Poster
The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Hugo Laurençon · Lucile Saulnier · Thomas Wang · Christopher Akiki · Albert Villanova del Moral · Teven Le Scao · Leandro Von Werra · Chenghao Mou · Eduardo González Ponferrada · Huu Nguyen · Jörg Frohberg · Mario Šaško · Quentin Lhoest · Angelina McMillan-Major · Gerard Dupont · Stella Biderman · Anna Rogers · Loubna Ben allal · Francesco De Toni · Giada Pistilli · Olivier Nguyen · Somaieh Nikpoor · Maraim Masoud · Pierre Colombo · Javier de la Rosa · Paulo Villegas · Tristan Thrush · Shayne Longpre · Sebastian Nagel · Leon Weber · Manuel Muñoz · Jian Zhu · Daniel Van Strien · Zaid Alyafeai · Khalid Almubarak · Minh Chien Vu · Itziar Gonzalez-Dios · Aitor Soroa · Kyle Lo · Manan Dey · Pedro Ortiz Suarez · Aaron Gokaslan · Shamik Bose · David Adelani · Long Phan · Hieu Tran · Ian Yu · Suhas Pai · Jenny Chim · Violette Lepercq · Suzana Ilic · Margaret Mitchell · Sasha Alexandra Luccioni · Yacine Jernite
Hall J (level 1) #1012
Keywords: [ dataset ] [ Language Modeling ] [ BigScience ] [ Multilingual ]
As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed with the goal of researching and training large language models as a values-driven undertaking, putting issues of ethics, harm, and governance in the foreground. This paper documents the data creation and curation efforts undertaken by BigScience to assemble the Responsible Open-science Open-collaboration Text Sources (ROOTS) corpus, a 1.6TB dataset spanning 59 languages that was used to train the 176-billion-parameter BigScience Large Open-science Open-access Multilingual (BLOOM) language model. We further release a large initial subset of the corpus and analyses thereof, and hope to empower large-scale monolingual and multilingual modeling projects with both the data and the processing tools, as well as stimulate research around this large multilingual corpus.