uses torch load

app.py

@@ -5,7 +5,7 @@ import numpy as np
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
-with open('cnn_model_9961_sm.bin', 'rb') as f:
+with open('cnn_model.bin', 'rb') as f:
     # nn = pickle.load(f)
     nn = torch.load(f, map_location=torch.device('cpu'))
 
@@ -27,7 +27,7 @@ def predict(input):
 demo = gr.Interface(
     fn=predict,
     title='ConvNet for handwritten digits classification',
-    description='Check this out <a href="google.com">Google</a>',
+    description='Created using Python and Numpy only.',
     inputs=[
         gr.Sketchpad(
             shape=(28, 28),