Update README.md

README.md

@@ -62,13 +62,33 @@ pip install diffusers
 
 ```python
 import torch
-from diffusers import StableCascadeCombinedPipeline
+from diffusers import StableCascadeCombinedPipeline, StableCascadePriorPipeline, StableCascadeDecoderPipeline
+
+
 
 device = "cuda"
 dtype = torch.bfloat16
-model = "Disty0/sotediffusion-wuerstchen3-alpha1-decoder"
 
-pipe = StableCascadeCombinedPipeline.from_pretrained(model, torch_dtype=dtype)
+prior_model = "Disty0/sotediffusion-wuerstchen3-alpha1"
+decoder_model = "Disty0/sotediffusion-wuerstchen3-alpha1-decoder"
+
+
+prior = diffusers.StableCascadePriorPipeline.from_pretrained(prior_model, torch_dtype=dtype)
+decoder = diffusers.StableCascadeDecoderPipeline.from_pretrained(decoder_model, torch_dtype=dtype)
+
+pipe = diffusers.StableCascadeCombinedPipeline(
+    tokenizer=decoder.tokenizer,
+    text_encoder=decoder.text_encoder,
+    decoder=decoder.decoder,
+    scheduler=decoder.scheduler,
+    vqgan=decoder.vqgan,
+    prior_prior=prior.prior,
+    prior_text_encoder=prior.text_encoder,
+    prior_tokenizer=prior.tokenizer,
+    prior_scheduler=prior.scheduler,
+    prior_feature_extractor=prior.feature_extractor,
+    prior_image_encoder=prior.image_encoder)
+
 
 # send everything to the gpu:
 pipe = pipe.to(device, dtype=dtype)
@@ -79,16 +99,16 @@ pipe.prior_pipe = pipe.prior_pipe.to(device, dtype=dtype)
 
 
 
-prompt = "extremely aesthetic, best quality, newest, general, 1girl, solo, looking at viewer, blush, slight smile, cat ears, long hair, dress, bare shoulders, cherry blossoms, flowers, petals, vegetation, wind,"
-negative_prompt = "very displeasing, worst quality, oldest, monochrome, sketch, loli, child,"
+prompt = "1girl, solo, cowboy shot, straight hair, looking at viewer, hoodie, indoors, slight smile, casual, furniture, doorway, very aesthetic, best quality, newest,"
+negative_prompt = "very displeasing, worst quality, oldest, monochrome, sketch, realistic,"
 
 output = pipe(
     width=1024,
     height=1536,
     prompt=prompt,
     negative_prompt=negative_prompt,
-    decoder_guidance_scale=1.2,
-    prior_guidance_scale=8.0,
+    decoder_guidance_scale=1.0,
+    prior_guidance_scale=12.0,
     prior_num_inference_steps=40,
     output_type="pil",
     num_inference_steps=10