Update app.py

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 
 # Define the columns for the UGI Leaderboard
 UGI_COLS = [
-    '#P', 'Model', 'UGI 🏆', 'Willingness👍', 'Unruly', 'Internet', 'CrimeStats', 'Stories/Jokes', 'Pol Contro'
+    '#P', 'Model', 'UGI 🏆', 'Willingness👍', 'Unruly', 'Internet', 'CrimeStats', 'Stories/Jokes', 'PolContro'
 ]
 
 # Load the leaderboard data from a CSV file
@@ -57,11 +57,26 @@ def update_table(df: pd.DataFrame, query: str, param_ranges: dict) -> pd.DataFra
 demo = gr.Blocks()
 
 with demo:
-    gr.Markdown("## UGI Leaderboard", elem_classes="text-lg")
+    gr.Markdown("## UGI Leaderboard", elem_classes="text-lg text-center")
+    gr.Markdown("""
+    UGI: Uncensored General Intelligence. The average of 5 different subjects that LLMs are commonly steered away from. The leaderboard is made from roughly 60 questions overall, measuring both "willingness to answer" and "accuracy" in fact-based controversial questions.
+    
+    Willingness: A more narrow score, solely measuring the LLM's willingness to answer controversial questions.
+    
+    Unruly: Knowledge of activities that are generally frowned upon.
+    
+    Internet: Knowledge of various internet information, from professional to deviant.
+    
+    CrimeStats: Knowledge of crime statistics which are uncomfortable to talk about.
+    
+    Stories/Jokes: Ability to write offensive stories and jokes.
+    
+    PolContro: Knowledge of politically/socially controversial information.
+    """)
     with gr.Column():
         with gr.Row():
             search_bar = gr.Textbox(placeholder=" 🔍 Search for a model...", show_label=False)
-        with gr.Row():
+        with gr.Row(variant="compact"):
             gr.Markdown("Model sizes (in billions of parameters)", elem_classes="text-sm")
             param_range_1 = gr.Checkbox(label="~1.5", value=False)
             param_range_2 = gr.Checkbox(label="~3", value=False)