Update README.md

README.md

@@ -4,20 +4,40 @@ license: mit
 
 ## How to run
 
-```python
-import torch
-from diffusers import AutoPipelineForText2Image
-from diffusers.pipelines.wuerstchen import WuerstchenPrior
+This pipeline should be run together with https://huggingface.co/warp-diffusion/wuerstchen:
 
-prior_model = WuerstchenPrior.from_pretrained("warp-diffusion/wuerstchen-prior", torch_dtype=torch.float16)
-pipe = AutoPipelineForText2Image.from_pretrained("warp-diffusion/wuerstchen", prior_prior=prior_model, torch_dtype=torch.float16).to("cuda")
+```py
+import torch                                                                                                                                                                                                                                                                    
+from diffusers import WuerstchenDecoderPipeline, WuerstchenPriorPipeline                                                                                                                                                                                                        
+                                                                                                                                                                                                                                                                                
+device = "cuda"                                                                                                                                                                                                                                                                 
+dtype = torch.float16                                                                                                                                                                                                                                                           
+num_images_per_prompt = 2                                                                                                                                                                                                                                                       
+                                                                                                                                                                                                                                                                                
+prior_pipeline = WuerstchenPriorPipeline.from_pretrained(                                                                                                                                                                                                                       
+    "warp-diffusion/wuerstchen-prior", torch_dtype=dtype                                                                                                                                                                                                                        
+).to(device)                                                                                                                                                                                                                                                                    
+decoder_pipeline = WuerstchenDecoderPipeline.from_pretrained(                                                                                                                                                                                                                   
+    "warp-diffusion/wuerstchen", torch_dtype=dtype                                                                                                                                                                                                                              
+).to(device)                                                                                                                                                                                                                                                                    
+                                                                                                                                                                                                                                                                                
+caption = "A captivating artwork of a mysterious stone golem"
+negative_prompt = ""
 
-prompt = [
-    "An old destroyed car standing on a cliff in norway, cinematic photography",
-    "Western movie, closeup cinematic photography",
-    "Pink nike shoe commercial, closeup cinematic photography",
-    "Croatia, closeup cinematic photography",
-    "South Tyrol mountains at sunset, closeup cinematic photography",
-]
-images = pipe(prompt, guidance_scale=8.0, width=1024, height=1024).images
+prior_output = prior_pipeline(
+    prompt=caption,
+    height=1024,
+    width=1024,
+    negative_prompt=negative_prompt,
+        guidance_scale=4.0,
+    num_images_per_prompt=num_images_per_prompt,
+)
+decoder_output = decoder_pipeline(
+    image_embeddings=prior_output.image_embeddings,
+    prompt=caption,
+    negative_prompt=negative_prompt,
+    num_images_per_prompt=num_images_per_prompt,
+    guidance_scale=0.0,
+    output_type="pil",
+).images
 ```