nerator = torch.manual_seed(33)
output = pipe(class_labels=class_ids, num_inference_steps=25, generator=generator)

image = output.images[0]  # label 'white shark'

DiTPipeline
	

class diffusers.DiTPipeline

<
source
>
(
transformer: Transformer2DModel
vae: AutoencoderKL
scheduler: KarrasDiffusionSchedulers
id2label: typing.Union[typing.Dict[int, str], NoneType] = None

)


Parameters 

transformer (Transformer2DModel) —
Class conditioned Tran