Update the demo code without the post-processing steps and with the new API

README.md

@@ -19,25 +19,17 @@ tags:
 ```python
 # !pip install diffusers
 from diffusers import DiffusionPipeline
-import PIL.Image
-import numpy as np
 
-model_id = "google/ddpm-celeba-hq"
+model_id = "google/ddpm-celebahq-256"
 
 # load model and scheduler
 ddpm = DiffusionPipeline.from_pretrained(model_id)
 
 # run pipeline in inference (sample random noise and denoise)
-image = ddpm()
-
-# process image to PIL
-image_processed = image.cpu().permute(0, 2, 3, 1)
-image_processed = (image_processed + 1.0) * 127.5
-image_processed = image_processed.numpy().astype(np.uint8)
-image_pil = PIL.Image.fromarray(image_processed[0])
+images = ddpm()["sample"]
 
 # save image
-image_pil.save("test.png")
+images[0].save("ddpm_generated_image.png")
 ```
 
 ## Samples