Meta Unveils Code Llama AI for Coding Assistance in 2025 – Free Download Available
Meta Platforms launches Code Llama, a powerful AI chatbot fine-tuned to help developers write and debug code efficiently. Supporting multiple programming languages, this free tool is designed for both research and commercial use.
Meta Platforms has taken a significant leap forward in artificial intelligence innovation by releasing Code Llama, a free AI chatbot specifically tailored to assist with computer programming tasks.
Highlights of Code Llama
- Code Llama is Meta’s latest AI large language model optimized for generating and reviewing computer code.
- It supports a wide range of programming languages including Python, C++, Java, PHP, Typescript, Bash, and more.
- The model is available in multiple sizes, offering options for faster responses or more comprehensive coding assistance.
This new AI tool is built upon Meta's earlier Llama 2 model, launched in July 2023, which functions similarly to ChatGPT by generating human-like text. However, Code Llama is uniquely fine-tuned to specialize in software development queries and code generation.
Meta emphasizes that Code Llama is designed to accelerate developer workflows, improve code quality, and lower the learning curve for new programmers. It aims to serve a broad audience including researchers, industry professionals, open-source contributors, NGOs, and businesses.
Versatile and Efficient Coding Support
Code Llama comes in three parameter sizes: 7 billion, 13 billion, and 34 billion. The smaller models offer quicker, low-latency responses, while the largest 34 billion parameter model delivers the most accurate and detailed coding assistance.
Additionally, Meta provides specialized versions of Code Llama: one fine-tuned specifically for Python programming and another called Code Llama - Instruct, optimized for following natural language instructions, enhancing its usability in training and educational contexts.
Available for free download, Code Llama is accessible for both commercial and research purposes, making it a versatile tool for boosting productivity and learning in the coding community.
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