Update app.py

app.py

@@ -31,12 +31,13 @@ def formatter(x):
     else:
         return round(x, 2)
 
+# Apply formatting to other columns
 for col in original_df.columns:
-    if col == "model":
-        original_df[col] = original_df[col].apply(lambda x: x.replace(x, make_clickable_model(x)))
+    if col in ['model', 'Model']:
+        continue  # Skip the 'model' and 'Model' columns
     else:
         original_df[col] = original_df[col].apply(formatter)
-
+        
 original_df.rename(columns=column_names, inplace=True)
 original_df.sort_values(by='WER ⬇️', inplace=True)
 
@@ -51,8 +52,8 @@ def request_model(model_text):
     if not base_model_on_hub:
         return styled_error(f"Base model '{model_text}' {error_msg}")
 
-    # Check if the model has already been evaluated
-    if model_text in original_df['Model'].apply(lambda x: x.split('href="')[1].split('"')[0].replace('https://huggingface.co/', '')).values:
+    # Check if the model has already been evaluated using the raw 'model' column
+    if model_text in original_df['model'].values:
         return styled_error(f"The model '{model_text}' is already in the leaderboard.")
 
     try:
@@ -74,7 +75,7 @@ def request_model(model_text):
         pipe = pipeline(
             "automatic-speech-recognition",
             model=model_text,
-            torch_dtype=torch.float32,
+            torch_dtype=torch.float16,
             device=0 if torch.cuda.is_available() else -1,  # Use GPU if available
         )
 
@@ -111,12 +112,14 @@ def request_model(model_text):
         df_results.to_csv(csv_results, index=False)
 
         # Update the leaderboard DataFrame
-
         original_df = df_results.copy()
-        original_df['Model'] = original_df['model'].apply(lambda x: make_clickable_model(x))
-        original_df['WER ⬇️'] = original_df['wer'].apply(lambda x: round(x, 2))
-        original_df['CER ⬇️'] = original_df['cer'].apply(lambda x: round(x, 2))
-        original_df = original_df[['Model', 'WER ⬇️', 'CER ⬇️']]
+        original_df['Model'] = original_df['model'].apply(make_clickable_model)
+        for col in original_df.columns:
+            if col in ['model', 'Model']:
+                continue  # Skip the 'model' and 'Model' columns
+            else:
+                original_df[col] = original_df[col].apply(formatter)
+        original_df.rename(columns=column_names, inplace=True)
         original_df.sort_values(by='WER ⬇️', inplace=True)
 
         # Update the leaderboard table in the UI