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Bloomz Mt by bigscience

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  127   
  Arxiv:2211.01786   Ak   Ar   As   Autotrain compatible   Bloom   Bm   Bn   Ca   Code   Dataset:bigscience/xp3mt   En   Endpoints compatible   Es   Eu   Fon   Fr   Gu   Hi   Id   Ig   Ki   Kn   Lg   Ln   Ml   Model-index   Mr   Ne   Nso   Ny   Or   Pa   Pt   Pytorch   Region:us   Rn   Rw   Safetensors   Sn   St   Sw   Ta   Te   Tensorboard   Tn   Ts   Tum   Tw   Ur   Vi   Wo   Xh   Yo   Zh   Zu
Model Card on HF 🤗: https://huggingface.co/bigscience/bloomz-mt 

Bloomz Mt Benchmarks

LLME Score: 0.052
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bloomz Mt (bigscience/bloomz-mt)

Bloomz Mt Parameters and Internals

Model Type 
text-generation
Use Cases 
Areas:
research, natural language understanding
Primary Use Cases:
Translating between multiple languages, Coreference resolution, Natural language inference, Program synthesis, Sentence completion
Limitations:
Prompt Engineering: Performance may vary depending on the prompt.
Considerations:
Make prompts clear with proper punctuation.
Additional Notes 
Multitask finetuned models like bloomz-mt are more suitable for non-English tasks.
Supported Languages 
language_codes (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, zu), programming_languages (C, C++, C#, Go, Java, JavaScript, Lua, PHP, Python, Ruby, Rust, Scala, TypeScript)
Training Details 
Data Sources:
bigscience/xP3mt
Data Volume:
2.09 billion tokens (finetuning)
Methodology:
Multitask finetuned on crosslingual task mixture (xP3)
Hardware Used:
288 A100 80GB GPUs using NVLink 4 inter-gpu connects
Model Architecture:
Pretrained multilingual language models, same architecture as BLOOM
Input Output 
Input Format:
text in various languages
Accepted Modalities:
text
Output Format:
generated text in the specified format/language
Performance Tips:
Use clear prompts with proper context to improve accuracy.
LLM NameBloomz Mt
Repository 🤗https://huggingface.co/bigscience/bloomz-mt 
Model Size176.2b
Required VRAM4.9 GB
Updated2025-03-13
Maintainerbigscience
Model Typebloom
Model Files  7.2 GB: 1-of-72   4.9 GB: 2-of-72   4.9 GB: 3-of-72   4.9 GB: 4-of-72   4.9 GB: 5-of-72   4.9 GB: 6-of-72   4.9 GB: 7-of-72   4.9 GB: 8-of-72   4.9 GB: 9-of-72   4.9 GB: 10-of-72   4.9 GB: 11-of-72   4.9 GB: 12-of-72   4.9 GB: 13-of-72   4.9 GB: 14-of-72   4.9 GB: 15-of-72   4.9 GB: 16-of-72   4.9 GB: 17-of-72   4.9 GB: 18-of-72   4.9 GB: 19-of-72   4.9 GB: 20-of-72   4.9 GB: 21-of-72   4.9 GB: 22-of-72   4.9 GB: 23-of-72   4.9 GB: 24-of-72   4.9 GB: 25-of-72   4.9 GB: 26-of-72   4.9 GB: 27-of-72   4.9 GB: 28-of-72   4.9 GB: 29-of-72   4.9 GB: 30-of-72   4.9 GB: 31-of-72   4.9 GB: 32-of-72   4.9 GB: 33-of-72   4.9 GB: 34-of-72   4.9 GB: 35-of-72   4.9 GB: 36-of-72   4.9 GB: 37-of-72   4.9 GB: 38-of-72   4.9 GB: 39-of-72   4.9 GB: 40-of-72   4.9 GB: 41-of-72   4.9 GB: 42-of-72   4.9 GB: 43-of-72   4.9 GB: 44-of-72   4.9 GB: 45-of-72
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
Vocabulary Size250880

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Note: green Score (e.g. "73.2") means that the model is better than bigscience/bloomz-mt.

Rank the Bloomz Mt Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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