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Mistral 7B Instruct V2 Quant V2 by edpowers

 »  All LLMs  »  edpowers  »  Mistral 7B Instruct V2 Quant V2   URL Share it on

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  4bit Base model:quantized:unsloth/m... Base model:unsloth/mistral-7b-...   Conversational   En   Endpoints compatible   Gguf   Instruct   Mistral   Quantized   Region:us   Unsloth
Model Card on HF 🤗: https://huggingface.co/edpowers/mistral_7b_instruct_v2_quant_v2 

Mistral 7b Instruct V2 Quant V2 Benchmarks

LLME Score: 0.18146
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Instruct V2 Quant V2 (edpowers/mistral_7b_instruct_v2_quant_v2)

Mistral 7B Instruct V2 Quant V2 Parameters and Internals

Model Type 
Text Generation
Additional Notes 
Trained 2x faster with Unsloth and Huggingface's TRL library.
Supported Languages 
English (Proficient)
LLM NameMistral 7b Instruct V2 Quant V2
Repository 🤗https://huggingface.co/edpowers/mistral_7b_instruct_v2_quant_v2 
Base Model(s)  unsloth/mistral-7b-instruct-v0.2-bnb-4bit   unsloth/mistral-7b-instruct-v0.2-bnb-4bit
Model Size7b
Required VRAM4.4 GB
Updated2025-01-27
Maintaineredpowers
Model Typemistral
Instruction-BasedYes
Model Files  4.4 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Model ArchitectureAutoModel
Licenseapache-2.0

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Note: green Score (e.g. "73.2") means that the model is better than edpowers/mistral_7b_instruct_v2_quant_v2.

Rank the Mistral 7B Instruct V2 Quant V2 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 v20241227
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