OpenBezoar SFT by SurgeGlobal

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  Arxiv:2306.02707   Arxiv:2404.12195   Autotrain compatible Base model:finetune:openlm-res... Base model:openlm-research/ope... Dataset:surgeglobal/evol-instr...   Dataset:surgeglobal/lamini   Dataset:surgeglobal/orca   En   Endpoints compatible   Instruct   Llama   Pytorch   Region:us   Safetensors   Sharded   Tensorflow

OpenBezoar SFT Benchmarks

OpenBezoar SFT (SurgeGlobal/OpenBezoar-SFT)
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OpenBezoar SFT Parameters and Internals

Model Type 
instruction-following, text generation
Additional Notes 
The model uses Q-LoRA with a configuration of r: 16, alpha: 16, dropout: 0.05 on target modules [q_proj, v_proj, k_proj]. Uses datasets LaMini, Orca, Evol-Instruct for instruction tuning.
Supported Languages 
en (full)
Input Output 
Input Format:
Modified Alpaca prompt template
Accepted Modalities:
text
Output Format:
Text
Performance Tips:
Use the prescribed prompt template for optimal results
LLM NameOpenBezoar SFT
Repository ๐Ÿค—https://huggingface.co/SurgeGlobal/OpenBezoar-SFT 
Base Model(s)  Open Llama 3b V2   openlm-research/open_llama_3b_v2
Model Size3b
Required VRAM13.7 GB
Updated2025-06-19
MaintainerSurgeGlobal
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   3.7 GB: 2-of-2   10.0 GB: 1-of-2   3.7 GB: 2-of-2
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensecc-by-nc-4.0
Context Length2048
Model Max Length2048
Transformers Version4.33.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than SurgeGlobal/OpenBezoar-SFT.

Rank the OpenBezoar SFT 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124