Update app.py

app.py

@@ -20,7 +20,7 @@ class_names = [line.strip() for line in open("classes.txt")]
 # Load the model
 model = torchvision.models.vit_b_16(weights=None)  # Initialize the model architecture
 model.heads = nn.Linear(in_features=768, out_features=len(class_names))  # Adjust the classifier head
-checkpoint = torch.load('08_pretrained_vit_feature_extractor_pizza_steak_sushi.pth')
+checkpoint = torch.load('08_pretrained_vit_feature_extractor_pizza_steak_sushi.pth', map_location=torch.device('cpu'))
 model.load_state_dict(checkpoint, strict=False)
 model = model.to(device)
 model.eval()
@@ -69,7 +69,7 @@ iface = gr.Interface(
     fn=predict, 
     inputs=gr.Image(type="numpy"), 
     outputs=[gr.Textbox(label="Top Prediction"), gr.Plot()],  # Textbox for top prediction and Plot for the bar chart
-    examples=[r"C:\Users\Asus\Desktop\download (1).jpg", r"C:\Users\Asus\Desktop\download (3).jpg"]  # Optional: Add paths to example images
+    examples=["Image  1.jpg", "Image 2"]  # Optional: Add paths to example images
 )
 
 # Launch the Gradio app