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Multi Verse Model GPTQ by MTSAIR

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Multi Verse Model GPTQ is an open-source language model by MTSAIR. Features: 7.2b LLM, VRAM: 4.2GB, Context: 32K, License: other, Quantized, HF Score: 76.7, LLM Explorer Score: 0.13, Arc: 72.9, HellaSwag: 89.2, MMLU: 64.4, TruthfulQA: 77.9, WinoGrande: 84.8, GSM8K: 71.3.

  4-bit   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

ARC: 72.87 vs 96.7 (so35)-24.6%
HellaSwag: 89.2 vs 95.3 (gpt4)-6.4%
MMLU: 64.4 vs 88.3 (so35)-27.1%
TruthfulQA: 77.92 vs 59 (gpt4)32.1%
WinoGrande: 84.77 vs 87.5 (gpt4)-3.1%
GSM8K: 71.27 vs 96.4 (so35)-26.1%
LLME Score: 0.1332
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 Size7.2b
Required VRAM4.2 GB
Updated2026-03-02
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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