CodeLlama-70b is a large language model specializing in code generation and understanding, representing the largest and most capable variant in the Code Llama family of models. Built upon the Llama 2 architecture, it features 70 billion parameters and utilizes an optimized transformer architecture designed specifically for coding tasks.
Architecture and Training
The model was trained between January 2023 and January 2024 using Meta's Research Super Cluster and custom training libraries. The training process involved 1400K GPU hours on A100-80GB hardware, resulting in estimated emissions of 228.55 tCO2eq, which Meta fully offset through their sustainability program. The model supports context lengths of up to 16k tokens during training and can handle up to 100k tokens during inference.
The training focused on a massive dataset of code and code-related text, though specific details about the dataset composition remain undisclosed. This specialized training enables the model to excel at various coding tasks, including code generation, completion, debugging, and instruction following.
Model Family and Variants
The Code Llama family includes models of various sizes (7B, 13B, 34B, and 70B parameters) and three distinct variants for each size:
- Base model for general code tasks
- Python-specialized model optimized for Python programming
- Instruct model designed for instruction following and safer deployment
The 70B parameter model represents the most advanced version, demonstrating superior performance across various coding benchmarks compared to its smaller siblings. While larger models generally exhibit better performance on complex tasks, they also require more computational resources.
Usage and Licensing
CodeLlama-70b accepts text input and generates text output, capable of handling various tasks including:
- Code completion
- Code infilling
- Instruction following
- Specialized Python programming tasks
The model is released under Meta's non-commercial license, making it free for research and non-commercial purposes. This licensing approach aims to promote research and development in the field of AI-assisted coding while maintaining certain usage restrictions.
More detailed information about the model's training and evaluation can be found in the research paper "Code Llama: Open Foundation Models for Code".
References
- Meta AI Blog Post - Official announcement and overview of Code Llama
- Research Paper - Detailed technical information about Code Llama's architecture and capabilities
- Model License - Official licensing information and terms of use
- Hugging Face Model Page - Technical specifications and model files
- arXiv Paper - Academic publication with detailed methodology and results
