Updating repo for leads

app.py

@@ -291,7 +291,7 @@ def display_leaderboard():
 #     if st.button("Show Leaderboard"):
 #         try:
 #             # Load the 'leaders' configuration or split from your dataset
-#             dataset = load_dataset("Jay-Rajput/DIS_IPL_Dataset", "leaders", split='train')
+#             dataset = load_dataset("Jay-Rajput/DIS_IPL_Leads", split='train')
 #             # Convert the dataset to a pandas DataFrame
 #             df_users = pd.DataFrame(dataset)
             
@@ -383,7 +383,7 @@ ADMIN_PASSPHRASE = "admin123"
 
 def fetch_latest_predictions(match_id):
     # Load the dataset. Adjust "split" to "train" or appropriate if "predictions" is a configuration.
-    dataset = load_dataset("Jay-Rajput/DIS_IPL_Preds")
+    dataset = load_dataset("Jay-Rajput/DIS_IPL_Preds", split="train")
 
     # Convert the dataset to a pandas DataFrame
     df = pd.DataFrame(dataset)
@@ -412,7 +412,7 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
 
     outcomes = load_data(OUTCOMES_JSON)  # Load existing match outcomes
     # Load existing match outcomes and user data from the test split
-    dataset = load_dataset("Jay-Rajput/DIS_IPL_Leads")
+    dataset = load_dataset("Jay-Rajput/DIS_IPL_Leads", split="train")
     users = pd.DataFrame(dataset)
 
     # Directly update or add the match outcome
@@ -435,7 +435,7 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
         # Update points based on prediction accuracy
         if predicted_winner == winning_team:
             users[user_name] += 1000
-            users[user_name] += bid_points 
+            users[user_name] += bid_points
             if predicted_motm == man_of_the_match:
                 users[user_name] += 400  # Bonus for both correct predictions
         else:
@@ -445,7 +445,7 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
     users.to_json(USERS_JSON)
     # Convert the updated DataFrame back to a Hugging Face Dataset and push updates
     updated_dataset = Dataset.from_pandas(users)
-    updated_dataset.push_to_hub("Jay-Rajput/DIS_IPL_Leads")
+    updated_dataset.push_to_hub("Jay-Rajput/DIS_IPL_Leads", split="train")
 
 
 with st.sidebar: