activity
20222026
most citedStarCoder: may the source be with you!

200 citations · 352 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Benchmarking Automatic Speech Recognition Tools for Iberian Languages

Fernando López, Pablo Gómez, David Solans +2

Comprehensive evaluations of automatic speech recognition (ASR) for Iberian languages remain limited, and low-resource languages, biases, and efficiency trade-offs are underexplore…

cs.CL2023★ 200 cited

StarCoder: may the source be with you!

Raymond Li, Loubna Ben Allal, Yangtian Zi +64

The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase…

cs.CL2023★ 65 cited

The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset

Hugo Laurençon, Lucile Saulnier, Thomas Wang +51

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,…

cs.CL2023

The ROOTS Search Tool: Data Transparency for LLMs

Aleksandra Piktus, Christopher Akiki, Paulo Villegas +5

ROOTS is a 1.6TB multilingual text corpus developed for the training of BLOOM, currently the largest language model explicitly accompanied by commensurate data governance efforts.…

cs.SE2023★ 54 cited

SantaCoder: don't reach for the stars!

Loubna Ben Allal, Raymond Li, Denis Kocetkov +38

The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This tech report describes the progress of the col…

cs.CL2022

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience Workshop, :, Teven Le Scao +391

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…

cs.CL2022★ 33 cited

BERTIN: Efficient Pre-Training of a Spanish Language Model using Perplexity Sampling

Javier de la Rosa, Eduardo G. Ponferrada, Paulo Villegas +3

The pre-training of large language models usually requires massive amounts of resources, both in terms of computation and data. Frequently used web sources such as Common Crawl mig…