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| # ConsisIDTransformer3DModel | |
| A Diffusion Transformer model for 3D data from [ConsisID](https://github.com/PKU-YuanGroup/ConsisID) was introduced in [Identity-Preserving Text-to-Video Generation by Frequency Decomposition](https://huggingface.co/papers/2411.17440) by Peking University & University of Rochester & etc. | |
| The model can be loaded with the following code snippet. | |
| ```python | |
| from diffusers import ConsisIDTransformer3DModel | |
| transformer = ConsisIDTransformer3DModel.from_pretrained("BestWishYsh/ConsisID-preview", subfolder="transformer", torch_dtype=torch.bfloat16).to("cuda") | |
| ``` | |
| ## ConsisIDTransformer3DModel | |
| [[autodoc]] ConsisIDTransformer3DModel | |
| ## Transformer2DModelOutput | |
| [[autodoc]] models.modeling_outputs.Transformer2DModelOutput | |