Year: 2021
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Lhoest, Quentin, del Moral, Albert Villanova, Jernite, Yacine, Thakur, Abhishek, von Platen, Patrick, Patil, Suraj, Chaumond, Julien, Drame, Mariama, Plu, Julien, Tunstall, Lewis, Davison, Joe, Šaško, Mario, Chhablani, Gunjan, Malik, Bhavitvya, Brandeis, Simon, Scao, Teven Le, Sanh, Victor, Xu, Canwen, Patry, Nicolas, McMillan-Major, Angelina, Schmid, Philipp, Gugger, Sylvain, Delangue, Clément, Matussière, Théo, Debut, Lysandre, Bekman, Stas, Cistac, Pierric, Goehringer, Thibault, Mustar, Victor, Lagunas, François, Rush, Alexander M., Wolf, Thomas
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3213208261