2021.emnlp-demo.21@ACL

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#1 Datasets: A Community Library for Natural Language Processing [PDF] [Copy] [Kimi]

Authors: Quentin Lhoest ; Albert Villanova del Moral ; Yacine Jernite ; Abhishek Thakur ; Patrick von Platen ; Suraj Patil ; Julien Chaumond ; Mariama Drame ; Julien Plu ; Lewis Tunstall ; Joe Davison ; Mario Šaško ; Gunjan Chhablani ; Bhavitvya Malik ; Simon Brandeis ; Teven Le Scao ; Victor Sanh ; Canwen Xu ; Nicolas Patry ; Angelina McMillan-Major ; Philipp Schmid ; Sylvain Gugger ; Clément Delangue ; Théo Matussière ; Lysandre Debut ; Stas Bekman ; Pierric Cistac ; Thibault Goehringer ; Victor Mustar ; François Lagunas ; Alexander Rush ; Thomas Wolf

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.