Update app.py

app.py

@@ -96,13 +96,13 @@ with gr.Blocks() as demo:
         This is a demo created to explore floods and wildfire classification in social media posts.\n
         Usage:\n
         (1.) Upload .tsv data file (must contain a text column with social media posts).\n
-            -Next, type the name of the text column.\n
-            -Then, choose a BERT classifier model from the drop down.\n
-            -Finally, click the 'start prediction' buttton.\n
+        (2.) Next, type the name of the text column.\n
+        (3.) Then, choose a BERT classifier model from the drop down.\n
+        (4.) Finally, click the 'start prediction' buttton.\n
         Evaluation:\n
-            -To evaluate the model's accuracy select the INCORRECT classifications using the checkboxes in front of each post.\n
-            -Then, click on the 'Calculate Accuracy' button.\n
-            -Then, click on the 'Download data as CSV' to get the classifications and evaluation data as a .csv file.
+        (1.) To evaluate the model's accuracy select the INCORRECT classifications using the checkboxes in front of each post.\n
+        (2.) Then, click on the 'Calculate Accuracy' button.\n
+        (3.) Then, click on the 'Download data as CSV' to get the classifications and evaluation data as a .csv file.
         """)
         with gr.Row(equal_height=True):
             with gr.Column(scale=4):