Как деплоить диффузионные (diffusion) модели

Muse is an open-source text-to-image generator built on Stable Diffusion that also serves as a reference architecture for deploying diffusion-model applications with Lightning. The post explains how the project combines a React interface, a FastAPI model server, and a Lightning Work component that downloads and loads the model, accepts prompts, and returns base64-encoded images, with options for faster 25-step generation or higher-quality 50-step generation. After the initial deployment reached capacity at roughly 10 concurrent users, the team introduced a FastAPI round-robin load balancer, autoscaling based on request volume, and dynamic batching that queues and aggregates requests before sending them to model servers. These changes reportedly increased simultaneous request capacity from fewer than five to more than 300. Muse can also be integrated into Slack through a slash-command bot that generates and posts images from prompts. The project is presented as a reusable, clonable template demonstrating how Lightning can manage cloud resources, GPUs, storage, parallel workloads, and deployment infrastructure for scalable AI applications.

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