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Notux 8x7b V1 GPTQ by TheBloke

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Model Card on HF 🤗: https://huggingface.co/TheBloke/notux-8x7b-v1-GPTQ 

Notux 8x7b V1 GPTQ Benchmarks

LLME Score: 0.12572
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 GPTQ (TheBloke/notux-8x7b-v1-GPTQ)
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Notux 8x7b V1 GPTQ Parameters and Internals

Model Type 
Pretrained generative Sparse Mixture of Experts
Additional Notes 
This model represents the first experiment in tuning a MoE model that has already been fine-tuned with DPO.
Supported Languages 
English (NLP), Spanish (NLP), Italian (NLP), German (NLP), French (NLP)
Training Details 
Data Sources:
argilla/ultrafeedback-binarized-preferences-cleaned
Methodology:
DPO (Direct Preference Optimization)
Training Time:
~10hr
Hardware Used:
8 x H100 80GB hosted in runpod.io
LLM NameNotux 8x7b V1 GPTQ
Repository 🤗https://huggingface.co/TheBloke/notux-8x7b-v1-GPTQ 
Model NameNotux 8X7B v1
Model CreatorArgilla
Base Model(s)  Notux 8x7b V1   argilla/notux-8x7b-v1
Model Size46.7b
Required VRAM23.8 GB
Updated2026-02-21
MaintainerTheBloke
Model Typemixtral
Model Files  23.8 GB
Supported Languagesen de es fr it
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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

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Release v20241124
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