, Prodromos",
... | null | 1 | 2 | ---
annotations_creators:
- found
language_creators:
- found
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- en
license:
- cc-by-nc-sa-4.0
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- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-retrieval
task_ids:
- document-retrieval
paperswithcode_id: null
pretty_name: the RegIR datasets
tags:
-... |
igbo_ner | 2022-11-03T16:16:30.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ig",
"license:unknown",
"arxiv:2004.00648",
"region:us"
] | null | Igbo Named Entity Recognition Dataset | @misc{ezeani2020igboenglish,
title={Igbo-English Machine Translation: An Evaluation Benchmark},
author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},
year={2020},
eprint={2004.00648},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | null | 0 | 2 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ig
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: null
pretty_name: Igbo NER dataset
datas... |
multi_re_qa | 2023-06-01T14:59:53.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"annotations_creators:found",
"language_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categ... | null | MultiReQA contains the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA. Five of these datasets, including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, contain both training and te... | @misc{m2020multireqa,
title={MultiReQA: A Cross-Domain Evaluation for Retrieval Question Answering Models},
author={Mandy Guo and Yinfei Yang and Daniel Cer and Qinlan Shen and Noah Constant},
year={2020},
eprint={2005.02507},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | null | 0 | 2 | ---
annotations_creators:
- expert-generated
- found
language_creators:
- expert-generated
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 10K<n<100K
- 1K<n<10K
- 1M<n<10M
source_datasets:
- extended|other-BioASQ
- extended|other-DuoRC
- extended|other-HotpotQA
- ... |
ncslgr | 2022-11-03T16:16:28.000Z | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:n<1K",
"source_datasets:original",
"language:ase",
"language:en",
"license:mit",
"region:us"
] | null | A small corpus of American Sign Language (ASL) video data from native signers, annotated with non-manual features. | @misc{dataset:databases2007volumes,
title={Volumes 2--7},
author={Databases, NCSLGR},
year={2007},
publisher={American Sign Language Linguistic Research Project (Distributed on CD-ROM~…}
} | null | 4 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ase
- en
license:
- mit
multilinguality:
- translation
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: NCSLGR
dataset_info:
- config_name: e... |
norec | 2023-01-25T14:41:38.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:nb",
"language:nn",
"language:no",
"license:cc-by-nc-... | null | NoReC was created as part of the SANT project (Sentiment Analysis for Norwegian Text), a collaboration between the Language Technology Group (LTG) at the Department of Informatics at the University of Oslo, the Norwegian Broadcasting Corporation (NRK), Schibsted Media Group and Aller Media. This first release of the co... | @InProceedings{VelOvrBer18,
author = {Erik Velldal and Lilja Ovrelid and
Eivind Alexander Bergem and Cathrine Stadsnes and
Samia Touileb and Fredrik Jorgensen},
title = {{NoReC}: The {N}orwegian {R}eview {C}orpus},
booktitle = {Proceedings of the 11th edition of the
Language... | null | 1 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- nb
- nn
- 'no'
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: norec
pretty_... |
norne | 2023-01-25T14:41:42.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:no",
"license:other",
"arxiv:1911.12146",
"re... | null | NorNE is a manually annotated
corpus of named entities which extends the annotation of the existing
Norwegian Dependency Treebank. Comprising both of the official standards of
written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000
tokens and annotates a rich set of entity types including persons,
or... | @inproceedings{johansen2019ner,
title={NorNE: Annotating Named Entities for Norwegian},
author={Fredrik Jørgensen, Tobias Aasmoe, Anne-Stine Ruud Husevåg,
Lilja Øvrelid, and Erik Velldal},
booktitle={LREC 2020},
year={2020},
url={https://arxiv.org/abs/1911.12146}
} | null | 1 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- 'no'
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: 'NorNE: Norwegian Named Enti... |
reasoning_bg | 2022-11-03T16:31:39.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:bg",
"license:apache-2.0",
"arxiv:1908.01519",
"region:us"
] | null | This new dataset is designed to do reading comprehension in Bulgarian language. | @article{hardalov2019beyond,
title={Beyond english-only reading comprehension: Experiments in zero-shot multilingual transfer for bulgarian},
author={Hardalov, Momchil and Koychev, Ivan and Nakov, Preslav},
journal={arXiv preprint arXiv:1908.01519},
year={2019}
} | null | 0 | 2 | ---
annotations_creators:
- found
language_creators:
- found
language:
- bg
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: null
pretty_name: ReasoningBg
dataset_info:
- confi... |
sharc_modified | 2022-11-03T16:31:23.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|sharc",
"language:en",
"license:unknow... | null | ShARC, a conversational QA task, requires a system to answer user questions based on rules expressed in natural language text. However, it is found that in the ShARC dataset there are multiple spurious patterns that could be exploited by neural models. SharcModified is a new dataset which reduces the patterns identifie... | @inproceedings{verma-etal-2020-neural,
title = "Neural Conversational {QA}: Learning to Reason vs Exploiting Patterns",
author = "Verma, Nikhil and
Sharma, Abhishek and
Madan, Dhiraj and
Contractor, Danish and
Kumar, Harshit and
Joshi, Sachindra",
booktitle = "Proceedings ... | null | 0 | 2 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|sharc
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: null
pretty_na... |
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},
... | null | 0 | 2 | ---
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
... |
telugu_books | 2022-11-03T16:07:57.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"lang... | null | This dataset is created by scraping telugu novels from teluguone.com this dataset can be used for nlp tasks like topic modeling, word embeddings, transfer learning etc | @InProceedings{huggingface:dataset,
title = {Indic NLP - Natural Language Processing for Indian Languages},
authors = {Sudalai Rajkumar, Anusha Motamarri},
year={2019}
} | null | 1 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- te
license:
- unknown
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_i... |
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}}
} | null | 0 | 2 | ---
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... |
un_ga | 2023-06-01T14:59:53.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:translation",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ar",
"language:en",
"language:es",
"language:fr",
"language:ru",
"language:zh",
"license:unknown",
"reg... | null | United nations general assembly resolutions: A six-language parallel corpus.
This is a collection of translated documents from the United Nations originally compiled into a translation memory by Alexandre Rafalovitch, Robert Dale (see http://uncorpora.org).
6 languages, 15 bitexts
total number of files: 6
total number ... | @inproceedings{title = "United Nations General Assembly Resolutions: a six-language parallel corpus",
abstract = "In this paper we describe a six-ways parallel public-domain corpus consisting of 2100 United Nations General Assembly Resolutions with translations in the six official languages of the United Nations, with ... | null | 0 | 2 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
- en
- es
- fr
- ru
- zh
license:
- unknown
multilinguality:
- translation
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: UnGa
dataset_info:
- config_na... |
AConsApart/anime_subtitles_DialoGPT | 2021-03-06T02:31:23.000Z | [
"region:us"
] | AConsApart | null | null | null | 1 | 2 | Entry not found |
ARTeLab/mlsum-it | 2022-11-17T02:51:00.000Z | [
"task_categories:summarization",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"language:it",
"region:us"
] | ARTeLab | null | null | null | 1 | 2 | ---
language:
- it
multilinguality:
- monolingual
size_categories:
- 10K<n<100k
task_categories:
- summarization
---
# Dataset Card for mlsum-it
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Lang... |
Abdo1Kamr/Arabic_Hadith | 2021-08-21T12:40:44.000Z | [
"region:us"
] | Abdo1Kamr | null | null | null | 0 | 2 | # Hadith-Data-Sets
There are two files of Hadith, the first one for all `hadith With Tashkil and Without Tashkel` from the Nine Books that are 62,169 Hadith.
The second one it `Hadith pre-processing` data, which is applyed normalization and removeing stop words and lemmatization on it
<!-- ## `All Hadith Books`: All Ha... |
Abirate/code_net_dataset | 2021-12-11T17:41:32.000Z | [
"region:us"
] | Abirate | null | null | null | 2 | 2 | Entry not found |
Annielytics/DoctorsNotes | 2021-05-07T14:35:26.000Z | [
"region:us"
] | Annielytics | null | null | null | 0 | 2 | Entry not found |
Atsushi/fungi_trait_circus_database | 2022-12-26T10:38:17.000Z | [
"annotations_creators:other",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"language:ja",
"license:cc-by-4.0",
"region:us"
] | Atsushi | null | null | null | 0 | 2 | ---
annotations_creators:
- other
language:
- en
- ja
multilinguality:
- multilingual
license:
- cc-by-4.0
source_datasets:
- original
size_categories:
- 100K<n<1M
---
fungi_trait_circus_database
大菌輪「Trait Circus」データセット（統制形質）
最終更新日：2022/12/26
====
### Languages
Japanese and English
Please do not use this data... |
Baybars/parla_text_corpus | 2022-10-21T15:29:15.000Z | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:various",
"multilinguality:monolingual",
"size_categories:100k<n<1M",
"source_datasets:found",
"language:ca",
"license:cc-by-4.0",
"robust-speech-event",
"region:us"
] | Baybars | null | null | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- various
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: ParlaTextCorpus
size_categories:
- 100k<n<1M
source_datasets:
- found
task_categories:
- sequence-modeling
task_ids:
- language-modeling
tags:
- robust-speech-event
---
... |
CodedotAI/code_clippy | 2022-11-17T19:54:28.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:code",
"license:gpl-3.0",
"arxiv:2107.03374",
"region:us"
] | CodedotAI | This dataset was generated by selecting GitHub repositories from a large collection of repositories. These repositories were collected from https://seart-ghs.si.usi.ch/ and Github portion of [The Pile](https://github.com/EleutherAI/github-downloader) (performed on July 7th, 2021). The goal of this dataset is to provide... | @misc{cooper-2021-code-clippy-data,
author = {Nathan Coooper, Artashes Arutiunian, Santiago Hincapié-Potes, Ben Trevett, Arun Raja, Erfan Hossami, Mrinal Mathur, and contributors},
title = {{Code Clippy Data: A large dataset of code data from Github for research into code language models}},
mon... | null | 10 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- code
license:
- gpl-3.0
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Code Clippy
---
# Dataset Card for Code Cl... |
Cropinky/rap_lyrics_english | 2021-07-21T03:07:36.000Z | [
"region:us"
] | Cropinky | null | null | null | 3 | 2 | ## Rap lyrics dataset
this is the repo containing the dataset we made for the hugging face community week, in order to download more songs you need to request and get(it's very simple and fast) your genius API key which ou put in the genius.py file<br/>
#TODO: turn it into an actual huggingface dataset |
CyranoB/polarity | 2022-10-25T08:54:09.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:1509.01626",
"regi... | CyranoB | The Amazon reviews dataset consists of reviews from amazon.
The data span a period of 18 years, including ~35 million reviews up to March 2013.
Reviews include product and user information, ratings, and a plaintext review. | @inproceedings{mcauley2013hidden,
title={Hidden factors and hidden topics: understanding rating dimensions with review text},
author={McAuley, Julian and Leskovec, Jure},
booktitle={Proceedings of the 7th ACM conference on Recommender systems},
pages={165--172},
year={2013}
} | null | 1 | 2 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: Amazon Review Polarity
---
# Da... |
DDSC/reddit-da | 2022-10-27T11:00:42.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:da",
"license:mit",
"region:us"
] | DDSC | null | null | null | 2 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- da
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Reddit-da
---
# Dataset Card for SQuAD-da
## Table of ... |
GEM/OrangeSum | 2022-09-03T18:26:49.000Z | [
"task_categories:summarization",
"annotations_creators:unknown",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:fr",
"license:other",
"region:us"
] | GEM | 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 ... | @inproceedings{kamal-eddine-etal-2021-barthez,
title = "{BART}hez: a Skilled Pretrained {F}rench Sequence-to-Sequence Model",
author = "Kamal Eddine, Moussa and
Tixier, Antoine and
Vazirgiannis, Michalis",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language... | null | 0 | 2 | ---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- fr
license:
- other
multilinguality:
- unknown
pretty_name: OrangeSum
size_categories:
- unknown
source_datasets:
- original
task_categories:
- summarization
task_ids:
- unknown
---
# Dataset Card for GEM/OrangeSum
## Dataset Description
- ... |
GEM/RiSAWOZ | 2022-10-24T15:30:01.000Z | [
"task_categories:conversational",
"annotations_creators:crowd-sourced",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:zh",
"license:cc-by-4.0",
"dialog-response-generation",
"region:us"
] | GEM | RiSAWOZ contains 11.2K human-to-human (H2H) multiturn semantically annotated dialogues, with more than 150K utterances spanning over 12 domains, which is larger than all previous annotated H2H conversational datasets.Both single- and multi-domain dialogues are constructed, accounting for 65% and 35%, respectively. | @inproceedings{quan-etal-2020-risawoz,
title = "{R}i{SAWOZ}: A Large-Scale Multi-Domain {W}izard-of-{O}z Dataset with Rich Semantic Annotations for Task-Oriented Dialogue Modeling",
author = "Quan, Jun and
Zhang, Shian and
Cao, Qian and
Li, Zizhong and
Xiong, Deyi",
booktitle = "... | null | 5 | 2 | ---
annotations_creators:
- crowd-sourced
language_creators:
- unknown
language:
- zh
license:
- cc-by-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: RiSAWOZ
tags:
- dialog-response-generation
---
# Dataset Card for GEM/... |
GEM/RotoWire_English-German | 2022-10-24T15:30:03.000Z | [
"task_categories:table-to-text",
"annotations_creators:automatically-created",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"language:de",
"license:cc-by-4.0",
"data-to-text",
"region:us"
] | GEM | Dataset for the WNGT 2019 DGT shared task on "Document-Level Generation and Translation”. | @article{hayashi2019findings,
title={Findings of the Third Workshop on Neural Generation and Translation},
author={Hayashi, Hiroaki and Oda, Yusuke and Birch, Alexandra and Konstas, Ioannis and Finch, Andrew and Luong, Minh-Thang and Neubig, Graham and Sudoh, Katsuhito},
journal={EMNLP-IJCNLP 2019},
pages={1},
... | null | 1 | 2 | ---
annotations_creators:
- automatically-created
language_creators:
- unknown
language:
- en
- de
license:
- cc-by-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
pretty_name: RotoWire_English-German
tags:
- data-to-text
---
# Dataset... |
GEM/SciDuet | 2022-10-24T15:30:06.000Z | [
"task_categories:other",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"text-to-slide",
"region:us"
] | GEM | SciDuet is the first publicaly available dataset for the challenging task of document2slides generation,
The dataset integrated into GEM is the ACL portion of the whole dataset described in "https://aclanthology.org/2021.naacl-main.111.pdf".
It contains the full Dev and Test sets, and a portion of the Train dataset.
W... | @inproceedings{sun-etal-2021-d2s,
title = "{D}2{S}: Document-to-Slide Generation Via Query-Based Text Summarization",
author = "Sun, Edward and
Hou, Yufang and
Wang, Dakuo and
Zhang, Yunfeng and
Wang, Nancy X. R.",
booktitle = "Proceedings of the 2021 Conference of the North Amer... | null | 1 | 2 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- apache-2.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids: []
pretty_name: SciDuet
tags:
- text-to-slide
---
# Dataset Card for GEM/SciDuet
## Dataset Descriptio... |
GEM/Taskmaster | 2022-10-24T15:30:09.000Z | [
"task_categories:conversational",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"dialog-response-generation",
"arxiv:2012.12458",
"region:us"
] | GEM | The Taskmaster-3 (aka TicketTalk) dataset consists of 23,789 movie ticketing dialogs
(located in Taskmaster/TM-3-2020/data/). By "movie ticketing" we mean conversations
where the customer's goal is to purchase tickets after deciding on theater, time,
movie name, number of tickets, and date, or opt out of the transactio... | @article{byrne2020tickettalk,
title={TicketTalk: Toward human-level performance with end-to-end, transaction-based dialog systems},
author={Byrne, Bill and Krishnamoorthi, Karthik and Ganesh, Saravanan and Kale, Mihir Sanjay},
journal={arXiv preprint arXiv:2012.12458},
year={2020}
} | null | 1 | 2 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- cc-by-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: Taskmaster
tags:
- dialog-response-generation
---
# Dataset Card for GEM/Taskma... |
GEM/cs_restaurants | 2022-10-24T15:30:14.000Z | [
"task_categories:conversational",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:cs",
"license:cc-by-sa-4.0",
"dialog-response-generation",
"region:us"
] | GEM | The task is generating responses in the context of a (hypothetical) dialogue
system that provides information about restaurants. The input is a basic
intent/dialogue act type and a list of slots (attributes) and their values.
The output is a natural language sentence. | @inproceedings{cs_restaurants,
address = {Tokyo, Japan},
title = {Neural {Generation} for {Czech}: {Data} and {Baselines}},
shorttitle = {Neural {Generation} for {Czech}},
url = {https://www.aclweb.org/anthology/W19-8670/},
urldate = {2019-10-18},
booktitle = {Proceedings of the 12th {International} {Conference} ... | null | 1 | 2 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- cs
license:
- cc-by-sa-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: cs_restaurants
tags:
- dialog-response-generation
---
# Dataset Card for GEM... |
GEM/dstc10_track2_task2 | 2022-10-24T15:30:17.000Z | [
"task_categories:conversational",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"dialog-response-generation",
"region:us"
] | GEM | \ | @article{kim2020domain,
title={Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access},
author={Seokhwan Kim and Mihail Eric and Karthik Gopalakrishnan and Behnam Hedayatnia and Yang Liu and Dilek Hakkani-Tur},
journal={arXiv preprint arXiv:2006.03533}
year={2020}
} | null | 4 | 2 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- apache-2.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: dstc10_track2_task2
tags:
- dialog-response-generation
---
# Dataset Card for ... |
GEM/surface_realisation_st_2020 | 2022-10-24T15:30:30.000Z | [
"task_categories:table-to-text",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:ar",
"language:zh",
"language:en",
"language:fr",
"language:hi",
"language:id",
"language:ja",
"language:ko... | GEM | null | null | null | 0 | 2 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- ar
- zh
- en
- fr
- hi
- id
- ja
- ko
- pt
- ru
- es
license:
- cc-by-2.5
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
pretty_name: surface_realisation_st_2020
tag... |
GEM-submissions/GEM__bart_base_schema_guided_dialog__1645547915 | 2022-02-22T16:38:38.000Z | [
"benchmark:gem",
"region:us"
] | GEM-submissions | null | null | null | 0 | 2 | ---
benchmark: gem
type: prediction
submission_name: BART_BASE_schema_guided_dialog
---
|
GEM-submissions/lewtun__hugging-face-test-t5-base.outputs.json-36bf2a59__1646049601 | 2022-02-28T12:00:08.000Z | [
"benchmark:gem",
"region:us"
] | GEM-submissions | null | null | null | 0 | 2 | ---
benchmark: gem
type: prediction
submission_name: Hugging Face test T5-base.outputs.json 36bf2a59
---
|
GroNLP/ik-nlp-22_winemag | 2022-02-13T11:03:27.000Z | [
"license:cc-by-sa-4.0",
"region:us"
] | GroNLP | null | null | null | 3 | 2 | ---
license: cc-by-sa-4.0
---
|
Jeska/autonlp-data-vaccinfaq | 2021-10-19T12:06:57.000Z | [
"task_categories:text-classification",
"region:us"
] | Jeska | null | null | null | 0 | 2 | ---
task_categories:
- text-classification
---
# AutoNLP Dataset for project: vaccinfaq
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#dat... |
khondoker/SentNoB | 2023-04-23T10:32:36.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:bn",
"region:us"
] | khondoker | null | null | null | 0 | 2 | ---
language:
- bn
task_categories:
- text-classification
pretty_name: SentNoB
task_ids:
- sentiment-classification
annotations_creators:
- expert-generated
language_creators:
- expert-generated
paperswithcode_id: sentnob
---
# Dataset Card for "SentNoB"
### Dataset Summary
Social Media User Comments' Sentiment Anal... |
Langame/starter | 2022-12-06T18:54:01.000Z | [
"task_categories:text-generation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | Langame | null | null | null | 0 | 2 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- expert-generated
license:
- mit
multilinguality:
- monolingual
pretty_name: ''
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-generation
task_ids: []
---
# Dataset Card for [Dataset Name]
## Table of Cont... |
Llamacha/monolingual-quechua-iic | 2022-10-02T14:40:00.000Z | [
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<5M",
"source_datasets:original",
"language:qu",
"license:apache-2.0",
"regi... | Llamacha | null | null | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- qu
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 1M<n<5M
source_datasets:
- original
task_categories:
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
---
# Dataset Card for Monolingual... |
Motahar/github-issues | 2022-10-25T09:06:29.000Z | [
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:document-retrieval",
"task_ids:multi-label-classification",
"task_ids:multi-class-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unkno... | Motahar | null | null | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: Huggingface Datasets github issues
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-retrieval
- text-classification
task_ids:
- document-retrie... |
NLPC-UOM/English-Tamil-Parallel-Corpus | 2022-05-20T03:28:51.000Z | [
"region:us"
] | NLPC-UOM | null | null | null | 0 | 2 | ---
annotations_creators: []
languages:
- si
licenses:
- mit
---
# English-Tamil parallel Corpus prepared by the National Languages Processing Center, University of Moratuwa. The data has been cleaned and then aligned.
#En-Ta Glossary Line Count : 22477
#En-Ta Corpus Line Count : 8950
#Source: Data extracted from pu... |
NbAiLab/NPSC_test | 2022-11-07T12:37:31.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:2G<n<1B",
"source_datasets:original",
"language:nb",
"language:no",
"language:nn",
"license:cc0... | NbAiLab | null | null | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- nb
- 'no'
- nn
license:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 2G<n<1B
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- audio-classification
task_ids:
- speech-modeling
pretty_name: NPSC
ta... |
Nuwaisir/Quran_speech_recognition_kaggle | 2022-02-20T13:07:06.000Z | [
"region:us"
] | Nuwaisir | null | null | null | 0 | 2 | This dataset can be found in Kaggle |
Recognai/corrected_labels_ag_news | 2021-12-29T16:57:56.000Z | [
"region:us"
] | Recognai | null | null | null | 0 | 2 | Entry not found |
SaulLu/Natural_Questions_HTML | 2021-08-27T18:58:58.000Z | [
"region:us"
] | SaulLu | null | null | null | 0 | 2 | This is a dataset extracted from the Natural Questions dataset
This dataset is currently under development |
Shushant/NepaliSentiment | 2022-01-07T05:12:33.000Z | [
"region:us"
] | Shushant | null | null | null | 2 | 2 | Entry not found |
SoLID/shellcode_i_a32 | 2022-11-17T19:53:43.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language_creators:found",
"multilinguality:translation",
"size_categories:unknown",
"source_datasets:original",
"language:code",
"language:en",
"licens... | SoLID | Shellcode_IA32 is a dataset for shellcode generation from English intents. The shellcodes are compilable on Intel Architecture 32-bits. | @inproceedings{liguori-etal-2021-shellcode,
title = "{S}hellcode{\_}{IA}32: A Dataset for Automatic Shellcode Generation",
author = "Liguori, Pietro and
Al-Hossami, Erfan and
Cotroneo, Domenico and
Natella, Roberto and
Cukic, Bojan and
Shaikh, Samira",
booktitle = "Pro... | null | 4 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- found
language:
- code
- en
license:
- gpl-3.0
multilinguality:
- translation
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
paperswithcode_id: shellcode-ia32
---... |
TRoboto/names | 2022-01-29T16:33:25.000Z | [
"license:cc-by-4.0",
"region:us"
] | TRoboto | List of Arabic first names with meaning and origin of most names | @software{Al-Fetyani_Maha_Processing_Library_2021,
author = {Al-Fetyani, Mohammad},
month = {11},
title = {{Maha Processing Library}},
url = {https://github.com/TRoboto/Maha},
year = {2021}
} | null | 1 | 2 | ---
project: Maha
license: cc-by-4.0
---
## Dataset Summary
It includes list of Arabic names with meaning and origin of most names
|
Wikidepia/IndoParaCrawl | 2021-04-13T10:22:22.000Z | [
"region:us"
] | Wikidepia | null | null | null | 2 | 2 | # IndoParaCrawl
IndoParaCrawl is ParaCrawl v7.1 dataset bulk-translated to Indonesian using Google Translate.
Thanks HuggingFace for providing free storage for datasets <3.
|
XiangPan/snli_break | 2021-09-20T05:45:54.000Z | [
"region:us"
] | XiangPan | The SNLI corpus (version 1.0) is a collection of 570k human-written English
sentence pairs manually labeled for balanced classification with the labels
entailment, contradiction, and neutral, supporting the task of natural language
inference (NLI), also known as recognizing textual entailment (RTE). | null | null | 0 | 2 | Entry not found |
addy88/nq-question-answeronly | 2021-12-14T13:59:58.000Z | [
"region:us"
] | addy88 | null | null | null | 1 | 2 | Entry not found |
albertvillanova/carbon_24 | 2022-10-24T15:25:03.000Z | [
"task_categories:other",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:other-crystallography",
"size_categories:unknown",
"language:cif",
"license:mit",
"material-property-optimization",
"material-reconstruction",
"material-generation",
"arxiv:... | albertvillanova | null | null | null | 0 | 2 | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- cif
license:
- mit
multilinguality:
- other-crystallography
size_categories:
- unknown
source_datasets: []
task_categories:
- other
task_ids: []
pretty_name: Carbon-24
tags:
- material-property-optimization
- material-recon... |
albertvillanova/sat | 2022-10-24T15:25:54.000Z | [
"task_categories:text-generation",
"task_categories:translation",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:translation",
"size_categories:1M<n<10M",
"source_datasets:original",
"source_datasets:extended|bible_para",
"source_datasets:extended|kde4",
"source_... | albertvillanova | SAT (Style Augmented Translation) dataset contains roughly 3.3 million English-Vietnamese pairs of texts. | \ | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
- vi
license:
- unknown
multilinguality:
- translation
size_categories:
- 1M<n<10M
source_datasets:
- original
- extended|bible_para
- extended|kde4
- extended|opus_gnome
- extended|open_subtitles
- extended|tatoeba
task_categories:
- t... |
anton-l/superb | 2022-07-04T10:48:08.000Z | [
"task_ids:keyword-spotting",
"task_ids:speaker-identification",
"task_ids:intent-classification",
"task_ids:slot-filling",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"source_datasets:extended|libris... | anton-l | Self-supervised learning (SSL) has proven vital for advancing research in
natural language processing (NLP) and computer vision (CV). The paradigm
pretrains a shared model on large volumes of unlabeled data and achieves
state-of-the-art (SOTA) for various tasks with minimal adaptation. However, the
speech processing co... | @article{DBLP:journals/corr/abs-2105-01051,
author = {Shu{-}Wen Yang and
Po{-}Han Chi and
Yung{-}Sung Chuang and
Cheng{-}I Jeff Lai and
Kushal Lakhotia and
Yist Y. Lin and
Andy T. Liu and
Jiatong Shi and
... | null | 1 | 2 | ---
annotations_creators:
- other
language_creators:
- other
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: SUPERB
size_categories:
- unknown
source_datasets:
- original
- extended|librispeech_asr
- extended|other-librimix
- extended|other-speech_commands
task_categories:
- speech-process... |
asoroa/bsbasque | 2021-11-18T15:00:09.000Z | [
"region:us"
] | asoroa | BSBasque dataset. The text is extracted from the following domains:
https://www.berria.eus
https://eu.wikipedia.org
https://goiena.eus
https://www.argia.eus
https://goierri.hitza.eus | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | null | 0 | 2 | Entry not found |
badranx/opus_raw | 2022-01-28T14:19:19.000Z | [
"region:us"
] | badranx | mono corpus from http://www.opensubtitles.org/. Please check http://www.opensubtitles.org/ for the available corpora and licenses. | P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016) | null | 1 | 2 | ## Load mono corpora from OPUS
OPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from [opus.nlpl.eu](https://opus.nlpl.eu/). Please check [opus.nlpl.eu](https://opus.nlpl.eu/) for the available corpora and licenses. The targeted corpus is call... |
castorini/msmarco_v1_doc_doc2query-t5_expansions | 2022-07-02T19:16:12.000Z | [
"language:en",
"license:apache-2.0",
"region:us"
] | castorini | null | null | null | 0 | 2 | ---
language:
- en
license: apache-2.0
---
# Dataset Summary
The repo provides queries generated for the MS MARCO V1 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that ... |
castorini/msmarco_v1_doc_segmented_doc2query-t5_expansions | 2021-11-10T04:51:35.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | null | 0 | 2 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides queries generated for the MS MARCO V1 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea i... |
castorini/msmarco_v2_doc_doc2query-t5_expansions | 2021-11-11T17:41:32.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | null | 0 | 2 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides queries generated for the MS MARCO v2 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to ... |
castorini/msmarco_v2_doc_segmented_doc2query-t5_expansions | 2021-11-02T08:13:56.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | null | 0 | 2 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides queries generated for the MS MARCO v2 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic i... |
castorini/nq_gar-t5_expansions | 2023-10-10T18:58:22.000Z | [
"language:en",
"license:apache-2.0",
"region:us"
] | castorini | null | null | null | 1 | 2 | ---
language:
- "en"
license: "apache-2.0"
---
# Dataset Summary
The repo provides answer, title and sentence expansions for the Natural Questions corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
"predicted_answe... |
castorini/triviaqa_gar-t5_expansions | 2022-02-17T00:58:32.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | null | 0 | 2 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
... |
cestwc/cnn_dailymail-metaeval100 | 2022-01-07T10:55:08.000Z | [
"region:us"
] | cestwc | null | null | null | 0 | 2 | Entry not found |
clarin-pl/nkjp-pos | 2023-01-30T22:53:57.000Z | [
"task_categories:other",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:pl",
"license:gpl-3.0",
"structure-prediction",
"region:us"
] | clarin-pl | NKJP-POS tagging dataset. | null | null | 1 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- gpl-3.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids:
- part-of-speech
pretty_name: nkjp-pos
tags:
- structure-prediction
---
# nkjp-pos
## Descr... |
classla/janes_tag | 2022-10-25T07:31:04.000Z | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:part-of-speech",
"language:si",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | classla | The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent_id'),
list of tokens ('tokens'), list of normalised word forms ('norms'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos_tags... | null | null | 0 | 2 | ---
language:
- si
license:
- cc-by-sa-4.0
task_categories:
- other
task_ids:
- lemmatization
- part-of-speech
tags:
- structure-prediction
- normalization
- tokenization
---
The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the foll... |
classla/reldi_hr | 2022-10-25T07:30:56.000Z | [
"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 dataset contains 6339 training samples, 815 validation samples and 785 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 UPOS tags ('upos_tags'),
list of Multext-East tags ('xpos_tags), list ... | null | null | 0 | 2 | ---
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
---
This dataset is based on 3,871 Croatian tweets that were segmented into sentences, tokens, and annotated with normaliz... |
corypaik/coda | 2022-10-20T16:57:23.000Z | [
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:2110.08182",
"region:us"
] | corypaik | *The Color Dataset* (CoDa) is a probing dataset to evaluate the representation of visual properties in language models. CoDa consists of color distributions for 521 common objects, which are split into 3 groups: Single, Multi, and Any. | @misc{paik2021world,
title={The World of an Octopus: How Reporting Bias Influences a Language Model's Perception of Color},
author={Cory Paik and Stéphane Aroca-Ouellette and Alessandro Roncone and Katharina Kann},
year={2021},
eprint={2110.08182},
archivePrefix={arXiv},
primaryClass... | null | 2 | 2 | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- en
language_bcp47:
- en-US
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: CoDa
paperswithcode_id: coda
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-scoring
task_ids:
- text-... |
damlab/HIV_PI | 2022-03-09T19:48:01.000Z | [
"license:mit",
"region:us"
] | damlab | null | null | null | 0 | 2 | ---
license: mit
---
# Dataset Description
## Dataset Summary
This dataset was derived from the Stanford HIV Genotype-Phenotype database and contains 1,733 HIV protease sequences. A
pproximately half of the sequences are resistant to at least one antiretroviral therapeutic (ART).
Supported Tasks and... |
davanstrien/embellishments-sample | 2022-02-24T15:44:29.000Z | [
"region:us"
] | davanstrien | null | null | null | 0 | 2 | Entry not found |
davanstrien/embellishments | 2022-01-10T16:59:02.000Z | [
"region:us"
] | davanstrien | null | null | null | 0 | 2 | Entry not found |
DebateLabKIT/deepa2 | 2022-12-16T14:49:35.000Z | [
"task_categories:text-retrieval",
"task_categories:text-generation",
"task_ids:text-simplification",
"task_ids:parsing",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:unknown",
"language:en",
"license:other",
"argument-mining",
"summarization",
"conditional-text-ge... | DebateLabKIT | null | null | null | 3 | 2 | ---
annotations_creators: []
language_creators:
- other
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets: []
task_categories:
- text-retrieval
- text-generation
task_ids:
- text-simplification
- parsing
pretty_name: deepa2
tags:
- argument-mining
- summarization
... |
DFKI-SLT/mobie | 2022-10-24T06:32:09.000Z | [
"task_categories:other",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"structure-prediction",
"region:us"
] | DFKI-SLT | MobIE is a German-language dataset which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities. The dataset consists of 3,232 social media texts and traffic reports with 91K tokens, and contains 20.5K annotated entities, 13.1K of which are l... | @inproceedings{hennig-etal-2021-mobie,
title = "{M}ob{IE}: A {G}erman Dataset for Named Entity Recognition, Entity Linking and Relation Extraction in the Mobility Domain",
author = "Hennig, Leonhard and
Truong, Phuc Tran and
Gabryszak, Aleksandra",
booktitle = "Proceedings of the 17th ... | null | 0 | 2 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- de
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- other
task_ids:
- named-entity-recognition
paperswithcode_id: mobie
pretty_name: MobIE
tags:
- structure... |
dragosnicolae555/RoITD | 2022-10-25T09:07:43.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:ro-RO",
"license:cc-by-4.0",
"region:us"
] | dragosnicolae555 | null | null | null | 0 | 2 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ro-RO
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'RoITD: Romanian IT Question Answering Dataset'
size_categories:
- unknown
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractiv... |
dram-conflict/horror-scripts | 2022-02-21T16:26:48.000Z | [
"region:us"
] | dram-conflict | This dataset is designed to generate scripts. | null | null | 0 | 2 | Entry not found |
enelpol/czywiesz | 2022-10-25T09:07:45.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:unknown",
"region:us"
] | enelpol | null | null | null | 2 | 2 | ---
language:
- pl
license:
- unknown
multilinguality:
- monolingual
pretty_name: Czywiesz
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
---
This is an extract of the original [Czywiesz](https://clarin-pl.eu/dspace/handle/11321/39) dataset. I... |
erwanlc/cocktails_recipe | 2022-10-25T09:17:00.000Z | [
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:2M<n<3M",
"language:en",
"license:other",
"region:us"
] | erwanlc | null | null | null | 2 | 2 | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 2M<n<3M
source_datasets: []
task_categories: []
task_ids: []
pretty_name: cocktails_recipe
language_bcp47:
- en
- en-US
---
# Dataset Card for cocktails... |
evageon/IADD | 2022-01-29T11:16:17.000Z | [
"license:cc-by-4.0",
"region:us"
] | evageon | null | null | null | 0 | 2 | ---
license: cc-by-4.0
---
# IADD
IADD is an Integrated Dataset for Arabic Dialect iDentification Dataset. It contains 136,317 texts representing 5 regions (Maghrebi (MGH) , Levantine (LEV), Egypt (EGY) , Iraq (IRQ) and Gulf (GLF)) and 9 countries (Algeria, Morocco, Tunisia, Palestine, Jordan, Syria, Lebanon, Egy... |
flax-community/german_common_crawl | 2023-10-02T16:46:37.000Z | [
"language:de",
"region:us"
] | flax-community | German Only Extract from Common Crawl
This Dataset is for pretraining a German Language Model (Unsupervised) or tune a Multilingual Model specifically to German | @inproceedings{wenzek2020ccnet,
title={CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data},
author={Wenzek, Guillaume and Lachaux, Marie-Anne and Conneau, Alexis and Chaudhary, Vishrav and Guzm{\'a}n, Francisco and Joulin, Armand and Grave, {\'E}douard},
booktitle={Proceedings of The 12th Lan... | null | 0 | 2 | ---
language:
- de
---
The dataset script is more or less ready and one file has correctly been converted so far: `https://opendata.iisys.de/systemintegration/Datasets/CommonCrawl/head/de_head_0000_2015-48.tar.gz`
You can try downloading the file as follows:
```python
from datasets import load_dataset
ds = load_datas... |
flexthink/ljspeech | 2022-02-06T00:09:16.000Z | [
"region:us"
] | flexthink | This is a public domain speech dataset consisting of 13,100 short audio
clips of a single speaker reading passages from 7 non-fiction books. A
transcription is provided for each clip. Clips vary in length from 1 to 10
seconds and have a total length of approximately 24 hours. | null | null | 1 | 2 | # The LJ Speech Dataset
Version 1.0
July 5, 2017
https://keithito.com/LJ-Speech-Dataset
# Overview
This is a public domain speech dataset consisting of 13,100 short audio clips
of a single speaker reading passages from 7 non-fiction books. A transcription
is provided for each clip. Clips vary in length from 1 to 10... |
giganticode/java-cmpx | 2022-07-01T20:33:03.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"multilinguality:monolingual",
"size_categories:unknown",
"language:java",
"license:mit",
"region:us"
] | giganticode | null | null | null | 0 | 2 | ---
language:
- java
license:
- mit
multilinguality:
- monolingual
pretty_name:
- java-cmpx
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- multi-class-classification
---
|
gorkemgoknar/tr_ted_talk_translated | 2022-01-13T09:14:54.000Z | [
"language:tr",
"license:apache-2.0",
"dataset",
"turkish",
"ted-multi",
"cleaned",
"region:us"
] | gorkemgoknar | null | null | null | 1 | 2 | ---
language:
- tr
thumbnail:
tags:
- dataset
- turkish
- ted-multi
- cleaned
license: apache-2.0
datasets:
- ted-multi
---
# Turkish Ted talk translations
# Created from ted-multi dataset
adding processing steps here if you want another language
```python
#using Turkish as target
target_lang="tr" # change to y... |
huggingartists/architects | 2022-10-25T09:23:24.000Z | [
"language:en",
"huggingartists",
"lyrics",
"region:us"
] | huggingartists | This dataset is designed to generate lyrics with HuggingArtists. | @InProceedings{huggingartists:dataset,
title = {Lyrics dataset},
author={Aleksey Korshuk
},
year={2021}
} | null | 1 | 2 | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/architects"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How ... |
huggingartists/bob-dylan | 2022-10-25T09:25:08.000Z | [
"language:en",
"huggingartists",
"lyrics",
"region:us"
] | huggingartists | This dataset is designed to generate lyrics with HuggingArtists. | @InProceedings{huggingartists:dataset,
title = {Lyrics dataset},
author={Aleksey Korshuk
},
year={2021}
} | null | 0 | 2 | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/bob-dylan"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How t... |
huggingartists/mikhail-krug | 2022-10-25T09:39:07.000Z | [
"language:en",
"huggingartists",
"lyrics",
"region:us"
] | huggingartists | This dataset is designed to generate lyrics with HuggingArtists. | @InProceedings{huggingartists:dataset,
title = {Lyrics dataset},
author={Aleksey Korshuk
},
year={2021}
} | null | 0 | 2 | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/mikhail-krug"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Ho... |
huggingartists/pyrokinesis | 2022-10-25T09:42:04.000Z | [
"language:en",
"huggingartists",
"lyrics",
"region:us"
] | huggingartists | This dataset is designed to generate lyrics with HuggingArtists. | @InProceedings{huggingartists:dataset,
title = {Lyrics dataset},
author={Aleksey Korshuk
},
year={2021}
} | null | 0 | 2 | ---
language:
- en
tags:
- huggingartists
- lyrics
---
# Dataset Card for "huggingartists/pyrokinesis"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [How... |
image-search-2/unsplash_lite_image_dataset | 2021-11-19T12:44:46.000Z | [
"region:us"
] | image-search-2 | null | null | null | 1 | 2 | # The Unsplash Dataset
The Unsplash Dataset is made up of over 250,000+ contributing global photographers and data sourced from hundreds of millions of searches across a nearly unlimited number of uses and contexts. Due to the breadth of intent and ... |
jamescalam/climate-fever-similarity | 2021-12-18T09:24:24.000Z | [
"region:us"
] | jamescalam | null | null | null | 0 | 2 | Entry not found |
jegormeister/dutch-snli | 2023-10-02T19:06:35.000Z | [
"language:nl",
"region:us"
] | jegormeister | This is the Dutch version of the original SNLI dataset. The translation was performed using Google Translate. Original SNLI available at https://nlp.stanford.edu/projects/snli/ | null | null | 0 | 2 | ---
language:
- nl
---
This is a translated version of SNLI in Dutch. The translation was performed using Google Translate. |
jgammack/SAE-door-abstracts | 2022-10-22T08:23:24.000Z | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | jgammack | null | null | null | 0 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
language_bcp47:
- en-US
license:
- unknown
multilinguality:
- monolingual
pretty_name: SAE-door-abstracts
size_categories:
- unknown
source_datasets:
- original
task_categories:
- sequence-modeling
task_ids:
- language-modeli... |
jonfd/ICC | 2022-10-22T15:15:16.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100M<n<1B",
"source_datasets:original",
"language:is",
"license:cc-by-4.0",
"region:us"
] | jonfd | null | null | null | 1 | 2 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- is
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100M<n<1B
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: ICC
---
# Dataset Card for ICC
## Table of Cont... |
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