Practical Gemma 4 Fundamentals

From Practical Gemma 4 Fundamentals

Table of Contents

4 of 24 chapters available · Premium unlocks the rest

• 1 Legal Notices
• 2 About This Book
• 3 Part I: Getting Oriented
• 4 Chapter 1: Introduction to Gemma 4 and the Book Project
• 5 Chapter 2: Setting Up Python, PyTorch, and the Gemma 4 Toolchain
• 6 Chapter 3: Gemma 4 Model Variants, Tokenization, Chat Templates, and Runtime Basics
• 7 Part II: Running Models Reliably
• 8 Chapter 4: First Inference with Gemma 4 in Python
• 9 Chapter 5: Generation Controls, Decoding Strategy, and Early Evaluation
• 10 Chapter 6: Prompt Engineering for Reliable Ticket Workflows
• 11 Chapter 7: Building the Ticket Triage Pipeline
• 12 Part III: Fine-Tuning Gemma 4
• 13 Chapter 8: Preparing Fine-Tuning Data for Support Tickets
• 14 Chapter 9: Supervised Fine-Tuning Workflow for Gemma 4
• 15 Chapter 10: Fine-Tuning Gemma 4 with LoRA
• 16 Chapter 11: Memory-Efficient Fine-Tuning with QLoRA
• 17 Part IV: Evaluating, Optimizing, and Packaging
• 18 Chapter 12: Evaluating Model Quality and Failure Modes
• 19 Chapter 13: Inference Optimization, Artifact Management, and Hugging Face Integration
• 20 Part V: Shipping to Production
• 21 Chapter 14: Deploying the Gemma 4 Ticket Assistant
• 22 Next Steps
• 23 Part VI: Review Questions
• 24 Answer Key