period dependent scaling law

app.py

@@ -307,12 +307,16 @@ def create_scaling_plot(all_data, period):
     fig.update_traces(
         hovertemplate="<b>%{hovertext}</b><br>Params(B): %{customdata[0]:.2f} B<br>Compression Rate (%): %{customdata[1]:.2f}<extra></extra>"
     )
-
-    names_to_connect = ['Meta-Llama-3.1-8B',
-                        'stablelm-3b-4e1t',
-                        'Qwen2-1.5B',
-                        'TinyLlama-1.1B-intermediate-step-1431k-3T',
-                        'Mistral-Nemo-Base-2407']
+    
+    names_to_connect_dict = {
+        '2024-05': ['Meta-Llama-3-8B', 'stablelm-3b-4e1t', 'Qwen2-1.5B', 'TinyLlama-1.1B-intermediate-step-1431k-3T', 'Mistral-Nemo-Base-2407'],
+        '2024-06': ['Meta-Llama-3-8B', 'stablelm-3b-4e1t', 'Qwen2-1.5B', 'TinyLlama-1.1B-intermediate-step-1431k-3T', 'Mistral-Nemo-Base-2407'],
+        '2024-07': ['Meta-Llama-3.1-8B', 'stablelm-3b-4e1t', 'Qwen2-1.5B', 'TinyLlama-1.1B-intermediate-step-1431k-3T', 'Mistral-Nemo-Base-2407'],
+        '2024-08': ['Meta-Llama-3.1-8B', 'Rene-v0.1-1.3b-pytorch', 'stablelm-3b-4e1t', 'Qwen2-1.5B', 'TinyLlama-1.1B-intermediate-step-1431k-3T', 'Mistral-Nemo-Base-2407'],
+    }
+
+    names_to_connect = names_to_connect_dict.get(period, names_to_connect_dict['2024-08'])
+    
     connection_points = new_df[new_df['Name'].isin(names_to_connect)]
 
     new_df['Color'] = new_df['Name'].apply(lambda name: '#39C5BB' if name in names_to_connect else '#636efa')