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', 'PolContro'
+    '#P', 'Model', 'UGI 🏆', 'W/10 👍', 'Unruly', 'Internet', 'CrimeStats', 'Stories/Jokes', 'PolContro'
 ]
 
 # Load the leaderboard data from a CSV file
@@ -61,9 +61,9 @@ GraInter = gr.Blocks()
 with GraInter:
     gr.HTML("""<h1 align="center">UGI Leaderboard</h1>""")
     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.
+    UGI: Uncensored General Intelligence. The average of 5 different subjects that LLMs are commonly steered away from. The leaderboard is made of roughly 60 questions/tasks, measuring both "willingness to answer" and "accuracy" in fact-based controversial questions.
     
-    Willingness: A more narrow, 10-point score, solely measuring the LLM's willingness to answer controversial questions.
+    W/10: A more narrow, 10-point score, solely measuring the LLM's Willingness to answer controversial questions.
     
     Unruly: Knowledge of activities that are generally frowned upon.