Update main.py

main.py

@@ -15,6 +15,7 @@ import torch
 import random
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 from collections import defaultdict
+import Path
 
 # Global model and tokenizer
 model = None
@@ -200,17 +201,10 @@ def load_dataset():
     """Load dataset and group examples by label"""
     global dataset_by_label, dataset_path
 
-    possible_paths = [
-        "xlam_function_calling_60k_processed_with_ground_truth.json",
-        os.getenv("DATASET_PATH", "")
-    ]
+        
 
     
-    dataset_path = None
-    for path in possible_paths:
-        if path and os.path.exists(path):
-            dataset_path = path
-            break
+    dataset_path = Path("xlam_function_calling_60k_processed_with_ground_truth.json")
     
     if not dataset_path:
         print("Warning: Dataset file not found. Using hardcoded examples.")