setup device

app.py

@@ -6,7 +6,8 @@ import numpy as np
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 with open('cnn_model_9961_sm.bin', 'rb') as f:
-    nn = pickle.load(f)
+    # nn = pickle.load(f)
+    nn = torch.load(f, map_location=torch.device('cpu'))
 
 nn.to(device)
 
@@ -25,6 +26,8 @@ def predict(input):
 
 demo = gr.Interface(
     fn=predict,
+    title='ConvNet for handwritten digits classification',
+    description='Check this out <a href="google.com">Google</a>',
     inputs=[
         gr.Sketchpad(
             shape=(28, 28),
@@ -34,7 +37,7 @@ demo = gr.Interface(
     outputs=[
         gr.Label(
             num_top_classes=3,
-            scale=2,
+            scale=3,
         )
     ],
     live=True,