#BentoML

BentoML is an open-source Python framework crafted for creating and deploying AI model serving systems. It enables seamless conversion of model scripts into REST API servers, supporting diverse ML frameworks and runtimes, while simplifying dependency management through straightforward configuration files. Optimized for high-performance, BentoML enhances resource usage with features like dynamic batching and model parallelism. Deploy models effortlessly using Docker containers or integrate smoothly with BentoCloud, offering a versatile solution for both local and production settings.

This guide illustrates the deployment and self-hosting of diffusion models with BentoML, specifically focusing on Stable Diffusion models for generating images and video from text prompts. It provides instructions to set up the SDXL Turbo model with an Nvidia GPU (minimum 12GB VRAM), details dependency installation, and local BentoML service execution. Interaction is possible through Swagger UI or cURL. For scalable solutions, it includes guidance on deploying to BentoCloud. The repository supports various models such as ControlNet, Latent Consistency Model, and Stable Video Diffusion, ensuring efficient deployment for both local and cloud environments.