Building LLMs for Production

Introduction

This book concentrates on the essential tech stack for adapting a large language model (LLM) to a specific use case and achieving a sufficient threshold of accuracy and reliability for scalable use by paying customers. Specifically, it will cover Prompt Engineering, Fine-tuning, Retrieval-Augmented Generation (RAG), and Deployment.

Building your own production-ready applications and products using these models requires a significant development effort. Hence, this book requires intermediate knowledge of Python. However, the first few chapters of this book should still be light and easily understandable. In parallel, we would advise you to take a look at Python and other free resources we have to grow your AI technical skills and ...