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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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# Models |
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Diffusers contains pretrained models for popular algorithms and modules for creating the next set of diffusion models. |
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The primary function of these models is to denoise an input sample, by modeling the distribution $p_\theta(\mathbf{x}_{t-1}|\mathbf{x}_t)$. |
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The models are built on the base class ['ModelMixin'] that is a `torch.nn.module` with basic functionality for saving and loading models both locally and from the HuggingFace hub. |
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## ModelMixin |
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[[autodoc]] ModelMixin |
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## UNet2DOutput |
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[[autodoc]] models.unet_2d.UNet2DOutput |
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## UNet2DModel |
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[[autodoc]] UNet2DModel |
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## UNet1DOutput |
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[[autodoc]] models.unet_1d.UNet1DOutput |
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## UNet1DModel |
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[[autodoc]] UNet1DModel |
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## UNet2DConditionOutput |
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[[autodoc]] models.unet_2d_condition.UNet2DConditionOutput |
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## UNet2DConditionModel |
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[[autodoc]] UNet2DConditionModel |
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## UNet3DConditionOutput |
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[[autodoc]] models.unet_3d_condition.UNet3DConditionOutput |
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## UNet3DConditionModel |
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[[autodoc]] UNet3DConditionModel |
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## DecoderOutput |
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[[autodoc]] models.vae.DecoderOutput |
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## VQEncoderOutput |
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[[autodoc]] models.vq_model.VQEncoderOutput |
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## VQModel |
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[[autodoc]] VQModel |
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## AutoencoderKLOutput |
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[[autodoc]] models.autoencoder_kl.AutoencoderKLOutput |
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## AutoencoderKL |
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[[autodoc]] AutoencoderKL |
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## Transformer2DModel |
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[[autodoc]] Transformer2DModel |
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## Transformer2DModelOutput |
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[[autodoc]] models.transformer_2d.Transformer2DModelOutput |
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## TransformerTemporalModel |
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[[autodoc]] models.transformer_temporal.TransformerTemporalModel |
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## Transformer2DModelOutput |
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[[autodoc]] models.transformer_temporal.TransformerTemporalModelOutput |
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## PriorTransformer |
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[[autodoc]] models.prior_transformer.PriorTransformer |
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## PriorTransformerOutput |
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[[autodoc]] models.prior_transformer.PriorTransformerOutput |
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## ControlNetOutput |
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[[autodoc]] models.controlnet.ControlNetOutput |
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## ControlNetModel |
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[[autodoc]] ControlNetModel |
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## FlaxModelMixin |
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[[autodoc]] FlaxModelMixin |
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## FlaxUNet2DConditionOutput |
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[[autodoc]] models.unet_2d_condition_flax.FlaxUNet2DConditionOutput |
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## FlaxUNet2DConditionModel |
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[[autodoc]] FlaxUNet2DConditionModel |
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## FlaxDecoderOutput |
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[[autodoc]] models.vae_flax.FlaxDecoderOutput |
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## FlaxAutoencoderKLOutput |
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[[autodoc]] models.vae_flax.FlaxAutoencoderKLOutput |
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## FlaxAutoencoderKL |
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[[autodoc]] FlaxAutoencoderKL |
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## FlaxControlNetOutput |
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[[autodoc]] models.controlnet_flax.FlaxControlNetOutput |
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## FlaxControlNetModel |
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[[autodoc]] FlaxControlNetModel |
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