# AllegroTransformer3DModel

A Diffusion Transformer model for 3D data from [Allegro](https://github.com/rhymes-ai/Allegro) was introduced in [Allegro: Open the Black Box of Commercial-Level Video Generation Model](https://huggingface.co/papers/2410.15458) by RhymesAI.

The model can be loaded with the following code snippet.

```python
from diffusers import AllegroTransformer3DModel

transformer = AllegroTransformer3DModel.from_pretrained("rhymes-ai/Allegro", subfolder="transformer", torch_dtype=torch.bfloat16).to("cuda")
```

## AllegroTransformer3DModel[[diffusers.AllegroTransformer3DModel]]

- **hidden_states** (`torch.Tensor` of shape `(batch_size, num_channels, num_frames, height, width)`) --
  Input `hidden_states`.
- **encoder_hidden_states** (`torch.Tensor` of shape `(batch_size, sequence_len, embed_dims)`) --
  Conditional embeddings (embeddings computed from the input conditions such as prompts) to use.
- **timestep** (`torch.LongTensor`) --
  Used to indicate denoising step.
- **attention_mask** (`torch.Tensor`, *optional*) --
  Self-attention mask applied to `hidden_states`.
- **encoder_attention_mask** (`torch.Tensor`, *optional*) --
  Cross-attention mask applied to `encoder_hidden_states`.
- **image_rotary_emb** (`tuple` of `torch.Tensor`, *optional*) --
  Pre-computed rotary positional embeddings.
- **return_dict** (`bool`, *optional*, defaults to `True`) --
  Whether or not to return a `~models.transformer_2d.Transformer2DModelOutput` instead of a plain
  tuple.If `return_dict` is True, an `~models.transformer_2d.Transformer2DModelOutput` is returned, otherwise a
`tuple` where the first element is the sample tensor.

The [AllegroTransformer3DModel](/docs/diffusers/main/en/api/models/allegro_transformer3d#diffusers.AllegroTransformer3DModel) forward method.

## Transformer2DModelOutput[[diffusers.models.modeling_outputs.Transformer2DModelOutput]]

- **sample** (`torch.Tensor` of shape `(batch_size, num_channels, height, width)` or `(batch size, num_vector_embeds - 1, num_latent_pixels)` if [Transformer2DModel](/docs/diffusers/main/en/api/models/transformer2d#diffusers.Transformer2DModel) is discrete) --
  The hidden states output conditioned on the `encoder_hidden_states` input. If discrete, returns probability
  distributions for the unnoised latent pixels.

The output of [Transformer2DModel](/docs/diffusers/main/en/api/models/transformer2d#diffusers.Transformer2DModel).