diff --git a/Deep-SAD-PyTorch/src/baselines/ocsvm.py b/Deep-SAD-PyTorch/src/baselines/ocsvm.py
index 29dfafe..fe6ca55 100644
--- a/Deep-SAD-PyTorch/src/baselines/ocsvm.py
+++ b/Deep-SAD-PyTorch/src/baselines/ocsvm.py
@@ -11,7 +11,7 @@ from sklearn.metrics import (
     roc_auc_score,
     roc_curve,
 )
-from thundersvm import OneClassSVM
+from sklearn.svm import OneClassSVM
 
 from base.base_dataset import BaseADDataset
 from networks.main import build_autoencoder
@@ -27,7 +27,7 @@ class OCSVM(object):
         self.rho = None
         self.gamma = None
 
-        self.model = OneClassSVM(kernel=kernel, nu=nu, verbose=True, max_mem_size=4048)
+        self.model = OneClassSVM(kernel=kernel, nu=nu)
 
         self.hybrid = hybrid
         self.latent_space_dim = latent_space_dim
@@ -166,8 +166,6 @@ class OCSVM(object):
                 kernel=self.kernel,
                 nu=self.nu,
                 gamma=gamma,
-                verbose=True,
-                max_mem_size=4048,
             )
 
             # Train
@@ -198,7 +196,7 @@ class OCSVM(object):
         # If hybrid, also train a model with linear kernel
         if self.hybrid:
             self.linear_model = OneClassSVM(
-                kernel="linear", nu=self.nu, max_mem_size=4048
+                kernel="linear", nu=self.nu
             )
             start_time = time.time()
             self.linear_model.fit(X)
@@ -479,14 +477,15 @@ class OCSVM(object):
             self.ae_net.to(torch.device(device))
         self.ae_net.eval()
 
-    def save_model(self, export_path: Path):
+    def save_model(self, export_path):
         """Save OC-SVM model to export_path."""
-        self.model.save_to_file(export_path)
+        with open(export_path, "wb") as fp:
+            pickle.dump(self.model, fp)
 
-    def load_model(self, import_path: Path):
+    def load_model(self, import_path):
         """Load OC-SVM model from import_path."""
-        self.model.save_to_file(import_path)
-        pass
+        with open(import_path, "rb") as fp:
+            self.model = pickle.load(fp)
 
     def save_results(self, export_pkl):
         with open(export_pkl, "wb") as fp:
diff --git a/Deep-SAD-PyTorch/src/main.py b/Deep-SAD-PyTorch/src/main.py
index 72e5046..2f48168 100644
--- a/Deep-SAD-PyTorch/src/main.py
+++ b/Deep-SAD-PyTorch/src/main.py
@@ -597,7 +597,7 @@ def main(
                     deepSAD.save_model(export_model=xp_path + "/model_deepsad.tar")
                 if train_ocsvm:
                     ocsvm.save_results(export_pkl=xp_path + "/results_ocsvm.pkl")
-                    ocsvm.save_model(export_path=xp_path + "/model_ocsvm.bin")
+                    ocsvm.save_model(export_path=xp_path + "/model_ocsvm.pkl")
                 if train_isoforest:
                     Isoforest.save_results(
                         export_pkl=xp_path + "/results_isoforest.pkl"
@@ -616,7 +616,7 @@ def main(
                         export_pkl=xp_path + f"/results_ocsvm_{fold_idx}.pkl"
                     )
                     ocsvm.save_model(
-                        export_path=xp_path + f"/model_ocsvm_{fold_idx}.bin"
+                        export_path=xp_path + f"/model_ocsvm_{fold_idx}.pkl"
                     )
                 if train_isoforest:
                     Isoforest.save_results(