Название: Hands-On Generative AI with Transformers and Diffusion Models (Final Release)Автор: Omar Sanseviero, Pedro Cuenca, Apolinário Passos, Jonathan Whitaker
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 416
Язык: английский
Формат: epub (true)
Размер: 25.0 MB
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.
Generative AI is a revolutionary technology that has rapidly transitioned from lab demos to real-world applications, impacting billions. It can create new content—images, text, audio, videos, and more—by learning patterns from existing data, thereby enhancing creativity, augmenting data, or assisting in many tasks. For instance, a generative AI model trained on music can compose new melodies, while one trained on text can generate stories or even programming code.
This book isn’t just for experts—it’s for anyone who wants to learn about this fascinating new field. We won’t focus on building models from scratch or diving straight into complicated mathematics. Instead, we’ll leverage existing models to solve real-world problems, helping you to build a solid intuition around how these techniques work and providing the foundation for you to keep exploring.
This hands-on approach, we hope, will help you get up and running quickly and efficiently with generative AI. You’ll learn how to use pretrained models, adapt them for your needs, and generate new data with them. You’ll also learn how to evaluate the quality of generated data and explore ethical and social issues that may arise from using generative AI. This exposure will allow you to stay up-to-date with new models and help you identify areas that you may want to explore more deeply.
• 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
Who Should Read This Book:
Given the impressive products and news you might have seen about generative AI, it’s normal to be excited, or worried, about it! Whether you’re curious about how programs can generate images, want to train a model to tweet in your style, or are looking to gain a deeper understanding of products like ChatGPT, this book is for you. With generative AI, we can do all of that and many other things, including these:
Write summaries of news articles
Generate images based on a description
Enhance the quality of an image
Transcribe meetings
Generate synthetic speech in your voice style
Incorporate new subjects or styles into image-generation models, like creating images of “your cat dressed as an astronaut”
No matter your reason, you’ve decided to learn about generative AI, and this book will guide you through it.
Prerequisites:
This book assumes that you are comfortable programming in Python and have a foundational understanding of what Machine Learning is, including basic usage of frameworks like PyTorch or TensorFlow. Having practical experience with training models is not required, but it will be helpful to understand the content with more depth.
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