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Mistral 7B Instruct V0.2 Quantized by GIPmbH

 »  All LLMs  »  GIPmbH  »  Mistral 7B Instruct V0.2 Quantized   URL Share it on

  5   
  Arxiv:1910.09700   4-bit   Autotrain compatible   Bitsandbytes   Endpoints compatible   Instruct   Mistral   Region:eu   Safetensors
Model Card on HF 🤗: https://huggingface.co/GIPmbH/Mistral-7B-Instruct-v0.2-quantized 

Mistral 7B Instruct V0.2 Quantized Benchmarks

LLME Score: 0.14892
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 V0.2 Quantized (GIPmbH/Mistral-7B-Instruct-v0.2-quantized)
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Mistral 7B Instruct V0.2 Quantized Parameters and Internals

LLM NameMistral 7B Instruct V0.2 Quantized
Repository 🤗https://huggingface.co/GIPmbH/Mistral-7B-Instruct-v0.2-quantized 
Model Size7b
Required VRAM4.1 GB
Updated2025-07-24
MaintainerGIPmbH
Model Typemistral
Instruction-BasedYes
Model Files  4.1 GB
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Vocabulary Size32000
Torch Data Typebfloat16

Best Alternatives to Mistral 7B Instruct V0.2 Quantized

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... Summarize 64K QLoRANET Merged128K / 4.1 GB60
...1 Summarize 64K LoRANET Merged128K / 14.4 GB90
Mistral 7B Instruct V0.232K / 14.4 GB33160952630
Mistral 7B Instruct V0.132K / 14.4 GB1501691793
Seed X Instruct 7B32K / 15 GB2672123
Mixtral AI CyberCoder32K / 14.3 GB00
Note: green Score (e.g. "73.2") means that the model is better than GIPmbH/Mistral-7B-Instruct-v0.2-quantized.

Rank the Mistral 7B Instruct V0.2 Quantized 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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Release v20241124
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