From 20c2ab026916fcdc808dbb89d56199883dfea632 Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 6 Jun 2022 18:17:15 +0200
Subject: [PATCH 1/2] Update README.md

---
 README.md | 26 ++++++++------------------
 1 file changed, 8 insertions(+), 18 deletions(-)

diff --git a/README.md b/README.md
index c03553078c..62f608fee1 100644
--- a/README.md
+++ b/README.md
@@ -80,28 +80,18 @@ image_pil.save("test.png")
 Example:
 
 ```python
-from diffusers import UNetModel, GaussianDDPMScheduler
 from modeling_ddpm import DDPM
-import tempfile
 
-unet = UNetModel.from_pretrained("fusing/ddpm_dummy")
-sampler = GaussianDDPMScheduler.from_config("fusing/ddpm_dummy")
-
-# compose Diffusion Pipeline
-ddpm = DDPM(unet, sampler)
-# generate / sample
+ddpm = DDPM.from_pretrained("fusing/ddpm-lsun-bedroom-pipe")
 image = ddpm()
-print(image)
 
-
-# save and load with 0 extra code (handled by general `DiffusionPipeline` class)
-# will also be possible to do so from the Hub
-with tempfile.TemporaryDirectory() as tmpdirname:
-    ddpm.save_pretrained(tmpdirname)
-    print("Model saved")
-    ddpm_new = DDPM.from_pretrained(tmpdirname)
-    print("Model loaded")
-    print(ddpm_new)
+import PIL.Image
+import numpy as np
+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])
+image_pil.save("test.png")
 ```
 
 ## Library structure:

From 7ec721c5f7309229be7c1067786cacd9bad9ea8f Mon Sep 17 00:00:00 2001
From: Patrick von Platen <patrick.v.platen@gmail.com>
Date: Mon, 6 Jun 2022 18:19:02 +0200
Subject: [PATCH 2/2] Update README.md

---
 README.md | 17 +++++++++++++----
 1 file changed, 13 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 62f608fee1..b24623887a 100644
--- a/README.md
+++ b/README.md
@@ -67,10 +67,13 @@ for t in reversed(range(len(scheduler))):
     sampled_prev_image = prev_image + prev_variance
     image = sampled_prev_image
 
+# 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])
+
+# save image
 image_pil.save("test.png")
 ```
 
@@ -81,16 +84,22 @@ Example:
 
 ```python
 from modeling_ddpm import DDPM
-
-ddpm = DDPM.from_pretrained("fusing/ddpm-lsun-bedroom-pipe")
-image = ddpm()
-
 import PIL.Image
 import numpy as np
+
+# load model and scheduler
+ddpm = DDPM.from_pretrained("fusing/ddpm-lsun-bedroom-pipe")
+
+# 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])
+
+# save image
 image_pil.save("test.png")
 ```