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Bonito V1 by BatsResearch

 »  All LLMs  »  BatsResearch  »  Bonito V1   URL Share it on

  502   
  Arxiv:2402.18334   Autotrain compatible   Data generation   Dataset:batsresearch/ctga-v1   En   Endpoints compatible   Mistral   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/BatsResearch/bonito-v1 

Bonito V1 Benchmarks

LLME Score: 0.18863
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Bonito V1 (BatsResearch/bonito-v1)

Bonito V1 Parameters and Internals

Model Type 
MistralForCausalLM
Use Cases 
Areas:
synthetic instruction tuning dataset generation
Applications:
commercial applications, research
Primary Use Cases:
task adaptation without annotations
Limitations:
Limited to certain tasks mentioned in the model card.
Considerations:
Users should thoroughly inspect generated tasks and benchmark performance before deploying models.
Supported Languages 
language (English), proficiency (NLP)
Training Details 
Data Sources:
BatsResearch/ctga-v1
Methodology:
We train the model using Q-LoRA by optimizing the cross entropy loss over the output tokens. The model is trained for 100,000 steps.
Context Length:
2048
Training Time:
4 days
Hardware Used:
four GPUs
LLM NameBonito V1
Repository 🤗https://huggingface.co/BatsResearch/bonito-v1 
Model Size7b
Required VRAM15 GB
Updated2025-02-22
MaintainerBatsResearch
Model Typemistral
Model Files  9.9 GB: 1-of-2   5.1 GB: 2-of-2
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than BatsResearch/bonito-v1.

Rank the Bonito V1 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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Release v20241227
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