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Mixtral Instruct AWQ by casperhansen

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  4-bit   Autotrain compatible   Awq   Conversational   Endpoints compatible   Instruct   Mixtral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/casperhansen/mixtral-instruct-awq 

Mixtral Instruct AWQ Benchmarks

LLME Score: 0.19384
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral Instruct AWQ (casperhansen/mixtral-instruct-awq)

Mixtral Instruct AWQ Parameters and Internals

Additional Notes 
This is a working version of Mixtral Instruct that is AWQ quantized. The repository is suggested for use as of 11-02-2024, due to another version not working.
LLM NameMixtral Instruct AWQ
Repository 🤗https://huggingface.co/casperhansen/mixtral-instruct-awq 
Model Size6.5b
Required VRAM24.7 GB
Updated2025-02-05
Maintainercasperhansen
Model Typemixtral
Instruction-BasedYes
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than casperhansen/mixtral-instruct-awq.

Rank the Mixtral Instruct AWQ 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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