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Vicuna 7B V1.5 AWQ by casperhansen

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Vicuna 7B V1.5 AWQ is an open-source language model by casperhansen. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, HF Score: 45.1, LLM Explorer Score: 0.13, Arc: 40.7, HellaSwag: 73.1, MMLU: 47.3, TruthfulQA: 41.6, WinoGrande: 67.9, GSM8K: 0.1.

  4-bit   Autotrain compatible   Awq   Endpoints compatible   Llama   Pytorch   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/casperhansen/vicuna-7b-v1.5-awq 

Vicuna 7B V1.5 AWQ Benchmarks

ARC: 40.7 vs 96.7 (so35)-57.9%
HellaSwag: 73.08 vs 95.3 (gpt4)-23.3%
MMLU: 47.26 vs 88.3 (so35)-46.5%
TruthfulQA: 41.59 vs 59 (gpt4)-29.5%
WinoGrande: 67.88 vs 87.5 (gpt4)-22.4%
GSM8K: 0.08 vs 96.4 (so35)-99.9%
LLME Score: 0.12919
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Vicuna 7B V1.5 AWQ (casperhansen/vicuna-7b-v1.5-awq)
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Vicuna 7B V1.5 AWQ Parameters and Internals

Additional Notes 
To use this model, AutoAWQ must be installed.
LLM NameVicuna 7B V1.5 AWQ
Repository 🤗https://huggingface.co/casperhansen/vicuna-7b-v1.5-awq 
Base Model(s)  henilp105/InjecAgent-vicuna-7b-v1.5-5   henilp105/InjecAgent-vicuna-7b-v1.5-5
Model Size7b
Required VRAM3.9 GB
Updated2025-11-01
Maintainercasperhansen
Model Typellama
Model Files  3.9 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk 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 casperhansen/vicuna-7b-v1.5-awq.

Rank the Vicuna 7B V1.5 AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Text Summarization and Feature Extraction  
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