Update svm.py

svm.py

@@ -1,4 +1,4 @@
-```python
+
 from sklearn.svm import SVC
 svm_model = SVC(kernel='linear', random_state=42)
 svm_model.fit(X_train_tfidf, y_train)
@@ -6,4 +6,3 @@ y_pred = svm_model.predict(X_test_tfidf)
 accuracy = accuracy_score(y_test, y_pred)
 print(f"Random Forest Accuracy: {accuracy:.4f}")
 print(classification_report(y_test, y_pred))
-```