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Mixtral 8x7B Instruct V0.1 OmniQuantv1 W4a16g128 by ChenMnZ

 »  All LLMs  »  ChenMnZ  »  Mixtral 8x7B Instruct V0.1 OmniQuantv1 W4a16g128   URL Share it on

  12   
  Arxiv:2308.13137   Autotrain compatible   Conversational   Endpoints compatible   Instruct   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ChenMnZ/Mixtral-8x7B-Instruct-v0.1-OmniQuantv1-w4a16g128 

Mixtral 8x7B Instruct V0.1 OmniQuantv1 W4a16g128 Benchmarks

LLME Score: 0.15284
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 OmniQuantv1 W4a16g128 (ChenMnZ/Mixtral-8x7B-Instruct-v0.1-OmniQuantv1-w4a16g128)

Mixtral 8x7B Instruct V0.1 OmniQuantv1 W4a16g128 Parameters and Internals

Additional Notes 
For detailed usage, refer to the corresponding Jupyter notebook available in the repository.
LLM NameMixtral 8x7B Instruct V0.1 OmniQuantv1 W4a16g128
Repository 🤗https://huggingface.co/ChenMnZ/Mixtral-8x7B-Instruct-v0.1-OmniQuantv1-w4a16g128 
Model Size6.5b
Required VRAM24.7 GB
Updated2025-02-05
MaintainerChenMnZ
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-5   5.0 GB: 2-of-5   5.0 GB: 3-of-5   5.0 GB: 4-of-5   4.7 GB: 5-of-5
Model ArchitectureMixtralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.36.0
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 ChenMnZ/Mixtral-8x7B-Instruct-v0.1-OmniQuantv1-w4a16g128.

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Release v20241227
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