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Bloom 560M Intermediate by bigscience

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  27   
  Arxiv:1909.08053   Arxiv:2108.12409   Arxiv:2110.02861   Ak   Ar   As   Autotrain compatible   Bloom   Bm   Bn   Ca   Code   En   Endpoints compatible   Es   Eu   Fon   Fr   Gu   Hi   Id   Ig   Ki   Kn   Lg   Ln   Ml   Mr   Ne   Nso   Ny   Or   Pa   Pt   Pytorch   Region:us   Rn   Rw   Safetensors   Sn   St   Sw   Ta   Te   Tn   Ts   Tum   Tw   Ur   Vi   Wo   Xh   Yo   Zh   Zhs   Zht   Zu
Model Card on HF 🤗: https://huggingface.co/bigscience/bloom-560m-intermediate 

Bloom 560M Intermediate Benchmarks

LLME Score: 0.03153
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bloom 560M Intermediate (bigscience/bloom-560m-intermediate)
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Bloom 560M Intermediate Parameters and Internals

Model Type 
Transformer-based Language Model, Large Language Model (LLM)
Use Cases 
Primary Use Cases:
Text generation, Exploring characteristics of language generated by a language model
Limitations:
Out-of-scope uses: high-stakes settings, critical decisions
Considerations:
Indirect users should be made aware when the content they're working with is created by the LLM.
Additional Notes 
The model is intended for public research use on large language models and should not be used in high-stakes or critical decision-making scenarios.
Supported Languages 
ak (Akan), ar (Arabic), as (Assamese), bm (Bambara), bn (Bengali), ca (Catalan), code (Programming Languages), en (English), es (Spanish), eu (Basque), fon (Fon), fr (French), gu (Gujarati), hi (Hindi), id (Indonesian), ig (Igbo), ki (Kikuyu), kn (Kannada), lg (Luganda), ln (Lingala), ml (Malayalam), mr (Marathi), ne (Nepali), nso (Northern Sotho), ny (Nyanja), or (Oriya), pa (Punjabi), pt (Portuguese), rn (Kirundi), rw (Kinyarwanda), sn (Shona), st (Sesotho), sw (Swahili), ta (Tamil), te (Telugu), tn (Tswana), ts (Tsonga), tum (Tumbuka), tw (Twi), ur (Urdu), vi (Vietnamese), wo (Wolof), xh (Xhosa), yo (Yoruba), zh (Chinese), zhs (Simplified Chinese), zht (Traditional Chinese), zu (Zulu)
Training Details 
Data Sources:
45 natural languages, 12 programming languages
Data Volume:
1.5TB of pre-processed text
Methodology:
Modified from Megatron-LM GPT2
Context Length:
2048
Hardware Used:
384 A100 80GB GPUs (48 nodes), Additional 32 A100 80GB GPUs (4 nodes) in reserve
Model Architecture:
Decoder-only architecture with ALiBI positional encodings and GeLU activation functions
Release Notes 
Version:
1.0.0
Date:
11.July.2022
Notes:
Initial release with intermediary checkpoints.
LLM NameBloom 560M Intermediate
Repository 🤗https://huggingface.co/bigscience/bloom-560m-intermediate 
Model Size560m
Required VRAM1.1 GB
Updated2025-08-20
Maintainerbigscience
Model Typebloom
Model Files  1.1 GB   1.1 GB
Supported Languagesak ar as bm bn ca code en es eu fr gu hi id ig ki kn lg ln ml mr ne ny or pa pt rn rw sn st sw ta te tn ts tw ur vi wo xh yo zh zu
Model ArchitectureBloomForCausalLM
Licensebigscience-bloom-rail-1.0
Transformers Version4.21.0.dev0
Vocabulary Size250880

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Note: green Score (e.g. "73.2") means that the model is better than bigscience/bloom-560m-intermediate.

Rank the Bloom 560M Intermediate Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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