octocoder

Maintainer: bigcode

Total Score

63

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

octocoder is an instruction-tuned model with 15.5B parameters created by fine-tuning StarCoder on CommitPackFT and OASST as described in the OctoPack paper. It supports over 80 programming languages.

Model inputs and outputs

Inputs

  • Text prompts that describe the desired programming task or instruction

Outputs

  • Generated code that attempts to fulfill the provided instruction or programming task

Capabilities

octocoder can generate code in a variety of programming languages based on natural language prompts. It demonstrates strong task-completion abilities, being able to generate solutions for tasks like writing a function to perform bubble sort or printing "Hello, world!" in Python.

What can I use it for?

octocoder can be used for a variety of software development and engineering tasks. Developers can leverage it to speed up prototyping, generate boilerplate code, or explore novel solutions to programming problems. Businesses may find it helpful for automating routine coding tasks or empowering non-technical users to create basic programs. However, the generated code is not guaranteed to be bug-free or optimized, so users should carefully review and test any outputs before deploying them.

Things to try

One interesting aspect of octocoder is its ability to handle prompts that include specific technical requirements or constraints. For example, you could try providing a prompt like "Write a function in Python that sorts a list using the bubble sort algorithm" and see how the model responds. Exploring the model's handling of such detailed prompts can give you a sense of its capabilities and limitations.



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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