Hands-On Generative AI with Transformers and Diffusion Models

Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different domains. This go-to book introduces theoretical concepts followed by guided practical applications, with extensive code samples and easy-to-understand illustrations. You'll learn how to use open source libraries to utilize transformers and diffusion models, conduct code exploration, and study several existing projects to help guide your work.

• Build and customize models that can generate text and images
• Explore trade-offs between using a pretrained model and fine-tuning your own model
• Create and utilize models that can generate, edit, and modify images in any style
• Customize transformers and diffusion models for multiple creative purposes
• Train models that can reflect your own unique style

About the author

Omar Sanseviero was the Chief Llama Officer and Head of Platform and Community at Hugging Face, leading the developer advocacy engineering, on-device, and moonshot teams. Omar has extensive engineering experience working at Google in Google Assistant and TensorFlow Graphics. Omar's work at Hugging Face was at the intersection of open source, product, research, and technical communities.

Product details

• Authors: Pedro Cuenca, Cuenca Pedro, Apolinario Passos, Omar Sanseviero, Jonathan Whitaker
• Publisher: O'Reilly
• Languages: English
• Product format: Paperback / Softback
• Released: 28.01.2025
• EAN: 9781098149246
• ISBN: 978-1-0981-4924-6
• Dimensions: 178 mm x 233 mm x 23 mm
• Weight: 726 g
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Artificial Intelligence, COMPUTERS / Information Theory, COMPUTERS / Machine Theory, information architecture, Information theory, Mathematical theory of computation, COMPUTERS / Computer Architecture, COMPUTERS / Artificial Intelligence / General