Textbook in PDF format

This book offers you a hands-on experience using models from OpenAI and the Hugging Face library. You will use various tools and work on small projects, gradually applying the new knowledge you gain.
The book is divided into three parts. Part one covers techniques and libraries. Here, you'll explore different techniques through small examples, preparing to build projects in the next section. You'll learn to use common libraries in the world of Large Language Models. Topics and technologies covered include chatbots, code generation, OpenAI API, Hugging Face, vector databases, LangChain, fine tuning, PEFT fine tuning, soft prompt tuning, LoRA, QLoRA, evaluating models, and Direct Preference Optimization. Part two focuses on projects. You'll create projects, understanding design decisions. Each project may have more than one possible implementation, as there is often not just one good solution. You'll also explore LLMOps-related topics. Part three delves into enterprise solutions. Large Language Models are not a standalone solution; in large corporate environments, they are one piece of the puzzle. You'll explore how to structure solutions capable of transforming organizations with thousands of employees, highlighting the main role that Large Language Models play in these new solutions.
This book equips you to confidently navigate and implement Large Language Models, empowering you to tackle diverse challenges in the evolving landscape of language processing.
What You Will Learn
Gain practical experience by working with models from OpenAI and the Hugging Face library
Use essential libraries relevant to Large Language Models, covering topics such as Chatbots, Code Generation, OpenAI API, Hugging Face, and Vector databases
Create and implement projects using LLM while understanding the design decisions involved
Understand the role of Large Language Models in larger corporate settings
Introduction
Part I: Techniques and Libraries
Introduction to Large Language Models with OpenAI
Vector Databases and LLMs
LangChain and Agents
Evaluating Models
Fine-Tuning Models
Part II:
Natural Language to SQL
Creating and Publishing Your Own LLM
Part III: Enterprise Solutions
Architecting a NL2SQL Project for Immense Enterprise Databases
Decoding Risk: Transforming Banks with Customer Embeddings