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Notux 8x7b V1 AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:argilla/notux-8x7b-... Base model:quantized:argilla/n...   Conversational Dataset:argilla/ultrafeedback-...   De   Dpo   En   Es   Fr   It   Mixtral   Moe   Preference   Quantized   Region:us   Rlaif   Safetensors   Sharded   Tensorflow   Ultrafeedback
Model Card on HF 🤗: https://huggingface.co/TheBloke/notux-8x7b-v1-AWQ 

Notux 8x7b V1 AWQ Benchmarks

LLME Score: 0.12872
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Notux 8x7b V1 AWQ (TheBloke/notux-8x7b-v1-AWQ)
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Notux 8x7b V1 AWQ Parameters and Internals

Model Type 
generative, Sparse Mixture of Experts
Use Cases 
Areas:
research, commercial applications
Additional Notes 
AWQ (low-bit weight quantization) model files available.
Supported Languages 
en (high), de (high), es (high), fr (high), it (high)
Training Details 
Data Sources:
argilla/ultrafeedback-binarized-preferences-cleaned
Methodology:
Preference-tuning using DPO and MoE fine-tuning
Training Time:
1 epoch (~10hr)
Hardware Used:
8 x H100 80GB
Model Architecture:
Derived from Mixtral-8x7B-Instruct-v0.1
Input Output 
Input Format:
{prompt}
Output Format:
text
LLM NameNotux 8x7b V1 AWQ
Repository 🤗https://huggingface.co/TheBloke/notux-8x7b-v1-AWQ 
Model NameNotux 8X7B v1
Model CreatorArgilla
Base Model(s)  Notux 8x7b V1   argilla/notux-8x7b-v1
Model Size6.5b
Required VRAM24.7 GB
Updated2025-09-23
MaintainerTheBloke
Model Typemixtral
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
Supported Languagesen de es fr it
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/notux-8x7b-v1-AWQ.

Rank the Notux 8x7b V1 AWQ 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  
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Release v20241124
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