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Quant Model Vistral 7B by Nma

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  8-bit   8bit   Autotrain compatible   Conversational   Endpoints compatible   Gptq   Mistral   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/Nma/Quant_model_Vistral_7B 

Quant Model Vistral 7B Benchmarks

LLME Score: 0.17578
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Quant Model Vistral 7B (Nma/Quant_model_Vistral_7B)

Quant Model Vistral 7B Parameters and Internals

LLM NameQuant Model Vistral 7B
Repository 🤗https://huggingface.co/Nma/Quant_model_Vistral_7B 
Model Size7b
Required VRAM7.8 GB
Updated2025-06-01
MaintainerNma
Model Typemistral
Model Files  7.8 GB
GPTQ QuantizationYes
Quantization Typegptq|8bit
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.40.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size38369
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Nma/Quant_model_Vistral_7B.

Rank the Quant Model Vistral 7B Capabilities

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Release v20241227
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