load on cpu

app.py

@@ -17,8 +17,7 @@ device = "cpu"
 effnetb2, effnetb2_transforms = create_effnetb2_model(num_classes=len(class_names))
 
 # Load saved weights
-effnetb2.load_state_dict(torch.load("effnetb2.pth"), 
-                         map_location=torch.device(device))
+effnetb2.load_state_dict(torch.load("effnetb2.pth", map_location=torch.device(device)))
 
 # Define predict function
 def predict(img: Image) -> Tuple[dict, float]:
@@ -60,4 +59,4 @@ demo = gr.Interface(
     article=article,
 )
 
-demo.lauch()
+demo.lauch()