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Community announcement #87

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Expand Up @@ -6,28 +6,27 @@ Quick Links: [Documentation](https://docs.instructlab.ai/) | [FAQ](https://docs.

InstructLab is an approachable open source AI community project. Our community's mission is to enable anyone to shape the future of generative AI via the collaborative improvement of open source-licensed Granite large language models (LLMs) using InstructLab's fine-tuning technology.

## Who should use InstructLab?
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Have you ever asked an LLM a question about a subject you know well, and it gave an incorrect answer? “If only I could submit a patch to fix it,” you may have thought. With InstructLab, you can!
## Community Announcement (Sept 2, 2025)

InstructLab allows anyone to improve an existing LLM by [fine-tuning](https://www.youtube.com/watch?v=4lguiHJHgfo) it with additional data sources. This allows LLMs to continuously gain new knowledge, supplementing gaps in their initial training, even about current events that happened since their pre-training phase.
Over the past year, we’ve been honored by your creativity, insights, and shared passion for advancing generative AI through **InstructLab**. Whether you added a new “knowledge” via pull request, offered feedback, joined a community call, or helped translate documentation, you’ve shaped our project in meaningful ways. Thank you.

Subject matter experts from any domain—for example, [archaeology](https://github.com/instructlab/taxonomy/pull/1269), [astronomy](https://github.com/instructlab/taxonomy/pull/1159), and [human anatomy](https://github.com/instructlab/taxonomy/pull/742)—can use InstructLab to teach [the Granite LLM family](https://www.ibm.com/granite) new information.
To better align with evolving technical needs, we’re announcing an evolution for the InstructLab community. We will be refactoring the project by separating the components out to improve its maintainability and usability, primarily as a framework SDK for model tuning.

Project users can experiment with making updates to a quantized version of the Granite model and then rebuild that version locally, checking to see if the update improved the quality of the model’s responses. InstructLab’ s tools allow contributors to both see preview of a newly tuned model, and also check to ensure that a submission to improve the community model is properly composed.
## What's Changing

You can learn more about InstructLab and how it works in the [project documentation](https://docs.instructlab.ai/).
To enhance the long-term viability and efficiency of the InstructLab project, a strategic decision has been made to relocate its foundational building blocks into separate, dedicated project repositories. This carefully considered shift is anticipated to yield substantial benefits, primarily in the areas of maintainability and independent component maturation. This independent development will foster greater agility, allowing for more focused improvements and faster iteration cycles for individual parts of the project.

## Where can I find more information about the LLMs created by InstructLab?
## Looking Ahead

Check out [InstructLab on Hugging Face](https://huggingface.co/instructlab).
We’re excited about this next chapter and believe it will lead to more robust, flexible, and powerful tools for the generative AI community. We encourage you to follow the individual component projects in their new homes and continue contributing to their growth.

## Get started
SDG: [https://github.com/Red-Hat-AI-Innovation-Team/sdg_hub](https://github.com/Red-Hat-AI-Innovation-Team/sdg_hub)

* [Install InstructLab locally](https://docs.instructlab.ai/getting-started/mac_metal/)
* [Contribute to the InstructLab community model](https://docs.instructlab.ai/taxonomy/)
* [Contribute to the Core project code](https://github.com/instructlab/instructlab/blob/main/CONTRIBUTING/CONTRIBUTING.md)
* [Connect with the community](https://github.com/instructlab/community/blob/main/Collaboration.md) to share feedback and ideas, ask questions, and troubleshoot issues.
Training: [https://github.com/Red-Hat-AI-Innovation-Team/training_hub](https://github.com/Red-Hat-AI-Innovation-Team/training_hub)

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## Additional information

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