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<! |
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with |
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the License. You may obtain a copy of the License at |
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http://www.apache.org/licenses/LICENSE-2.0 |
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on |
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the |
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specific language governing permissions and limitations under the License. |
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# Pipelines |
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The [`DiffusionPipeline`] is the easiest way to load any pretrained diffusion pipeline from the [Hub](https://huggingface.co/models?library=diffusers) and to use it in inference. |
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<Tip> |
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One should not use the Diffusion Pipeline class for training or fine-tuning a diffusion model. Individual |
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components of diffusion pipelines are usually trained individually, so we suggest to directly work |
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with [`UNetModel`] and [`UNetConditionModel`]. |
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</Tip> |
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Any diffusion pipeline that is loaded with [`~DiffusionPipeline.from_pretrained`] will automatically |
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detect the pipeline type, *e.g.* [`StableDiffusionPipeline`] and consequently load each component of the |
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pipeline and pass them into the `__init__` function of the pipeline, *e.g.* [`~StableDiffusionPipeline.__init__`]. |
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Any pipeline object can be saved locally with [`~DiffusionPipeline.save_pretrained`]. |
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## DiffusionPipeline |
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[[autodoc]] DiffusionPipeline |
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- all |
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- __call__ |
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- device |
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- to |
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- components |
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## ImagePipelineOutput |
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By default diffusion pipelines return an object of class |
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[[autodoc]] pipelines.ImagePipelineOutput |
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## AudioPipelineOutput |
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By default diffusion pipelines return an object of class |
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[[autodoc]] pipelines.AudioPipelineOutput |
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