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Meta Code Llama AI tool for coding officially launches

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Meta Code Llama AI tool for coding officially launches

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Meta Code Llama AI tool for coding officially launches


In a groundbreaking announcement, Meta has today officially launched Code Llama, a state-of-the-art large language model (LLM) that is set to revolutionize the coding landscape. This innovative tool is designed to generate and discuss code using text prompts, making it a game-changer for developers and coding learners alike.

Code Llama is not just another coding tool; it is a productivity and educational instrument that aims to make workflows more efficient for developers. It lowers the barrier to entry for coding learners, enabling them to write more robust, well-documented software. This tool is a testament to Meta’s commitment to fostering a more inclusive and efficient coding environment.

Code Llama AI coding tool

“The Code Llama models provide stable generations with up to 100,000 tokens of context. All models are trained on sequences of 16,000 tokens and show improvements on inputs with up to 100,000 tokens. Aside from being a prerequisite for generating longer programs, having longer input sequences unlocks exciting new use cases for a code LLM. For example, users can provide the model with more context from their codebase to make the generations more relevant. It also helps in debugging scenarios in larger codebases, where staying on top of all code related to a concrete issue can be challenging for developers. When developers are faced with debugging a large chunk of code they can pass the entire length of the code into the model.”

Code Llama AI coding tool

  • Code Llama is a state-of-the-art LLM capable of generating code, and natural language about code, from both code and natural language prompts.
  • Its is free for research and commercial use.
  • Its built on top of Llama 2 and is available in three models:
    • The foundational code model;
    • Python specialized for Python;
    • Instruct, which is fine-tuned for understanding natural language instructions.
  • In Meta’s own benchmark testing, Code Llama outperformed state-of-the-art publicly available LLMs on code tasks
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The release of Code Llama is not limited to research purposes. It is also available for commercial use under the same community license as Llama 2. This move is expected to spur innovation and productivity in various sectors, including research, industry, open source projects, NGOs, and businesses.

Code Llama is a code-specialized version of Llama 2, created by further training Llama 2 on its code-specific datasets. This model can generate code and natural language about code, from both code and natural language prompts. It can be used for code completion and debugging and supports many popular programming languages, making it a versatile tool for programmers.

Meta is releasing three sizes of Code Llama, with 7B, 13B, and 34B parameters respectively. These models have been trained with an impressive 500B tokens of code and code-related data. The 7B and 13B models boast a fill-in-the-middle (FIM) capability, allowing them to insert code into existing code. These three models cater to different serving and latency requirements, making it a flexible tool for various coding needs.

Code Llama officially launches

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In addition to the main model, Meta has fine-tuned two additional variations  – Python and Code Llama – Instruct. Code Llama – Python is a language specialized variation, further fine-tuned on 100B tokens of Python code. On the other hand, Code Llama – Instruct is an instruction fine-tuned and aligned variation, making it better at understanding what people expect out of their prompts.

The ultimate goal of Code Llama is to make developer workflows more efficient and to facilitate the development of new technologies that improve peoples’ lives. Meta hopes that Code Llama will inspire others to leverage Llama 2 to create new innovative tools for research and commercial products. With the launch of Code Llama, the future of coding looks brighter and more efficient than ever before.

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Source: Meta

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