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Multi Verse Model GPTQ by MTSAIR

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  4-bit   Autotrain compatible   Conversational   Endpoints compatible   Gptq   Mistral   Pytorch   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/MTSAIR/multi_verse_model_GPTQ 

Multi Verse Model GPTQ Benchmarks

LLME Score: 0.14509
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Multi Verse Model GPTQ (MTSAIR/multi_verse_model_GPTQ)
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Multi Verse Model GPTQ Parameters and Internals

Additional Notes 
The model is described as an innovative idea developed through a groundbreaking training method. It aims to exhibit the capabilities of a novel approach and assist others by exploring its potential, illustrating the significance of ongoing learning and development.
Training Details 
Methodology:
GPTQ quantization method
LLM NameMulti Verse Model GPTQ
Repository 🤗https://huggingface.co/MTSAIR/multi_verse_model_GPTQ 
Model Size1.2b
Required VRAM4.2 GB
Updated2025-11-28
MaintainerMTSAIR
Model Typemistral
Model Files  4.2 GB   4.2 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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

Rank the Multi Verse Model GPTQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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