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Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ by mobiuslabsgmbh

 »  All LLMs  »  mobiuslabsgmbh  »  Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ   URL Share it on

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  4bit   Autotrain compatible   Mixtral   Moe   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-attn-4bit-moe-2bit-HQQ 

Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ Benchmarks

LLME Score: 0.14901
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ (mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-attn-4bit-moe-2bit-HQQ)

Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
The model is a quantized version with a mix of 4-bit and 2-bit via Half-Quadratic Quantization (HQQ).
LLM NameMixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ
Repository 🤗https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-attn-4bit-moe-2bit-HQQ 
Required VRAM18.2 GB
Updated2025-03-14
Maintainermobiuslabsgmbh
Model Typemixtral
Model Files  18.2 GB
Quantization Type4bit
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.1
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-v0.1-hf-attn-4bit-moe-2bit-HQQ.

Rank the Mixtral 8x7B V0.1 Hf Attn 4bit MoE 2bit HQQ Capabilities

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Release v20241227
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