Understanding pipelines, models and schedulers            🧨 Diffusers is designed to be a user-friendly and flexible toolbox for building diffusion systems tailored to your use-case. At the core of the toolbox are models and schedulers. While the DiffusionPipeline bundles these components together for convenience, you can also unbundle the pipeline and use the models and schedulers separately to create new diffusion systems. In this tutorial, you’ll learn how to use models and schedulers to assemble a diffusion system for inference, starting with a basic pipeline and then progressing to the Stable Diffusion pipeline.  Deconstruct a basic pipeline A pipeline is a quick and easy way to run a model for inference, requiring no more than four lines of code to generate an image:   Copied >>> from diffusers import DDPMPipeline