BLOOM-7.1B

Training compute

1.5×10²² FLOP

Parameters

7.1B

Published

Jul 5, 2022

BLOOM-7.1B is an AI model developed by Hugging Face and BigScience (United States and France), first published in July 2022. It works in the language domain, on tasks such as language modeling/generation and translation.

Training it took an estimated 1.5×10²² FLOP of compute (estimation method: operation counting). The model has 7,070,000,000 parameters. It was trained on roughly 354B datapoints.

Access: Open weights (restricted use). Its weights are openly available. The reference paper has 2,917 citations. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Hugging Face, BigScience
Country of organization: United States, France
Domain: Language
Task: Language modeling/generation, Translation
Training compute: 1.5×10²² FLOP
Compute estimation method: Operation counting
Parameters: 7,070,000,000
Dataset size: 354B
Model accessibility: Open weights (restricted use)
Open weights: Yes
Citations: 2,917
Epoch confidence: Confident