Fine-Tuning LLMs with PyTorch and Hugging Face: Train, Customize, and Deploy Large Language Models — A Hands-On Guide for Developers and AI Practitioners - Couverture souple

Voss, Kilian

Couverture souple

ISBN 13 : 9798273483422

Editeur : Independently published, 2025

Synopsis

Fine-Tuning LLMs with PyTorch and Hugging Face

Train, Customize, and Deploy Large Language Models — A Hands-On Guide for Developers and AI Practitioners

In the new era of open-weight AI, fine-tuning is no longer reserved for big tech. It’s the developer’s key to transforming powerful pretrained models into intelligent systems that understand your data, your tone, and your domain.

Fine-Tuning LLMs with PyTorch and Hugging Face is the definitive, hands-on guide for developers, engineers, and AI enthusiasts who want to move beyond prompt engineering and start teaching models to think. Through real-world examples, clean code, and practical workflows, this book takes you from your first training run to deploying a production-ready model that performs like it was built in-house.

You’ll learn how to:

• Set up your fine-tuning environment using PyTorch and the Hugging Face ecosystem
• Prepare, tokenize, and curate datasets that truly shape model behavior
• Run efficient fine-tuning using LoRA, QLoRA, and parameter-efficient methods
• Evaluate models for accuracy, coherence, and bias — quantitatively and qualitatively
• Deploy models with FastAPI, Gradio, and cloud or local infrastructure
• Apply fine-tuning to specialized domains like finance, healthcare, and law
• Compress and quantize models to run on low-memory devices without sacrificing quality
• Automate continuous learning pipelines and integrate retrieval systems (RAG) for real-world applications

What makes this book different is its developer-first focus. You’ll not only learn the how but the why behind each step — from understanding the transformer architecture to optimizing training loops for small GPUs. Each chapter reads like a real conversation between the model and the maker — bridging theory, experimentation, and production.

By the final chapters, you’ll see how fine-tuning reshapes your role from programmer to model designer. You’ll understand why the future of AI isn’t just about bigger models — it’s about smarter adaptation.

Whether you’re training your first conversational model, building a retrieval-augmented assistant, or deploying a fine-tuned LLaMA on your laptop, this book is your step-by-step roadmap to mastering the craft of model customization and deployment.

Perfect for:

Developers • AI engineers • Machine learning enthusiasts • Applied researchers • Tech founders exploring domain-specific AI

Détails de l'édition

• Éditeur: Independently published
• Date d'édition: 2025
• Langue: anglais
• ISBN 13: 9798273483422
• Reliure: Broché
• Nombre de pages: 247
• Coordonnées du fabricant: Manufactured by Amazon on behalf of the author; https://www.amazon.fr/hz/contact-us; ; c/o Amazon Media EU S.à.r.l., 38 Avenue John F. Kennedy; Luxembourg; L-1855; Luxembourg