Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG
Louis-François Bouchard & Louie Peters- Jerry Liu, Co-founder and CEO of LlamaIndex
TL;DR
With amazing feedback from industry leaders, this book is an end-to-end resource for anyone looking to enhance their skills or dive into the world of AI and develop their understanding of Generative AI and Large Language Models (LLMs). It explores various methods to adapt "foundational" LLMs to specific use cases with enhanced accuracy, reliability, and scalability. Written by over 10 people on our Team at Towards AI and curated by experts from Activeloop, LlamaIndex, Mila, and more, it is a roadmap to the tech stack of the future.
The book aims to guide developers through creating LLM products ready for production, leveraging the potential of AI across various industries. It is tailored for readers with an intermediate knowledge of Python.
[/b]What's Inside this 470-page Book?
Hands-on Guide on LLMs, Prompting, Retrieval Augmented Generation (RAG) & Fine-tuning
Roadmap for Building Production-Ready Applications using LLMs
Fundamentals of LLM Theory
Simple-to-Advanced LLM Techniques & Frameworks
Code Projects with Real-World Applications
Colab Notebooks that you can run right away
Community access and our own AI Tutor
[b]Table of Contents
Chapter I Introduction to Large Language Models
Chapter II LLM Architectures & Landscape
Chapter III LLMs in Practice
Chapter IV Introduction to Prompting
Chapter V Introduction to LangChain & LlamaIndex
Chapter VI Prompting with LangChain
Chapter VII Retrieval-Augmented Generation
Chapter VIII Advanced RAG
Chapter IX Agents
Chapter X Fine-Tuning
Chapter XI Deployment
What Experts Think About The Book
"A truly wonderful resource that develops understanding of LLMs from the ground up, from theory to code and modern frameworks. Grounds your knowledge in research trends and frameworks that develop your intuition around what'
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