Update README.md

README.md

@@ -66,7 +66,7 @@ steps), SDXL (50 inference steps), SDXL Turbo (1 inference step) and Würstchen
 
 ## Code Example
 
-For the code below to work, you have to install `diffusers` from this branch while the PR is WIP.
+**⚠️ Important**: For the code below to work, you have to install `diffusers` from this branch while the PR is WIP.
 
 ```shell
 pip install git+https://github.com/kashif/diffusers.git@wuerstchen-v3
@@ -77,11 +77,10 @@ import torch
 from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
 
 device = "cuda"
-dtype = torch.bfloat16
 num_images_per_prompt = 2
 
-prior = StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", torch_dtype=dtype).to(device)
-decoder = StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade",  torch_dtype=dtype).to(device)
+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)
 
 prompt = "Anthropomorphic cat dressed as a pilot"
 negative_prompt = ""
@@ -93,16 +92,18 @@ prior_output = prior(
     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,
+    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
 
-decoder_output
+#Now decoder_output is a list with your PIL images
 ```
 
 ## Uses