<!--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. --> # Models Diffusers contains pretrained models for popular algorithms and modules for creating the next set of diffusion models. The primary function of these models is to denoise an input sample, by modeling the distribution $p_\theta(\mathbf{x}_{t-1}|\mathbf{x}_t)$. 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. ## ModelMixin [[autodoc]] ModelMixin ## UNet2DOutput [[autodoc]] models.unet_2d.UNet2DOutput ## UNet2DModel [[autodoc]] UNet2DModel ## UNet1DOutput [[autodoc]] models.unet_1d.UNet1DOutput ## UNet1DModel [[autodoc]] UNet1DModel ## UNet2DConditionOutput [[autodoc]] models.unet_2d_condition.UNet2DConditionOutput ## UNet2DConditionModel [[autodoc]] UNet2DConditionModel ## UNet3DConditionOutput [[autodoc]] models.unet_3d_condition.UNet3DConditionOutput ## UNet3DConditionModel [[autodoc]] UNet3DConditionModel ## DecoderOutput [[autodoc]] models.vae.DecoderOutput ## VQEncoderOutput [[autodoc]] models.vq_model.VQEncoderOutput ## VQModel [[autodoc]] VQModel ## AutoencoderKLOutput [[autodoc]] models.autoencoder_kl.AutoencoderKLOutput ## AutoencoderKL [[autodoc]] AutoencoderKL ## Transformer2DModel [[autodoc]] Transformer2DModel ## Transformer2DModelOutput [[autodoc]] models.transformer_2d.Transformer2DModelOutput ## TransformerTemporalModel [[autodoc]] models.transformer_temporal.TransformerTemporalModel ## Transformer2DModelOutput [[autodoc]] models.transformer_temporal.TransformerTemporalModelOutput ## PriorTransformer [[autodoc]] models.prior_transformer.PriorTransformer ## PriorTransformerOutput [[autodoc]] models.prior_transformer.PriorTransformerOutput ## ControlNetOutput [[autodoc]] models.controlnet.ControlNetOutput ## ControlNetModel [[autodoc]] ControlNetModel ## FlaxModelMixin [[autodoc]] FlaxModelMixin ## FlaxUNet2DConditionOutput [[autodoc]] models.unet_2d_condition_flax.FlaxUNet2DConditionOutput ## FlaxUNet2DConditionModel [[autodoc]] FlaxUNet2DConditionModel ## FlaxDecoderOutput [[autodoc]] models.vae_flax.FlaxDecoderOutput ## FlaxAutoencoderKLOutput [[autodoc]] models.vae_flax.FlaxAutoencoderKLOutput ## FlaxAutoencoderKL [[autodoc]] FlaxAutoencoderKL ## FlaxControlNetOutput [[autodoc]] models.controlnet_flax.FlaxControlNetOutput ## FlaxControlNetModel [[autodoc]] FlaxControlNetModel