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Mixtral 8x7B V0.1 Hf 2bit G16 S128 HQQ by mobiuslabsgmbh

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  2bit   Autotrain compatible   Mixtral   Moe   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-2bit_g16_s128-HQQ 

Mixtral 8x7B V0.1 Hf 2bit G16 S128 HQQ Benchmarks

LLME Score: 0.12289
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 2bit G16 S128 HQQ (mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-2bit_g16_s128-HQQ)
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Mixtral 8x7B V0.1 Hf 2bit G16 S128 HQQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
This is a version of the Mixtral-8x7B-v0.1 model quantized to 2-bit via Half-Quadratic Quantization (HQQ).
LLM NameMixtral 8x7B V0.1 Hf 2bit G16 S128 HQQ
Repository 🤗https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-v0.1-hf-2bit_g16_s128-HQQ 
Required VRAM18 GB
Updated2025-09-23
Maintainermobiuslabsgmbh
Model Typemixtral
Model Files  18.0 GB
Quantization Type2bit
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-v0.1-hf-2bit_g16_s128-HQQ.

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Release v20241124
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