Update hrefs to models

src/process_leaderboard_data.py

@@ -3,7 +3,7 @@ import gradio as gr
 
 
 class Leaderboard():
-    def __init__(self, data_path='models_performance.csv'):
+    def __init__(self, data_path='results.csv'):
         self.data_path = data_path
         self.models_performance_dataframe = self.initialize_models_performance_dataframe()
         self.link_dict = self.initialize_link_dict()
@@ -11,7 +11,6 @@ class Leaderboard():
         self.emotional_dataset_list = sorted(self.initialize_emotional_datasets())
         self.emotion_list = sorted(list(set(self.models_performance_dataframe['emotion'])))
 
-
     def get_dataset_list(self) -> list:
         return self.dataset_list
     
@@ -42,11 +41,11 @@ class Leaderboard():
     # Dictionary mapping model names to their GitHub repository links
     def initialize_link_dict(self) -> dict:
         return {
-            'WhisperSpeech': 'https://github.com/collabora/WhisperSpeech',
-            'SpeechT5': 'https://github.com/microsoft/SpeechT5',
-            'VALL-E-X': 'https://github.com/Plachtaa/VALL-E-X',
-            'XTTS-v2': 'https://huggingface.co/coqui/XTTS-v2',
-            'OuteTTS': 'https://huggingface.co/OuteAI/OuteTTS-0.2-500M'
+            'WhisperSpeech/WhisperSpeech': 'https://huggingface.co/WhisperSpeech/WhisperSpeech',
+            'microsoft/speecht5_vc': 'https://huggingface.co/microsoft/speecht5_vc',
+            'Plachtaa/VALL-E-X': 'https://github.com/Plachtaa/VALL-E-X',
+            'coqui/XTTS-v2': 'https://huggingface.co/coqui/XTTS-v2',
+            'OuteAI/OuteTTS-0.2-500M': 'https://huggingface.co/OuteAI/OuteTTS-0.2-500M'
         }
         
 
@@ -102,7 +101,7 @@ class Leaderboard():
         # Map model names to hyperlinks using the link_dict.
         leaderboard_dataframe['Model'] = leaderboard_dataframe['Model'].map(lambda model: f"[{model}]({self.link_dict.get(model, '')})")
         leaderboard_dataframe.sort_values(by='Average', ascending=False, inplace=True)
-
+        leaderboard_dataframe.insert(0, "Rank", range(1, len(leaderboard_dataframe) + 1))
         return leaderboard_dataframe