Codellama CodeLlama 13B Python Hf W4 G128 AWQ by abhinavkulkarni

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Codellama CodeLlama 13B Python Hf W4 G128 AWQ is an open-source language model by abhinavkulkarni. Features: 13b LLM, VRAM: 7.2GB, Context: 16K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.09.

  Arxiv:2308.12950   Autotrain compatible   Awq   Code   Codegen   Llama   Llama2   Pytorch   Quantized   Region:us   Sharded

Codellama CodeLlama 13B Python Hf W4 G128 AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Codellama CodeLlama 13B Python Hf W4 G128 AWQ (abhinavkulkarni/codellama-CodeLlama-13b-Python-hf-w4-g128-awq)
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Codellama CodeLlama 13B Python Hf W4 G128 AWQ Parameters and Internals

Model Type 
generative, text models
Training Details 
Methodology:
AWQ quantization
Input Output 
Accepted Modalities:
text
LLM NameCodellama CodeLlama 13B Python Hf W4 G128 AWQ
Repository ๐Ÿค—https://huggingface.co/abhinavkulkarni/codellama-CodeLlama-13b-Python-hf-w4-g128-awq 
Model Size13b
Required VRAM7.2 GB
Updated2025-09-23
Maintainerabhinavkulkarni
Model Typellama
Model Files  3.2 GB: 1-of-3   3.2 GB: 2-of-3   0.8 GB: 3-of-3
Supported Languagescode
AWQ QuantizationYes
Quantization Typeawq
Generates CodeYes
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length16384
Model Max Length16384
Transformers Version4.33.1
Tokenizer ClassCodeLlamaTokenizer
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 abhinavkulkarni/codellama-CodeLlama-13b-Python-hf-w4-g128-awq.

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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 v20260328a