Update app.py

app.py

@@ -16,7 +16,7 @@ else:
 
 pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
 #pipe.unet.load_adapter("um235/cartoon_cat_stickers")
-#pipe.unet = PeftModel.from_pretrained(pipe.unet,"um235/cartoon_cat_stickers")
+pipe.unet = PeftModel.from_pretrained(pipe.unet,"um235/cartoon_cat_stickers")
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -59,7 +59,7 @@ def infer(
 
 
 examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "Sticker, cartoon-style cat character with soft yellow fur. A gentle cat with expressive eyes that shine with a sad, emotional look. The cat, with a small pink nose and a flower on its head, appears to be crying, with blue teardrops around its eyes, giving the sticker a simple yet poignant design.",
     "An astronaut riding a green horse",
     "A delicious ceviche cheesecake slice",
 ]
@@ -121,7 +121,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Replace with defaults that work for your model
                 )
 
                 height = gr.Slider(
@@ -129,7 +129,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Replace with defaults that work for your model
                 )
 
             with gr.Row():