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<!-- Copyright 2024 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. --> | ||
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# AutoencoderKLMochi | ||
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The 3D variational autoencoder (VAE) model with KL loss used in [Mochi](https://github.com/genmoai/models) was introduced in [Mochi 1 Preview](https://huggingface.co/genmo/mochi-1-preview) by Tsinghua University & ZhipuAI. | ||
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The model can be loaded with the following code snippet. | ||
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```python | ||
from diffusers import AutoencoderKLMochi | ||
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vae = AutoencoderKLMochi.from_pretrained("genmo/mochi-1-preview", subfolder="vae", torch_dtype=torch.float32).to("cuda") | ||
``` | ||
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## AutoencoderKLMochi | ||
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[[autodoc]] AutoencoderKLMochi | ||
- decode | ||
- all | ||
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## DecoderOutput | ||
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[[autodoc]] models.autoencoders.vae.DecoderOutput |
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<!-- Copyright 2024 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. --> | ||
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# MochiTransformer3DModel | ||
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A Diffusion Transformer model for 3D video-like data was introduced in [Mochi-1 Preview](https://huggingface.co/genmo/mochi-1-preview) by Genmo. | ||
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The model can be loaded with the following code snippet. | ||
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```python | ||
from diffusers import MochiTransformer3DModel | ||
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vae = MochiTransformer3DModel.from_pretrained("genmo/mochi-1-preview", subfolder="transformer", torch_dtype=torch.float16).to("cuda") | ||
``` | ||
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## MochiTransformer3DModel | ||
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[[autodoc]] MochiTransformer3DModel | ||
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## Transformer2DModelOutput | ||
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[[autodoc]] models.modeling_outputs.Transformer2DModelOutput |
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<!-- Copyright 2024 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. | ||
--> | ||
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# Mochi | ||
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[Mochi 1 Preview](https://huggingface.co/genmo/mochi-1-preview) from Genmo. | ||
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*Mochi 1 preview is an open state-of-the-art video generation model with high-fidelity motion and strong prompt adherence in preliminary evaluation. This model dramatically closes the gap between closed and open video generation systems. The model is released under a permissive Apache 2.0 license.* | ||
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<Tip> | ||
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Make sure to check out the Schedulers [guide](../../using-diffusers/schedulers.md) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](../../using-diffusers/loading.md#reuse-a-pipeline) section to learn how to efficiently load the same components into multiple pipelines. | ||
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</Tip> | ||
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## MochiPipeline | ||
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[[autodoc]] MochiPipeline | ||
- all | ||
- __call__ | ||
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## MochiPipelineOutput | ||
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[[autodoc]] pipelines.mochi.pipeline_output.MochiPipelineOutput |
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