Create svm.py

svm.py

@@ -0,0 +1,9 @@
+```python
+from sklearn.svm import SVC
+svm_model = SVC(kernel='linear', random_state=42)
+svm_model.fit(X_train_tfidf, y_train)
+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))
+```