Mistral 11B OmniMix GPTQ by TheBloke

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Mistral 11B OmniMix GPTQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 11B OmniMix GPTQ (TheBloke/Mistral-11B-OmniMix-GPTQ)
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Mistral 11B OmniMix GPTQ Parameters and Internals

Model Type 
mistral
Use Cases 
Limitations:
This model appears to be primarily for testing the merge and layer rotation capabilities and isn't explicitly optimized for any particular practical application at the moment.
Additional Notes 
This model is quantized and multifaceted with multiple GPTQ (Group-based Post-training Quantization) configurations tailored for different VRAM usage and accuracy trade-offs.
Training Details 
Methodology:
Merge and layer toying involving multiple base models to achieve higher scoring.
Model Architecture:
Combination of multiple Mistral 7B models using layer slicing and slerp merge methods with specific filter parameters for each component.
Input Output 
Input Format:
<|system|> Below is an instruction that describes a task. Write a response that appropriately completes the request. <|user|> {prompt} <|assistant|>
LLM NameMistral 11B OmniMix GPTQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/Mistral-11B-OmniMix-GPTQ 
Model NameMistral 11B OmniMix
Model CreatorNeverSleep
Base Model(s)  Mistral 11B OmniMix Bf16   NeverSleep/Mistral-11B-OmniMix-bf16
Model Size11b
Required VRAM6 GB
Updated2025-08-20
MaintainerTheBloke
Model Typemistral
Model Files  6.0 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Mistral-11B-OmniMix-GPTQ.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124