took out examples from ui

app.py

@@ -23,9 +23,6 @@ feature_extractor = ViTFeatureExtractor()
 
 image = "cats.jpg"
 
-
-torch.hub.download_url_to_file('http://images.cocodataset.org/val2017/000000039769.jpg', 'cats.jpg')
-torch.hub.download_url_to_file('https://storage.googleapis.com/perceiver_io/dalmation.jpg', 'dog.jpg')
  
 feature_extractor = PerceiverFeatureExtractor.from_pretrained("deepmind/vision-perceiver-conv")
 model = PerceiverForImageClassificationConvProcessing.from_pretrained("deepmind/vision-perceiver-conv")
@@ -49,7 +46,7 @@ title = "Interactive demo: Perceiver for image classification"
 description = "Demo for classifying images with Perceiver IO. To use it, simply upload an image or use the example images below and click 'submit' to let the model predict the 5 most probable ImageNet classes. Results will show up in a few seconds."
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.14795'>Perceiver IO: A General Architecture for Structured Inputs & Outputs</a> | <a href='https://deepmind.com/blog/article/building-architectures-that-can-handle-the-worlds-data/'>Official blog</a></p>"
 
-gr.Interface(fn=classify_image, inputs=image, outputs=label, title=title, description=description, examples=examples, enable_queue=True).launch(debug=True)
+gr.Interface(fn=classify_image, inputs=image, outputs=label, title=title, description=description, examples="", enable_queue=True).launch(debug=True)