Add early authentication check with whoami validation

- Validate token at script start using HfApi.whoami()
- Fail fast with clear error if authentication fails
- Show authenticated username for confirmation

classify-dataset.py

@@ -218,6 +218,30 @@ def prepare_prompts(
 def main():
     args = parse_args()
     
+    # Check authentication early
+    logger.info("Checking authentication...")
+    token = args.hf_token
+    if not token:
+        # Try to get token from environment or huggingface-cli login
+        token = os.environ.get("HF_TOKEN") or get_token()
+    
+    if not token:
+        logger.error("No authentication token found. Please either:")
+        logger.error("1. Run 'huggingface-cli login'")
+        logger.error("2. Set HF_TOKEN environment variable")
+        logger.error("3. Pass --hf-token argument")
+        sys.exit(1)
+    
+    # Validate token by checking who we are
+    try:
+        api = HfApi(token=token)
+        user_info = api.whoami()
+        logger.info(f"Authenticated as: {user_info['name']}")
+    except Exception as e:
+        logger.error(f"Authentication failed: {e}")
+        logger.error("Please check your token is valid")
+        sys.exit(1)
+    
     # Check CUDA availability
     if not torch.cuda.is_available():
         logger.error("CUDA is not available. This script requires a GPU.")
@@ -341,20 +365,7 @@ def main():
     success_rate = (valid_texts / total_texts * 100) if total_texts > 0 else 0
     logger.info(f"Classification success rate: {success_rate:.1f}%")
     
-    # Get token for authentication
-    token = args.hf_token
-    if not token:
-        # Try to get token from environment or huggingface-cli login
-        token = os.environ.get("HF_TOKEN") or get_token()
-    
-    if not token:
-        logger.error("No authentication token found. Please either:")
-        logger.error("1. Run 'huggingface-cli login'")
-        logger.error("2. Set HF_TOKEN environment variable")
-        logger.error("3. Pass --hf-token argument")
-        sys.exit(1)
-    
-    # Save to Hub
+    # Save to Hub (token already validated at start)
     logger.info(f"Pushing dataset to Hub: {args.output_dataset}")
     try:
         dataset.push_to_hub(