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* Fix typos, improve, update * Change to trending and apply some Grammarly fixes * Grammarly fixes * Update loading_adapters.md * Update loading_adapters.md * Update other-formats.md * Update push_to_hub.md * Update loading_adapters.md * Update loading.md * Update docs/source/en/using-diffusers/push_to_hub.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update schedulers.md * Update docs/source/en/using-diffusers/loading.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/using-diffusers/loading_adapters.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update A1111 LoRA files part * Update other-formats.md --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
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Overview
🧨 Diffusers offers many pipelines, models, and schedulers for generative tasks. To make loading these components as simple as possible, we provide a single and unified method - from_pretrained() - that loads any of these components from either the Hugging Face Hub or your local machine. Whenever you load a pipeline or model, the latest files are automatically downloaded and cached so you can quickly reuse them next time without redownloading the files.
This section will show you everything you need to know about loading pipelines, how to load different components in a pipeline, how to load checkpoint variants, and how to load community pipelines. You'll also learn how to load schedulers and compare the speed and quality trade-offs of using different schedulers. Finally, you'll see how to convert and load KerasCV checkpoints so you can use them in PyTorch with 🧨 Diffusers.