CodeLlama-13b-hf

Maintainer: codellama

Total Score

92

Last updated 5/28/2024

📉

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

CodeLlama-13b-hf is a 13 billion parameter language model developed by Meta's AI research team. It is part of the Code Llama family of large language models designed for code synthesis and understanding tasks. The CodeLlama-34b-hf and CodeLlama-7b-Python-hf are similar models in the Code Llama collection, with larger and smaller parameter sizes as well as specialized Python variants. All Code Llama models leverage an optimized transformer architecture and have been trained on a diverse dataset to handle a range of programming languages and code-related tasks.

Model inputs and outputs

CodeLlama-13b-hf is an autoregressive language model that takes in text as input and generates text as output. The model can handle a variety of text-based tasks, including code completion, infilling, and instruction following. It is particularly adept at working with Python code, but can be applied to other programming languages as well.

Inputs

  • Text prompts of varying lengths, from short snippets to longer contextual passages

Outputs

  • Continuation of the input text, generating relevant and coherent additional text
  • Infilled text to complete partial code or text fragments
  • Responses to natural language instructions or prompts

Capabilities

CodeLlama-13b-hf can be used for a range of code-related tasks, such as generating new code, completing partially written code, translating between programming languages, and even providing explanations and instructions for coding concepts. The model's strong performance on Python makes it well-suited for tasks like automated code generation, code refactoring, and code-to-text translation.

What can I use it for?

Developers and researchers can leverage CodeLlama-13b-hf to build applications that streamline and accelerate code-related workflows. For example, the model could be integrated into an IDE to provide intelligent code completion and generation features. It could also power chatbots that can engage in back-and-forth conversations about coding problems and solutions. Additionally, the model could be fine-tuned for specific domains or tasks, such as generating specialized scripts or automating repetitive coding tasks.

Things to try

One interesting aspect of CodeLlama-13b-hf is its ability to understand and work with a variety of programming languages. Try providing the model with prompts that mix code from different languages, or ask it to translate code between languages. You can also experiment with giving the model more complex, multi-step instructions and see how it handles tasks that require reasoning and planning.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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