add more examples

app.py

@@ -84,12 +84,6 @@ def _predict(inputs):
             predicted_images.append((str(image_url), f"Confidence: {top_pred['score']}, \n image url: {image_url}"))
 
     return predicted_images
-    # for image in images:
-
-    #     top_pred = classif_pipeline(image, top_k=1)[0]
-    #     if top_pred['label'] == 'illustrated':
-    #         predicted_images.append((image, top_pred['score']))
-    #     return predicted_images
 
 
 gallery = gr.Gallery()
@@ -101,6 +95,7 @@ demo = gr.Interface(
     outputs=gallery,
     title="ImageIN",
     description="Identify illustrations in pages of historical books!",
-    examples=['https://iiif.lib.harvard.edu/manifests/drs:427603172']
+    examples=['https://iiif.lib.harvard.edu/manifests/drs:427603172',
+              "https://iiif.lib.harvard.edu/manifests/drs:427342693","https://iiif.archivelab.org/iiif/holylandbiblebok0000cunn/manifest.json"]
 )
 demo.launch(debug=True)