docs/source/en/api/diffusion_pipeline.md

<!--Copyright 2023 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Pipelines

The [`DiffusionPipeline`] is the quickest way to load any pretrained diffusion pipeline from the [Hub](https://huggingface.co/models?library=diffusers) for inference.

<Tip>

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.

</Tip>

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