Code Llama 70B Is an Open-Source Large Language Model That Can Generate and Complete Code Using Natural Language Instructions.
Meta, the company previously known as Facebook, has released Code Llama 70B that is a new and enhanced version of its open-source large language model (LLM) for coding. Code Llama 70B is a generative AI model that can generate and complete code using natural language instructions. It can also provide helpful and safe answers in natural language. Code Llama 70B is based on Llama 2, Meta’s general-purpose LLM, and is fine-tuned for programming tasks. Code Llama 70B supports various programming languages, such as Python, C++, Java, PHP, and Typescript, and can handle up to 100,000 tokens of input, allowing users to provide more context from their codebase.
Code Llama 70B is available for free to researchers and developers, under the same license as previous Code Llama models. Users can download the models from Meta’s website or access them through platforms like Hugging Face or PyTorch. Code Llama 70B is also compatible with Google Cloud’s Vertex AI, a unified platform for managing the entire machine learning lifecycle.
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Code Llama 70B is one of the most advanced and best-performing models in the Llama family, which includes Llama Chat, a conversational AI model, and Llama 2, a 175-billion-parameter LLM that outdoes other open-source LLMs on many external benchmarks. Meta says that some of the developments of Code Llama 70B will be included in the upcoming Llama 3 and future models.
Code Llama 70B is a important and thrilling breakthrough for the AI industry and community, as it establishes the potential and challenges of using LLMs for coding. Code Llama 70B can enable developers to write and edit code faster and easier, as well as to learn and experiment with new languages and frameworks. Code Llama 70B can also foster innovation and collaboration in coding, as users can share and reuse code snippets and solutions. However, Code Llama 70B also raises ethical and social concerns, such as the quality and safety of the generated code, the intellectual property and attribution of the code, and the impact of LLMs on the coding profession and education.
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Meta recognizes these risks and calls for more research and regulation on the responsible use of LLMs for coding. Meta also proposes some technical solutions, such as watermarking, digital signatures, and provenance tracking, to help detect and verify the authenticity of the generated code. Meta also encourages users to review and test the code before using it, and to report any issues or feedback to the company.
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