Update app.py

app.py

@@ -405,7 +405,6 @@
 
 # if __name__ == "__main__":
 #     demo.launch()
-
 import gradio as gr
 import pandas as pd
 from datasets import load_dataset
@@ -1278,9 +1277,9 @@ with gr.Blocks(
                     ranking_method = gr.Radio(
                         ["Combined Score (WER 70%, CER 30%)", "WER Only", "CER Only"], 
                         label="🔄 Ranking Method",
-                        value="Combined Score (WER 70%, CER 30%)",
-                        info="Choose how to rank the models"
+                        value="Combined Score (WER 70%, CER 30%)"
                     )
+                    gr.Markdown("*Choose how to rank the models*")
                 
                 leaderboard_view = gr.DataFrame(
                     value=initial_leaderboard,
@@ -1347,23 +1346,23 @@ with gr.Blocks(
                         with gr.Column(scale=2):
                             model_name_input = gr.Textbox(
                                 label="🤖 Model Name", 
-                                placeholder="e.g., MALIBA-AI/bambara-whisper-large",
-                                info="Use a descriptive name (organization/model format preferred)"
+                                placeholder="e.g., MALIBA-AI/bambara-whisper-large"
                             )
+                            gr.Markdown("*Use a descriptive name (organization/model format preferred)*")
                             
                             model_type = gr.Dropdown(
                                 label="🏷️ Model Type",
                                 choices=["Whisper-based", "Wav2Vec2", "Foundation", "Custom", "Fine-tuned", "Multilingual", "Other"],
-                                value="Custom",
-                                info="Select the type/architecture of your model"
+                                value="Custom"
                             )
+                            gr.Markdown("*Select the type/architecture of your model*")
                             
                             origin_country = gr.Dropdown(
                                 label="🌍 Origin/Institution",
                                 choices=["Mali", "Senegal", "Burkina Faso", "Niger", "Guinea", "Ivory Coast", "USA", "France", "Canada", "UK", "Other"],
-                                value="Mali",
-                                info="Country or region of the developing institution"
+                                value="Mali"
                             )
+                            gr.Markdown("*Country or region of the developing institution*")
                         
                         with gr.Column(scale=1):
                             gr.Markdown("""
@@ -1383,9 +1382,9 @@ with gr.Blocks(
                 
                 csv_upload = gr.File(
                     label="📁 Upload Predictions CSV", 
-                    file_types=[".csv"],
-                    info="Upload your model's transcriptions in the required CSV format"
+                    file_types=[".csv"]
                 )
+                gr.Markdown("*Upload your model's transcriptions in the required CSV format*")
                 
                 submit_btn = gr.Button("🚀 Submit Model", variant="primary", size="lg", elem_classes=['gradio-button', 'primary'])
                 
@@ -1420,14 +1419,15 @@ with gr.Blocks(
                     
                     model_1_dropdown = gr.Dropdown(
                         choices=model_names,
-                        label="🤖 Model 1",
-                        info="Select the first model for comparison"
+                        label="🤖 Model 1"
                     )
+                    gr.Markdown("*Select the first model for comparison*")
+                    
                     model_2_dropdown = gr.Dropdown(
                         choices=model_names,
-                        label="🤖 Model 2", 
-                        info="Select the second model for comparison"
+                        label="🤖 Model 2"
                     )
+                    gr.Markdown("*Select the second model for comparison*")
                 
                 compare_btn = gr.Button("⚡ Compare Models", variant="primary", elem_classes=['gradio-button', 'primary'])