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Mixtral 8x7B Instruct V0.1 FP8 V2 by comaniac

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  Autotrain compatible   Conversational   Endpoints compatible   Fp8   Instruct   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/comaniac/Mixtral-8x7B-Instruct-v0.1-FP8-v2 

Mixtral 8x7B Instruct V0.1 FP8 V2 Benchmarks

LLME Score: 0.1664
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 FP8 V2 (comaniac/Mixtral-8x7B-Instruct-v0.1-FP8-v2)
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Mixtral 8x7B Instruct V0.1 FP8 V2 Parameters and Internals

Additional Notes 
Weights and activations are per-tensor quantized to float8_e4m3.
Training Details 
Data Volume:
Ultrachat-200k
Methodology:
Quantization with AutoFP8
Context Length:
8192
LLM NameMixtral 8x7B Instruct V0.1 FP8 V2
Repository 🤗https://huggingface.co/comaniac/Mixtral-8x7B-Instruct-v0.1-FP8-v2 
Model Size46.7b
Required VRAM47.1 GB
Updated2025-07-19
Maintainercomaniac
Model Typemixtral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-10   5.0 GB: 2-of-10   5.0 GB: 3-of-10   5.0 GB: 4-of-10   5.0 GB: 5-of-10   5.0 GB: 6-of-10   5.0 GB: 7-of-10   5.0 GB: 8-of-10   5.0 GB: 9-of-10   2.1 GB: 10-of-10
Model ArchitectureMixtralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.40.2
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 comaniac/Mixtral-8x7B-Instruct-v0.1-FP8-v2.

Rank the Mixtral 8x7B Instruct V0.1 FP8 V2 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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Release v20241124
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