Books Hands-On Generative AI with Transformers and Diffusion Models Book by Jonathan Whitaker and Omar Sanseviero

"Hands-On Generative AI with Transformers and Diffusion Models" by Jonathan Whitaker, Omar Sanseviero, and co-authors is a practical, hands-on guide that teaches readers to use state-of-the-art generative AI techniques to create novel text, images, audio, and music. The book explains how transformers and diffusion models work, how to fine-tune and adapt them, and how to combine these building blocks to build new models and creative AI applications across various domains.

Key features of the book include:

A balance of theoretical concepts and guided practical applications with extensive code samples and clear illustrations.

Instructions on using open source libraries such as Transformers and Diffusers.

Lessons in building and customizing models that generate and modify text and images.

Exploration of trade-offs between using pretrained models versus fine-tuning custom models.

Techniques to train models that reflect personal style and creative goals.

Guidance on deploying models as interactive demos or services.

Practical projects runnable on platforms like Google Colaboratory, Kaggle, or Hugging Face Spaces with minimal setup.

With about 450 pages, this book is designed for data scientists, software engineers, and AI practitioners who want to gain hands-on expertise in generative AI using cutting-edge transformer and diffusion architectures. It serves as both a technical manual and a creative toolkit for building AI-generated media and applications.