google-gemma / cookbook

# Welcome to the Gemma Cookbook
This is a collection of guides and examples for Google Gemma.
> **Disclaimer:** Gemma is a family of developer-focused models built by Google DeepMind. This cookbook is a collection of guides and examples for Google Gemma. Please keep in mind that Gemma is an open model and can hallucinate as you build on examples in this cookbook.
## Repository Structure
* **Tutorials**: The latest tested notebooks for Gemma models and variants.
* **Apps**: Full-stack demos and complex end-to-end use cases.
* **Experiments**: Research-focused model notebooks, including TxGemma and MedGemma.
* **Responsible**: Notebooks for responsible AI development.
* **Docs**: Core documentation, capabilities, and technical guides.
* **Archive**: All older notebooks and historical examples.
## Get started with the Gemma models
Gemma is a family of lightweight, generative artificial intelligence (AI) open models, built from the same research and technology used to create the Gemini models. The Gemma model family includes:
* Gemma\
 The core models of the Gemma family.
 * Gemma\
 For a variety of text generation tasks and can be further tuned for specific use cases
 * Gemma 2\
 Higher-performing and more efficient, available in 2B, 9B, 27B parameter sizes
 * Gemma 3\
 Longer context window and handling text and image input, available in 1B, 4B, 12B, and 27B parameter sizes
 * Gemma 3n \
 Designed for efficient execution on low-resource devices. Handling text, image, video, and audio input, available in E2B and E4B parameter sizes
 * Gemma 4\
 Well-suited for reasoning, agentic workflows, coding, and multimodal understanding, available in E2B, E4B, 12B, 26B A4B, and 31B parameter sizes.
* Gemma variants
 * CodeGemma\
 Fine-tuned for a variety of coding tasks
 * DataGemma\
 Fine-tuned for using Data Commons to address AI hallucinations
 * DiffusionGemma\
 An experimental open model that explores text diffusion, an exceptionally fast approach to text generation.
 * FunctionGemma\
 Fine-tuned on Gemma 3 270M IT checkpoint for function calling
 * MedGemma
 The MedGemma collection contains Google's most capable open models for medical text and image comprehension, built on Gemma 3. Developers can use MedGemma to accelerate building healthcare-based AI applications. MedGemma comes in two variants: a 4B multimodal version and a 27B text-only version.
 * PaliGemma\
 Vision Language Model\
 For a deeper analysis of images and provide useful insights
 * PaliGemma 2\
 VLM which incorporates the capabilities of the Gemma 2 models
 * RecurrentGemma\
 Based on Griffin architecture\
 For a variety of text generation tasks
 * ShieldGemma\
 Fine-tuned for evaluating the safety of text prompt input and text output responses against a set of defined safety policies
 * ShieldGemma 2\
 Fine-tuned on Gemma 3 4B IT checkpoint for image safety classification
 * T5Gemma\
 A collection of encoder-decoder models that provide a strong quality-inference efficiency tradeoff
 *