Update train.py

train.py

@@ -76,11 +76,11 @@ y_test_pred = model_pipeline.predict(X_test)
 
 print("Serializing Model")
 
-# Save the model in the dataset directory
+# Save the model directly to the dataset directory
 saved_model_path = os.path.join(dataset_dir, "model.joblib")
 joblib.dump(model_pipeline, saved_model_path)
 
-print(f"Model Serialized and Saved to {saved_model_path}")
+print(f"Model Serialized and Saved directly to {saved_model_path}")
 
 # Get the Hugging Face API token securely from the secret environment variable
 api_token = os.getenv('FraudDemoWrite')  # Access the secret directly using its name
@@ -98,9 +98,7 @@ repo_url = api.create_repo(repo_id=repo_name, token=api_token, exist_ok=True)
 # Initialize the repository
 repo = Repository(local_dir="hf_model_repo", clone_from=repo_url, use_auth_token=api_token)
 
-# Move the model to the repository folder
-os.rename(saved_model_path, os.path.join("hf_model_repo", "model.joblib"))
+# Directly push the model file to the Hugging Face Hub from the dataset directory
+repo.push_to_hub(commit_message="Upload trained model", repo_id=repo_name)
 
-# Push the model to the Hugging Face Hub
-repo.push_to_hub(commit_message="Upload trained model")