latents sampled from a standard Gaussian prior) from a UniDiffuserPipeline will produce a (image, text) pair:   Copied import torch

from diffusers import UniDiffuserPipeline

device = "cuda"
model_id_or_path = "thu-ml/unidiffuser-v1"
pipe = UniDiffuserPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
pipe.to(device)

# Unconditional image and text generation. The generation task is automatically inferred.
sample = pipe(num_