Gridin I. The Practical Guide to Large Language Models. Hands-On AI Apps...2025
Download this torrent!
Gridin I. The Practical Guide to Large Language Models. Hands-On AI Apps...2025
To start this P2P download, you have to install a BitTorrent client like qBittorrent
Category: Other
Total size: 17.47 MB
Added: 1 day ago (2025-12-19 10:28:01)
Share ratio: 139 seeders, 6 leechers
Info Hash: 6CCC151EFA085D58D746A7AE7E8643F97AD5BB58
Last updated: 4 minutes ago (2025-12-21 06:08:59)
Description:
Textbook in PDF format
This book is a practical guide to harnessing Hugging Face's powerful transformers library, unlocking access to the largest open-source LLMs. By simplifying complex NLP concepts and emphasizing practical application, it empowers data scientists, machine learning engineers, and NLP practitioners to build robust solutions without delving into theoretical complexities.
The book is structured into three parts to facilitate a step-by-step learning journey. Part One covers building production-ready LLM solutions introduces the Hugging Face library and equips readers to solve most of the common NLP challenges without requiring deep knowledge of transformer internals. Part Two focuses on empowering LLMs with RAG and intelligent agents exploring Retrieval-Augmented Generation (RAG) models, demonstrating how to enhance answer quality and develop intelligent agents. Part Three covers LLM advances focusing on expert topics such as model training, principles of transformer architecture and other cutting-edge techniques related to the practical application of language models.
Each chapter includes practical examples, code snippets, and hands-on projects to ensure applicability to real-world scenarios. This book bridges the gap between theory and practice, providing professionals with the tools and insights to develop practical and efficient LLM solutions.
Introduction
Part I: LLM Basics
Chapter 1: Discovering Transformers
Chapter 2: LLM Internals and Evaluation
Chapter 3: Improving Chat Model Responses
Part II: Empowering LLM Applications with RAG and Agents
Chapter 4: Enriching the Model’s Knowledge with Retrieval-Augmented
Chapter 5: Building Agent Systems
Part III: LLM Advances
Chapter 6: Mastering Model Training
Chapter 7: Unpacking the Transformer Architecture
Summary