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Vicuna 7B V1.5 AWQ by casperhansen

 »  All LLMs  »  casperhansen  »  Vicuna 7B V1.5 AWQ   URL Share it on

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  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: 0.14622
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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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
Updated2025-06-09
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
Vicuna 7B V1.5 AWQ (casperhansen/vicuna-7b-v1.5-awq)

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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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Release v20241124
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