starcoder2-15b-instruct-v0.1

Maintainer: bigcode

Total Score

80

Last updated 5/17/2024

🛠️

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

starcoder2-15b-instruct-v0.1 is the very first entirely self-aligned code Large Language Model (LLM) trained with a fully permissive and transparent pipeline. It was developed by bigcode, an organization focused on building open-source AI models. The model was trained using an open-source pipeline that generates thousands of instruction-response pairs, which are then used to fine-tune the base starcoder2-15b model without any human annotations or distilled data from huge proprietary LLMs.

This self-alignment approach contrasts with the typical instruction-tuning process, which often relies on distilled data from large, closed-source models. By using a fully transparent and permissive pipeline, starcoder2-15b-instruct-v0.1 aims to provide a more ethical and accountable code generation model.

The starcoder2-15b model, which serves as the base for this instructed version, is a 15B parameter model trained on over 600 programming languages from The Stack v2 dataset. It uses advanced transformer architectures like Grouped Query Attention and a sliding window context of 16,384 tokens to enable efficient and high-quality code generation.

Model inputs and outputs

Inputs

  • Instruction: A natural language description of a task or request, such as "Write a function that computes the square root."

Outputs

  • Generated code: The model's attempt to generate code that fulfills the given instruction, such as a function that computes the square root.

Capabilities

starcoder2-15b-instruct-v0.1 is designed to respond to coding-related instructions in a single turn. It can generate code snippets across a wide range of programming languages to help with tasks like algorithm implementation, data processing, and software development. However, the generated code is not guaranteed to be correct or efficient, as the model may introduce bugs or suboptimal solutions.

What can I use it for?

You can use starcoder2-15b-instruct-v0.1 to help with a variety of coding-related tasks, such as:

  • Prototyping new algorithms or features
  • Automating repetitive coding tasks
  • Generating boilerplate code or scaffolding
  • Exploring different programming approaches to a problem

While the model can be a useful tool, it's important to review and test any generated code before using it in a production environment. The search index provided by the BigCode project can help you identify the origin of generated code and ensure proper attribution.

Things to try

One interesting aspect of starcoder2-15b-instruct-v0.1 is its ability to generate code in a fully self-aligned and transparent manner. This approach aims to address some of the ethical and accountability concerns surrounding large language models trained on proprietary data.

You could try providing the model with more complex or open-ended instructions to see how it responds, or experiment with the model's ability to generate code in different programming languages. Additionally, you could explore using the model in conjunction with other tools, such as unit testing frameworks, to validate the correctness of the generated code.



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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