Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
LLM Engineer's Handbook

You're reading from   LLM Engineer's Handbook Master the art of engineering large language models from concept to production

Arrow left icon
Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781836200079
Length 522 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Maxime Labonne Maxime Labonne
Author Profile Icon Maxime Labonne
Maxime Labonne
Paul Iusztin Paul Iusztin
Author Profile Icon Paul Iusztin
Paul Iusztin
Alex Vesa Alex Vesa
Author Profile Icon Alex Vesa
Alex Vesa
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Understanding the LLM Twin Concept and Architecture 2. Tooling and Installation FREE CHAPTER 3. Data Engineering 4. RAG Feature Pipeline 5. Supervised Fine-Tuning 6. Fine-Tuning with Preference Alignment 7. Evaluating LLMs 8. Inference Optimization 9. RAG Inference Pipeline 10. Inference Pipeline Deployment 11. MLOps and LLMOps 12. Other Books You May Enjoy
13. Index
Appendix: MLOps Principles

Summary

This first chapter was critical to understanding the book’s goal. As a product-oriented book that will walk you through building an end-to-end ML system, it was essential to understand the concept of an LLM Twin initially. Afterward, we walked you through what an MVP is and how to plan our LLM Twin MVP based on our available resources. Following this, we translated our concept into a practical technical solution with specific requirements. In this context, we introduced the FTI design pattern and showcased its real-world application in designing systems that are both modular and scalable. Ultimately, we successfully applied the FTI pattern to design the architecture of the LLM Twin to fit all our technical requirements.

Having a clear vision of the big picture is essential when building systems. Understanding how a single component will be integrated into the rest of the application can be very valuable when working on it. We started with a more abstract presentation of the LLM Twin architecture, focusing on each component’s scope, interface, and interconnectivity.

The following chapters will explore how to implement and deploy each component. On the MLOps side, we will walk you through using a computing platform, orchestrator, model registry, artifacts, and other tools and concepts to support all MLOps best practices.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime