starchat2-15b-v0.1

Maintainer: HuggingFaceH4

Total Score

88

Last updated 5/28/2024

🛸

PropertyValue
Run this modelRun on HuggingFace
API specView on HuggingFace
Github linkNo Github link provided
Paper linkNo paper link provided

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Model overview

The starchat2-15b-v0.1 model is a 15B parameter language model fine-tuned from the StarCoder2 model to act as a helpful coding assistant. It was trained by HuggingFaceH4 on a mix of synthetic datasets to balance chat and programming capabilities. The model achieves strong performance on chat benchmarks like MT Bench and IFEval, as well as the canonical HumanEval benchmark for Python code completion.

Model inputs and outputs

Inputs

  • Text: The model takes natural language text as input, which can include instructions, questions, or code snippets.

Outputs

  • Generated text: The model outputs generated text, which can include responses to the input, completed code, or new text continuing the provided input.

Capabilities

The starchat2-15b-v0.1 model is capable of engaging in helpful conversations, answering questions, and generating code across a wide range of programming languages. It can assist with tasks like code completion, code explanation, and even high-level program design.

What can I use it for?

With its strong chat and programming capabilities, the starchat2-15b-v0.1 model can be used for a variety of applications. Developers could integrate it into their IDEs or workflow to boost productivity, while businesses could use it to provide technical support or automate certain coding tasks. The model could also be fine-tuned further for specialized domains or applications.

Things to try

One interesting thing to try with the starchat2-15b-v0.1 model is to provide it with partial code snippets and see how it completes them. You could also try giving the model high-level instructions or ideas and see how it translates those into working code. Additionally, you could explore the model's ability to explain code and programming concepts in natural language.



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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