Update README.md

README.md

@@ -5,26 +5,78 @@ library_name: diffusers
 
 # Stage-A-ft-HQ
 
-`stage-a-ft-hq` is a version of [Würstchen](https://huggingface.co/warp-ai/wuerstchen)'s **Stage A** that was finetuned to generate sharper details and textures. <br/>
+`stage-a-ft-hq` is a version of [Würstchen](https://huggingface.co/warp-ai/wuerstchen)'s **Stage A** that was finetuned to have slightly-nicer-looking textures.
+
 `stage-a-ft-hq` works with any Würstchen-derived model (including [Stable Cascade](https://huggingface.co/stabilityai/stable-cascade)).
 
-> TODO: comparison goes here
+## Example comparison
+
+| Stable Cascade                    | Stable Cascade + `stage-a-ft-hq`   |
+| --------------------------------- | ---------------------------------- |
+| ![](example_baseline.png)         | ![](example_finetuned.png)         |
+| ![](example_baseline_closeup.png) | ![](example_finetuned_closeup.png) |
+
 
 ## 🧨 Diffusers Usage
 
+⚠️ As of 2024-02-17, Stable Cascade's [PR](https://github.com/huggingface/diffusers/pull/6487) is still under review.
+I've only confirmed Stable Cascade working with this particular version of the PR:
+```bash
+pip install --upgrade --force-reinstall https://github.com/kashif/diffusers/archive/a3dc21385b7386beb3dab3a9845962ede6765887.zip
+```
+
 ```py
-# TODO: code goes here
+import torch
+
+# Load the Stage-A-ft-HQ model
+from diffusers.pipelines.wuerstchen import PaellaVQModel
+stage_a_ft_hq = PaellaVQModel.from_pretrained("madebyollin/stage_a_ft_hq", torch_dtype=torch.float16)
+
+# Load the normal Stable Cascade pipeline
+from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
+
+device = "cuda"
+num_images_per_prompt = 2
+
+prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=torch.bfloat16).to(device)
+decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=torch.float16).to(device)
+
+# Swap in the Stage-A-ft-HQ model
+decoder.vqgan = stage_a_ft_hq
+
+prompt = "Anthropomorphic cat dressed as a pilot"
+negative_prompt = ""
+
+prior_output = prior(
+    prompt=prompt,
+    height=1024,
+    width=1024,
+    negative_prompt=negative_prompt,
+    guidance_scale=4.0,
+    num_images_per_prompt=num_images_per_prompt,
+    num_inference_steps=20
+)
+decoder_output = decoder(
+    image_embeddings=prior_output.image_embeddings.half(),
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    guidance_scale=0.0,
+    output_type="pil",
+    num_inference_steps=10
+).images
+
+display(decoder_output[0])
 ```
 
 ## Explanation
 
-Image generators like Würstchen and Stable Cascade create images via a multi-stage process. <br/>
+Image generators like Würstchen and Stable Cascade create images via a multi-stage process.
 Stage A is the ultimate stage, responsible for rendering out full-resolution, human-interpretable images (based on the output from prior stages).
 
-The original Stage A tends to render slightly-smoothed-out images with a distinctive grain pattern on top.
+The original Stage A tends to render slightly-smoothed-out images with a distinctive noise pattern on top.
 
-`stage-a-ft-hq` was finetuned on a high-quality dataset in order to generate cleaner, sharper, more realistic textures with fewer distinctive artifacts.
+`stage-a-ft-hq` was finetuned briefly on a high-quality dataset in order to reduce these artifacts.
 
-## Recommended Settings
+## Suggested Settings
 
-To generate highly detailed images, you probably want to use `stage-a-ft-hq` (which improves very fine detail) in combination with a large Stage B step count (which improves mid-level detail).
+To generate highly detailed images, you probably want to use `stage-a-ft-hq` (which improves very fine detail) in combination with a large Stage B step count (which [improves mid-level detail](https://old.reddit.com/r/StableDiffusion/comments/1ar359h/cascade_can_generate_directly_at_1536x1536_and/kqhjtk5/)).