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

Open Access
Authors
Publication date 27-06-2023
Edition v4
Number of pages 73
Publisher ArXiv
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR)
Abstract
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 widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License.
Document type Preprint
Note Versions v1 and v2 (2022) and v3 (2023) also available on ArXiv.
Language English
Published at https://doi.org/10.48550/arXiv.2211.05100
Downloads
BLOOM (Final published version)
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