Vigogne Opt 6.7B Instruct by bofenghuang

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  Alpaca   Dataset:tatsu-lab/alpaca   Fr   Instruct   Lora   Opt   Region:us   Tensorboard

Vigogne Opt 6.7B Instruct Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Vigogne Opt 6.7B Instruct (bofenghuang/vigogne-opt-6.7b-instruct)

Vigogne Opt 6.7B Instruct Parameters and Internals

Model Type 
text generation
Use Cases 
Limitations:
Model may generate biased or harmful content.
Additional Notes 
This repo only contains the low-rank adapter. Base LLM model and tokenizer needed.
Supported Languages 
French (high proficiency)
Training Details 
Data Sources:
tatsu-lab/stanford_alpaca
Methodology:
fine-tuning
Input Output 
Input Format:
Pre-trained OPT model for input
Accepted Modalities:
text
Output Format:
text generation
LLM NameVigogne Opt 6.7B Instruct
Repository ๐Ÿค—https://huggingface.co/bofenghuang/vigogne-opt-6.7b-instruct 
Model Size6.7b
Required VRAM0 GB
Updated2024-12-22
Maintainerbofenghuang
Instruction-BasedYes
Model Files  0.0 GB
Supported Languagesfr
Model ArchitectureAutoModel
Licenseopenrail
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|v_proj
LoRA Alpha32
LoRA Dropout0.05
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than bofenghuang/vigogne-opt-6.7b-instruct.

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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 v20241217