Update app.py

app.py

@@ -204,18 +204,18 @@ with gr.Blocks(fill_width=True) as demo:
     
     
     with gr.Tab("Event Type Classification"):
+        gr.Markdown(
+        """
+        # T4.5 Relevance Classifier Demo 
+        This is a demo created to explore floods and wildfire classification in social media posts.\n
+        Usage:\n
+            - Upload .tsv or .csv 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
+        """)
         with gr.Row():
             with gr.Column(scale=4):
-                gr.Markdown(
-                """
-                # T4.5 Relevance Classifier Demo 
-                This is a demo created to explore floods and wildfire classification in social media posts.\n
-                Usage:\n
-                    - Upload .tsv or .csv 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
-                """)
                 T_file_input = gr.File(label="Upload CSV or TSV File", file_types=['.tsv', '.csv']) 
                 T_text_field = gr.Textbox(label="Text field name", value="tweet_text")
                 T_event_model = gr.Dropdown(event_models, value=event_models[0], label="Select classification model")