Update app.py

app.py

@@ -28,8 +28,8 @@ This enables training on a wide range of transcription datasets with a single mo
 
 They use a simple two-stage process: MIDI to spectrograms with an encoder-decoder Transformer, then spectrograms to audio with a generative adversarial network (GAN) spectrogram inverter.
 """
-examples = []
 
+examples = ["examples/beethoven_mond_2.mid", "examples/beethoven_hammerklavier_2.mid"]
 
 gr.Interface(
     fn=predict,
@@ -41,5 +41,6 @@ gr.Interface(
     ],
     title=title,
     description=description,
-    theme='gstaff/xkcd',
+    theme='gradio/monochrome',
+    examples=examples,
 ).launch(debug=True)