Update app.py

app.py

@@ -9,14 +9,14 @@ import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_repo_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"  # Replace to the model you would like to use
-
 if torch.cuda.is_available():
     torch_dtype = torch.float16
 else:
     torch_dtype = torch.float32
 
 pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe.unet.load_adapter("um235/cartoon_cat_stickers")
+#pipe.unet.load_adapter("um235/cartoon_cat_stickers")
+pipe.unet = PeftModel.from_pretrained("um235/cartoon_cat_stickers")
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -42,7 +42,7 @@ def infer(
     generator = torch.Generator().manual_seed(seed)
     
     pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
-    if (model_repo_id=="stable-diffusion-v1-5/stable-diffusion-v1-5"): pipe.unet.load_adapter("um235/cartoon_cat_stickers")
+    if (model_repo_id=="stable-diffusion-v1-5/stable-diffusion-v1-5"): pipe.unet = PeftModel.from_pretrained("um235/cartoon_cat_stickers")
     pipe = pipe.to(device)
 
     image = pipe(