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Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ by mobiuslabsgmbh

 »  All LLMs  »  mobiuslabsgmbh  »  Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ   URL Share it on

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  4bit   Autotrain compatible   Conversational   Instruct   Mixtral   Moe   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-4bit_g64-HQQ 

Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ Benchmarks

LLME Score: 0.14844
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ (mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-4bit_g64-HQQ)

Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model uses Half-Quadratic Quantization for 4-bit quantization.
LLM NameMixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ
Repository 🤗https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-4bit_g64-HQQ 
Required VRAM25.9 GB
Updated2025-03-13
Maintainermobiuslabsgmbh
Model Typemixtral
Instruction-BasedYes
Model Files  25.9 GB
Quantization Type4bit
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0
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 mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-4bit_g64-HQQ.

Rank the Mixtral 8x7B Instruct V0.1 Hf 4bit G64 HQQ 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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