Update app.py

app.py

@@ -43,14 +43,14 @@ def gradio_predict(image, question, max_tokens):
     return answer
     
     
-examples = [["data/week_01_page_024.png", 'Can you explain the slide?'], 
-            ["data/week_03_page_091.png", 'Can you explain the slide?'], 
-            ["data/week_01_page_062.png", 'Are the training images labeled?'], 
-            ["data/week_05_page_027.png", 'What is meant by eigenvalue multiplicity?'],
-            ["data/week_05_page_030.png", 'What does K represent?'], 
-            ["data/week_15_page_046.png", 'How are individual heterogeneous models trained?'], 
-            ["data/week_15_page_021.png", 'How does Bagging affect error?'],
-            ["data/week_15_page_037.png", "What does the '+' and '-' represent?"]]
+examples = [["data/week_01_page_024.png", 'Can you explain the slide?',100], 
+            ["data/week_03_page_091.png", 'Can you explain the slide?',100], 
+            ["data/week_01_page_062.png", 'Are the training images labeled?',100], 
+            ["data/week_05_page_027.png", 'What is meant by eigenvalue multiplicity?',100],
+            ["data/week_05_page_030.png", 'What does K represent?',100], 
+            ["data/week_15_page_046.png", 'How are individual heterogeneous models trained?',100], 
+            ["data/week_15_page_021.png", 'How does Bagging affect error?',100],
+            ["data/week_15_page_037.png", "What does the '+' and '-' represent?",100]]
 
 # Define the Gradio interface
 iface = gr.Interface(