diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 3c211cfe..327f447e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -21,10 +21,10 @@ repos:
 
   # Check for spelling
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.2.6
+    rev: v2.3.0
     hooks:
       - id: codespell
-        args: ["-L", "fpr, tre, sav, provid"]
+        args: ["-L", "fpr, tre, sav, provid, assertIn"]
         exclude: >
             (?x)^(
                 .*\.svg|
@@ -53,7 +53,7 @@ repos:
 
   # Black format Python and notebooks
   - repo: https://github.com/psf/black
-    rev: 24.4.0
+    rev: 24.4.2
     hooks:
       - id: black-jupyter
 
diff --git a/aisdc/attacks/likelihood_attack.py b/aisdc/attacks/likelihood_attack.py
index d0bdae17..29af0853 100644
--- a/aisdc/attacks/likelihood_attack.py
+++ b/aisdc/attacks/likelihood_attack.py
@@ -564,13 +564,15 @@ def attack_from_config(self) -> None:  # pylint: disable = too-many-locals
         logger.info("Loading test predictions form %s", self.test_preds_filename)
         test_preds = np.loadtxt(self.test_preds_filename, delimiter=",")
         assert len(test_preds) == len(test_X)
-        if self.target_model is not None:
-            clf_module_name, clf_class_name = self.target_model
-            module = importlib.import_module(clf_module_name)
-            clf_class = getattr(module, clf_class_name)
-            if self.target_model_hyp is not None:
-                clf_params = self.target_model_hyp
-                clf = clf_class(**clf_params)
+        if self.target_model is None:
+            raise ValueError("Target model cannot be None")
+        if self.target_model_hyp is None:
+            raise ValueError("Target model hyperparameters cannot be None")
+        clf_module_name, clf_class_name = self.target_model
+        module = importlib.import_module(clf_module_name)
+        clf_class = getattr(module, clf_class_name)
+        clf_params = self.target_model_hyp
+        clf = clf_class(**clf_params)
         logger.info("Created model: %s", str(clf))
         self.run_scenario_from_preds(
             clf, train_X, train_y, train_preds, test_X, test_y, test_preds