diffusers/pr_12652/en/api/models/allegro_transformer3d.md

AllegroTransformer3DModel

A Diffusion Transformer model for 3D data from Allegro was introduced in Allegro: Open the Black Box of Commercial-Level Video Generation Model by RhymesAI.

The model can be loaded with the following code snippet.

from diffusers import AllegroTransformer3DModel

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

AllegroTransformer3DModel[[diffusers.AllegroTransformer3DModel]]

diffusers.AllegroTransformer3DModel[[diffusers.AllegroTransformer3DModel]]

Source

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

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

Source

The output of Transformer2DModel.

Parameters:

sample (torch.Tensor of shape (batch_size, num_channels, height, width) or (batch size, num_vector_embeds - 1, num_latent_pixels) if Transformer2DModel is discrete) : The hidden states output conditioned on the encoder_hidden_states input. If discrete, returns probability distributions for the unnoised latent pixels.