Overview

This book is a practical guide to using large language models (LLMs) for real-world tasks. It teaches you how to build, improve, and use LLMs for real projects. The book covers a lot, including: * How to build different parts of LLMs, like transformer models. * Techniques for giving LLMs instructions to get the desired results. * How to adjust LLMs to work on specific data sets. * Creating systems that combine searching information and generating new text. The book also explains how to deal with the challenges of using LLMs in real applications, such as making them run faster, storing them efficiently, and using cloud services. You'll also learn how to make sure your LLMs are accurate, reliable, and avoid biases. Finally, the book covers legal and ethical considerations, like data privacy and fairness in LLM outputs. This book is useful for anyone who wants to learn about LLMs, from engineers and researchers to developers and data scientists. Even if you're new to LLMs, this book will give you a strong foundation.

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