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CodeLlama 7B Python GGML by TheBloke

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  Arxiv:2308.12950   Code   Codegen   Ggml   Llama   Llama2   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/TheBloke/CodeLlama-7B-Python-GGML 

CodeLlama 7B Python GGML Benchmarks

LLME Score: 0.13469
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CodeLlama 7B Python GGML (TheBloke/CodeLlama-7B-Python-GGML)

CodeLlama 7B Python GGML Parameters and Internals

Model Type 
text-generation
Use Cases 
Primary Use Cases:
General code synthesis and understanding, specifically for Python
Limitations:
Use in languages other than English
Additional Notes 
This model is specifically designed for Python specialist tasks.
Training Details 
Hardware Used:
Meta’s Research Super Cluster (A100-80GB GPU)
Model Architecture:
Optimized transformer architecture
LLM NameCodeLlama 7B Python GGML
Repository 🤗https://huggingface.co/TheBloke/CodeLlama-7B-Python-GGML 
Model NameCodeLlama 7B Python
Model CreatorMeta
Base Model(s)  codellama/CodeLlama-7b-python-hf   codellama/CodeLlama-7b-python-hf
Model Size7b
Required VRAM2.9 GB
Updated2024-12-22
MaintainerTheBloke
Model Typellama
Model Files  2.9 GB   3.6 GB   3.3 GB   3.0 GB   3.8 GB   4.2 GB   4.1 GB   3.8 GB   4.7 GB   5.1 GB   4.8 GB   4.7 GB   5.5 GB   7.1 GB
Supported Languagescode
GGML QuantizationYes
Quantization Typeggml
Generates CodeYes
Model ArchitectureAutoModel
Licensellama2

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-7B-Python-GGML.

Rank the CodeLlama 7B Python GGML 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 v20241217
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