This is a collection of guides and examples for Google Gemma.
Gemma is a family of lightweight, state-of-the art open models built from the same research and technology used to create the Gemini models. The Gemma model family includes:
You can find the Gemma models on GitHub, Hugging Face models, Kaggle, Google Cloud Vertex AI Model Garden, and ai.nvidia.com.
| Name | Description |
|---|---|
| Gemma | |
| Gemma_Basics_with_HF.ipynb | Load, run, finetune and deploy Gemma using Hugging Face. |
| Guess_the_word.ipynb | Play a word guessing game with Gemma using Keras. |
| Game_Design_Brainstorming.ipynb | Use Gemma to brainstorm ideas during game design using Keras. |
| Translator_of_Old_Korean_Literature.ipynb | Use Gemma to translate old Korean literature using Keras. |
| Run_with_Ollama.ipynb | Run Gemma models using Ollama. |
| Deploy_with_vLLM.ipynb | Deploy a Gemma model using vLLM. |
| RAG_with_ChromaDB.ipynb | Build a Retrieval Augmented Generation (RAG) system with Gemma using ChromaDB and Hugging Face. |
| Minimal_RAG.ipynb | Minimal example of building a RAG system with Gemma using Google UniSim and Hugging Face. |
| Integrate_with_Mesop.ipynb | Integrate Gemma with Google Mesop. |
| Integrate_with_OneTwo.ipynb | Integrate Gemma with Google OneTwo. |
| Finetune_with_Axolotl.ipynb | Finetune Gemma using Axolotl. |
| Finetune_with_XTuner.ipynb | Finetune Gemma using XTuner. |
| Finetune_with_LLaMA_Factory.ipynb | Finetune Gemma using LLaMA-Factory. |
| PaliGemma | |
| Image_captioning_using_PaliGemma.ipynb | Use PaliGemma to generate image captions using Keras. |
| Image_captioning_using_finetuned_PaliGemma.ipynb | Compare the image captioning results using different PaliGemma versions with Hugging Face. |
| Finetune_PaliGemma_for_image_description.ipynb | Finetune PaliGemma for image description using JAX. |
| Description |
|---|
| Langchain integration |
| LlamaIndex integration |
| Common use cases |
| Prompt chaining |
| Advanced prompting |
Ask a Gemma cookbook-related question on the new Build with Google AI Forum, or open an issue on GitHub.
If you want to see addtional cookbooks implemented for specific features/integrations, please send us a pull request by adding your feature request(s) in the wish list.
If you want to make contributions to the Gemma Cookbook project, you are welcome to pick any idea in the wish list and implement it.
Contributions are always welcome. Please read contributing before implementation.
Thank you for developing with Gemma! We’re excited to see what you create.
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