Update README.md

README.md

@@ -5,6 +5,8 @@ sdk: static
 ## Evaluation Pipeline
 # Use eval_pipeline.py or the raw version of the code below to evaluate the model. Make sure to set the dataset and model path.
 
+```
+
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import accuracy_score, classification_report
@@ -160,3 +162,5 @@ y_true, y_pred = custom_model.evaluate(test_loader)
 
 print(f"Accuracy: {accuracy_score(y_true, y_pred):.4f}")
 print("Classification Report:\n", classification_report(y_true, y_pred))
+
+```