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Description of the change

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Colab Notebook

Checklist

  • I have added all the necessary unit tests for my change.
  • I have verified that my change does not break existing code and works with all backends (TensorFlow, JAX, and PyTorch).
  • My PR is based on the latest changes of the main branch (if unsure, rebase the code).
  • I have followed the Keras Hub Model contribution guidelines in making these changes.
  • I have followed the Keras Hub API design guidelines in making these changes.
  • I have signed the Contributor License Agreement.

@github-actions github-actions bot added the Gemma Gemma model specific issues label Aug 14, 2025
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Summary of Changes

Hello @sachinprasadhs, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on expanding the available Gemma model presets within the Keras Hub. It specifically registers two new "tiny" versions of the Gemma 3 model: a base 270-million parameter model and an instruction-tuned 270-million parameter model. These additions aim to provide more efficient options for AI development, particularly for scenarios requiring smaller models or task-specific fine-tuning.

Highlights

  • Registration of gemma3_270m preset: This change introduces a new preset for the base Gemma model with 270 million parameters, designed for hyper-efficient AI and task-specific fine-tuning.
  • Registration of gemma3_instruct_270m preset: This change adds a new preset for the instruction-tuned Gemma model, also with 270 million parameters, optimized for efficient AI applications and fine-tuning.
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Code Review

This pull request adds two new presets for tiny Gemma models: gemma3_270m and gemma3_instruct_270m. The changes are straightforward, but I've noticed that the descriptions for the new presets are inconsistent with the existing ones. I've left a comment suggesting to update them to match the established format for better clarity and consistency across all presets.

@divyashreepathihalli divyashreepathihalli merged commit 7e4652b into keras-team:master Aug 14, 2025
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sachinprasadhs added a commit that referenced this pull request Aug 14, 2025
* add tiny Gemma

* modify description

* update description
@sachinprasadhs sachinprasadhs deleted the tiny_gemma branch August 14, 2025 19:01
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