ipe = UniDiffuserPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
pipe.to(device)

# Image variation can be performed with an image-to-text generation followed by a text-to-image generation:
# 1. Image-to-text generation
image_url = "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/unidiffuser/unidiffuser_example_image.jpg"
init_image = load_image(image_url).resize((512, 512))

sample = pipe