fusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")

>>> # run pipeline in inference (sample random noise and denoise)
>>> prompt = "A painting of a squirrel eating a burger"
>>> images = ldm([prompt], num_inference_steps=50, eta=0.3, guidance_scale=6).images

>>> # save images
>>> for idx, image in enumerate(images):
...     image.save(f"squirrel-{idx}.png")  LDMSuperResolutionPipeline  class diffusers.LDMSuperResolutionPipeline  <