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Synopsis
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
"synopsis" may belong to another edition of this title.
About the Authors
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.
Pedro Cuenca is a Machine Learning Engineer at Hugging Face working on diffusion software, models, and applications. He has 20+ years of software development experience in fields like Internet applications (in Spain, he helped create the first interactive educational portal, the first book store, and the first free ISP) and, more recently, iOS. As a co-founder and CTO of LateNiteSoft, he worked on the technology behind Camera+, a successful iPhone photography app. He created deep-learning models for tasks such as photography enhancement and super-resolution. He was also involved in the development and operations behind dalle-mini. He brings a practical vision of integrating AI research into real-world services and the challenges and optimizations involved.
Apolinário Passos is a Machine Learning Art Engineer at Hugging Face working across different teams on multiple machine learning for art and creativity use-cases. Apolinario has 10+ years of professional and artistic experience, alternating between holding art exhibitions, coding, and product management, having been a Head of Product in World Data Lab. Apolinario aims to ensure that the ML ecosystem supports and makes sense for artistic use cases.
Jonathan Whitaker is a data scientist and deep learning researcher focused on generative modeling. He has previously worked on several courses related to the topics covered in this book, including the Hugging Face diffusion models class and Fast.AI's 'From Deep Learning Foundations to Stable Diffusion' which he co-created with Jeremy Howard in 2022. He has also applied these techniques in industry during his time as a consultant and now works full-time on AI research and development at Answer.AI.
"About this title" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. Learn how to use generative media techniques with AI to create novel images or music in this practical, hands-on guide. Data scientists and software engineers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to your needs, and how to combine existing building blocks to create new models and creative applications in different domains. This book introduces theoretical concepts in an intuitive way, with extensive code samples and illustrations that you can run on services such as Google Colaboratory, Kaggle, or Hugging Face Spaces with minimal setup. You'll learn how to use open source libraries such as Transformers and Diffusers, conduct code exploration, and study several existing projects to help guide your work. Learn the fundamentals of classic and modern generative AI techniquesBuild and customize models that can generate text, images, and soundExplore trade-offs between training from scratch and using large, pretrained modelsCreate models that can modify images by transferring the style of other images Tweak and bend transformers and diffusion models for creative purposesTrain a model that can write text based on your style Deploy models as interactive demos or services 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781098149246
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Paperback. Condition: New. 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 imagesExplore trade-offs between using a pretrained model and fine-tuning your own modelCreate and utilize models that can generate, edit, and modify images in any styleCustomize transformers and diffusion models for multiple creative purposesTrain models that can reflect your own unique style. Seller Inventory # LU-9781098149246
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