Heatmap: Added model_size_threshold constant

server.py

@@ -841,7 +841,8 @@ class LeaderboardServer:
         original_scores = original_scores.loc[sorted_indices]  # Sort rows by model size
         
         # Bigger models
-        original_scores_sub = original_scores[sizes_series >= 16]
+        model_size_threshold = 16
+        original_scores_sub = original_scores[sizes_series >= model_size_threshold]
 
         # Apply quantile transformation independently for each row
         normalized_scores_sub = original_scores_sub.apply(lambda x: (x - x.min()) / (x.max() - x.min()), axis=0)
@@ -852,13 +853,13 @@ class LeaderboardServer:
         p1 = create_heatmap(
             normalized_scores_sub,
             original_scores_sub * 100,
-            x_axis_label="Models ≥16B",
+            x_axis_label=f"Models ≥{model_size_threshold}B",
             y_axis_label=fig_y_axis_label,
             transpose=transpose,
         )
         
         # Smaller models
-        original_scores_sub = original_scores[sizes_series < 16]
+        original_scores_sub = original_scores[sizes_series < model_size_threshold]
 
         # Apply quantile transformation independently for each row
         normalized_scores_sub = original_scores_sub.apply(lambda x: (x - x.min()) / (x.max() - x.min()), axis=0)
@@ -867,7 +868,7 @@ class LeaderboardServer:
         p2 = create_heatmap(
             normalized_scores_sub,
             original_scores_sub * 100,
-            x_axis_label="Models <16B",
+            x_axis_label=f"Models <{model_size_threshold}B",
             y_axis_label=fig_y_axis_label,
             y_axis_visible=False,
             transpose=transpose,