model_card
Repository for BLOOM Model Card, detailing multiple language support and training data.
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Decision brief
The model_card for BLOOM LM provides comprehensive details on the model architecture and usage in multiple languages, licensed under RAIL License v1.0.
Good fit when
- When detailed multilingual support across over 40 languages is necessary
- For projects requiring extensive documentation and transparency on language risks and evaluations
Avoid when
- If a more generalized, less transparent documentation approach suffices for the project's needs
- In scenarios where licensing under Apache-2.0 or other standard open-source licenses is preferred over RAIL License v1.0
Observed Jul 14, 2026 · Source: enrich:decision_facts
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Overview
This repository contains the model card for the BigScience Language Open-source Open-access Multilingual (BLOOM) Language Model, which supports over 40 languages. It provides details regarding model architecture, usage, risks, evaluations, and licensing under RAIL License v1.0.
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README
license: bigscience-bloom-rail-1.0 language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
DEPRECATED. This is now live at https://huggingface.co/bigscience/bloom . Please make additional changes there!
BLOOM LM
BigScience Large Open-science Open-access Multilingual Language Model
Model Card
Version 1.0 / 25.May.2022
Table of Contents
- Model Details
- Uses
- Training Data
- Risks and Limitations
- Evaluation
- Recommendations
- Glossary and Calculations
- More Information
- Model Card Authors
Model Details
Basics
This section provides information for anyone who wants to know about the model.
Click to expand
Developed by: BigScience (website)
- All collaborators are either volunteers or have an agreement with their employer. (Further breakdown of participants forthcoming.)
Model Type: Transformer-based Language Model
Version: 1.0.0
Languages: Multiple; see training data
License: RAIL License v1.0 (link)
Release Date Estimate: Monday, 11.July.2022
Send Questions to: bigscience-contact@googlegroups.com
Cite as: BigScience, BigScience Language Open-source Open-access Multilingual (BLOOM) Language Model. International, May 2021-May 2022
Funded by:
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The French government.
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Hugging Face (website).
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Organizations of contributors. (Further breakdown of organizations forthcoming.)
Technical Specifications
This section provides information for people who work on model development.
Click to expand
Please see the BLOOM training README for full details on replicating training.
Model Architecture: Modified from Megatron-LM GPT2 (see paper, BLOOM Megatron code):
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Decoder-only architecture
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Layer normalization applied to word embeddings layer (
StableEmbedding; see code, paper) -
ALiBI positional encodings (see paper), with GeLU activation functions
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176 billion parameters:
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70 layers, 112 attention heads
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Hidden layers are 14336-dimensional
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Sequence length of 2048 tokens used (see BLOOM tokenizer, tokenizer description)
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Objective Function: Cross Entropy with mean reduction (see API documentation).
Compute infrastructure: Jean Zay Public Supercomputer, provided by the French government (see announcement).
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Hardware: 384 A100 80GB GPUs (48 nodes):
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Additional 32 A100 80GB GPUs (4 nodes) in reserve
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8 GPUs per node Using NVLink 4 inter-gpu connects, 4 OmniPath links
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CPU: AMD
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CPU memory: 512GB per node
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GPU memory: 640GB per node
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Inter-node connec
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For agents
This page has a .md twin and JSON over the API.