# Pipelines The [`DiffusionPipeline`] is the quickest way to load any pretrained diffusion pipeline from the [Hub](https://huggingface.co/models?library=diffusers) for inference. You shouldn't use the [`DiffusionPipeline`] class for training or finetuning a diffusion model. Individual components (for example, [`UNet2DModel`] and [`UNet2DConditionModel`]) of diffusion pipelines are usually trained individually, so we suggest directly working with them instead. The pipeline type (for example [`StableDiffusionPipeline`]) of any diffusion pipeline loaded with [`~DiffusionPipeline.from_pretrained`] is automatically detected and pipeline components are loaded and passed to the `__init__` function of the pipeline. Any pipeline object can be saved locally with [`~DiffusionPipeline.save_pretrained`]. ## DiffusionPipeline [[autodoc]] DiffusionPipeline - all - __call__ - device - to - components