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

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

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  4bit   Autotrain compatible   Conversational   Instruct   Mixtral   Moe   Quantized   Region:us

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

LLME Score: 0.19992
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 Attn 4bit MoE 2bit Metaoffload HQQ Parameters and Internals

LLM NameMixtral 8x7B Instruct V0.1 Hf Attn 4bit MoE 2bit Metaoffload HQQ
Repository 🤗https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-attn-4bit-moe-2bit-metaoffload-HQQ 
Required VRAM18.3 GB
Updated2024-09-07
Maintainermobiuslabsgmbh
Model Typemixtral
Instruction-BasedYes
Model Files  18.3 GB
Quantization Type4bit
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
Mixtral 8x7B Instruct V0.1 Hf Attn 4bit MoE 2bit Metaoffload HQQ (mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-attn-4bit-moe-2bit-metaoffload-HQQ)

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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-attn-4bit-moe-2bit-metaoffload-HQQ.

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

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Release v2024072803
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