Code Llama

Code Llama is a cutting-edge large language model designed to generate code and natural language about code. It's built on top of Llama 2, enhancing coding capabilities. The model comes in three variants: the foundational code model, a Python-specific version, and one fine-tuned for understanding natural language instructions.

Code Llama generates code based on prompts from both code and natural language inputs. It uses its extensive language model to comprehend the provided prompt and produce relevant code in return. This makes it suitable for tasks like code completion and debugging.

The three models of Code Llama are:

• Code Llama: The foundational code model, which generates code and natural language based on prompts from both code and natural language inputs.
• Code Llama - Python: A version specialized for Python code generation, fine-tuned on 100B tokens of Python code.
• Code Llama - Instruct: A model fine-tuned for understanding natural language instructions, providing helpful and safe answers in natural language.

Code Llama supports code completion through its fill-in-the-middle capability, enabling it to insert new code into existing code. It can handle input sequences of up to 100,000 tokens, allowing for more context and relevance in code generation and debugging scenarios.

The model is not suitable for general natural language tasks, but rather focuses on code-specific tasks. Its primary function and focus is on generating code based on prompts from both code and natural language inputs.

Code Llama has demonstrated superior performance on coding benchmarks such as HumanEval and Mostly Basic Python Programming (MBPP). It aids productivity and education by allowing developers to generate code and natural language about code, which can speed up workflows, help in new software creation, and debug existing code. For learners, it can lower the barrier to entry for people who are just starting to code.

Code Llama is considered more innovative, safe, and responsible due to its extensive safety measures, including red teaming efforts and quantitative evaluation of the risk of generating malicious code. It has also been developed in an open approach to encourage innovation and safety in its usage.

In debugging scenarios, Code Llama can be useful in handling large chunks of code. With its ability to take in input sequences of up to 100,000 tokens, developers can provide the model with more context from the codebase to make the generations more relevant, assisting in debugging larger codebases.

Code Llama is released under the same community license as Llama 2, facilitating the development of new technologies that improve people's lives and making it available for both non-commercial and commercial use. The hope is that by being openly available, the entire community can evaluate its capabilities, recognize issues, and fix vulnerabilities.