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Text-to-image generative AI models, like Stable Diffusion, are transforming the creative industry by generating high-quality images from text descriptions. In this workshop, you'll learn how to build scalable systems for these models by creating an end-to-end pipeline for pre-training a Stable Diffusion model on a billion-scale dataset using Ray Data and Ray Train.
You'll explore how to efficiently stream data preprocessing and conduct distributed training across multiple GPUs. Additionally, you'll gain practical experience in deploying and scaling a Stable Diffusion model using Ray Serve, allowing you to deliver real-time, high-quality generative outputs.
By the end of this session, you'll have a solid understanding of how to implement a complete generative AI pipeline with Ray. You'll leave with the skills to pre-train, deploy, and scale Stable Diffusion models, ready to handle large-scale generative tasks and produce impressive results.
Prerequisites:
Basic familiarity with computer vision tasks, including common challenges with data processing, training, and inference.
Intermediate programming skills with Python.
Basic understanding of text-to-image use cases.
Ray Libraries:
Ray Data
Ray Train Ray Serve
You'll explore how to efficiently stream data preprocessing and conduct distributed training across multiple GPUs. Additionally, you'll gain practical experience in deploying and scaling a Stable Diffusion model using Ray Serve, allowing you to deliver real-time, high-quality generative outputs.
By the end of this session, you'll have a solid understanding of how to implement a complete generative AI pipeline with Ray. You'll leave with the skills to pre-train, deploy, and scale Stable Diffusion models, ready to handle large-scale generative tasks and produce impressive results.
Prerequisites:
Basic familiarity with computer vision tasks, including common challenges with data processing, training, and inference.
Intermediate programming skills with Python.
Basic understanding of text-to-image use cases.
Ray Libraries:
Ray Data
Ray Train Ray Serve
