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Mistral 7B Instruct V0.2 AWQ by Vidushee

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Mistral 7B Instruct V0.2 AWQ is an open-source language model by Vidushee. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: mit, Quantized, Instruction-Based, HF Score: 61.2, LLM Explorer Score: 0.25, ELO: 1072, Arc: 56.7, HellaSwag: 80.8, MMLU: 59.1, TruthfulQA: 55.9, WinoGrande: 77.1, GSM8K: 37.6.

  4-bit   Awq   Conversational   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/Vidushee/Mistral-7B-Instruct-v0.2-awq 

Mistral 7B Instruct V0.2 AWQ Benchmarks

LMSys ELO: 1072 vs 1272 (so35)-15.7%
ARC: 56.74 vs 96.7 (so35)-41.3%
HellaSwag: 80.82 vs 95.3 (gpt4)-15.2%
MMLU: 59.1 vs 88.3 (so35)-33.1%
TruthfulQA: 55.86 vs 59 (gpt4)-5.3%
WinoGrande: 77.11 vs 87.5 (gpt4)-11.9%
GSM8K: 37.6 vs 96.4 (so35)-61%
LLME Score: 0.2542
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B Instruct V0.2 AWQ (Vidushee/Mistral-7B-Instruct-v0.2-awq)
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Mistral 7B Instruct V0.2 AWQ Parameters and Internals

LLM NameMistral 7B Instruct V0.2 AWQ
Repository 🤗https://huggingface.co/Vidushee/Mistral-7B-Instruct-v0.2-awq 
Base Model(s)  jan-hq/Mistral-7B-Instruct-v0.2-SLERP   jan-hq/Mistral-7B-Instruct-v0.2-SLERP
Model Size7b
Required VRAM4.2 GB
Updated2026-04-11
MaintainerVidushee
Model Typemistral
Instruction-BasedYes
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Rank the Mistral 7B Instruct V0.2 AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Text Summarization and Feature Extraction  
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