Datasets: A Community Library for Natural Language Processing

The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, vers...

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Published inarXiv.org
Main Authors Lhoest, Quentin, Albert Villanova del Moral, Jernite, Yacine, Thakur, Abhishek, Patrick von Platen, Patil, Suraj, Chaumond, Julien, Drame, Mariama, Plu, Julien, Tunstall, Lewis, Davison, Joe, Šaško, Mario, Chhablani, Gunjan, Malik, Bhavitvya, Brandeis, Simon, Teven Le Scao, Sanh, Victor, Xu, Canwen, Patry, Nicolas, McMillan-Major, Angelina, Schmid, Philipp, Gugger, Sylvain, Delangue, Clément, Matussière, Théo, Debut, Lysandre, Bekman, Stas, Cistac, Pierric, Thibault Goehringer, Mustar, Victor, Lagunas, François, Rush, Alexander M, Wolf, Thomas
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 07.09.2021
Subjects
Datasets
Libraries
Natural language processing
Research projects
User interfaces
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Summary:The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. Datasets aims to standardize end-user interfaces, versioning, and documentation, while providing a lightweight front-end that behaves similarly for small datasets as for internet-scale corpora. The design of the library incorporates a distributed, community-driven approach to adding datasets and documenting usage. After a year of development, the library now includes more than 650 unique datasets, has more than 250 contributors, and has helped support a variety of novel cross-dataset research projects and shared tasks. The library is available at https://github.com/huggingface/datasets.
ISSN:2331-8422