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Vicuna 33B Coder AWQ by TheBloke

 »  All LLMs  »  TheBloke  »  Vicuna 33B Coder AWQ   URL Share it on

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  Arxiv:1910.09700   4-bit   Autotrain compatible   Awq Base model:felixchao/vicuna-33... Base model:quantized:felixchao...   Code   Codegen   Llama   Model-index   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Vicuna 33B Coder AWQ Benchmarks

LLME Score: 0.15214
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Vicuna 33B Coder AWQ Parameters and Internals

Model Type
text-generation
Additional NotesAWQ is an efficient, accurate, and fast low-bit quantization method, supporting 4-bit quantization for this model.
LLM NameVicuna 33B Coder AWQ
Repository 🤗https://huggingface.co/TheBloke/vicuna-33B-coder-AWQ 
Model NameVicuna 33B Coder
Model CreatorChao Chang-Yu
Base Model(s)  Vicuna 33B Coder   FelixChao/vicuna-33b-coder
Model Size33b
Required VRAM17.6 GB
Updated2024-11-12
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   7.6 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.34.0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16
Vicuna 33B Coder AWQ (TheBloke/vicuna-33B-coder-AWQ)

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...der 33B V2 Base 8.0bpw H8 EXL216K / 33.5 GB81
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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/vicuna-33B-coder-AWQ.

Rank the Vicuna 33B Coder AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241110
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