diff --git a/optimum/intel/openvino/modeling_base.py b/optimum/intel/openvino/modeling_base.py
index 14ac76137f..59fc89649a 100644
--- a/optimum/intel/openvino/modeling_base.py
+++ b/optimum/intel/openvino/modeling_base.py
@@ -65,7 +65,6 @@ class PreTrainedModel(OptimizedModel):
     """,
 )
 class OVBaseModel(PreTrainedModel):
-    _AUTOMODELS_TO_TASKS = {cls_name: task for task, cls_name in TasksManager._TASKS_TO_AUTOMODELS.items()}
     auto_model_class = None
     export_feature = None
 
@@ -391,13 +390,6 @@ def _ensure_supported_device(self, device: str = None):
     def forward(self, *args, **kwargs):
         raise NotImplementedError
 
-    @classmethod
-    def _auto_model_to_task(cls, auto_model_class):
-        """
-        Get the task corresponding to a class (for example AutoModelForXXX in transformers).
-        """
-        return cls._AUTOMODELS_TO_TASKS[auto_model_class.__name__]
-
     def can_generate(self) -> bool:
         """
         Returns whether this model can generate sequences with `.generate()`.
diff --git a/tests/openvino/test_stable_diffusion.py b/tests/openvino/test_stable_diffusion.py
index 3c0c90475a..e04e2d6fd3 100644
--- a/tests/openvino/test_stable_diffusion.py
+++ b/tests/openvino/test_stable_diffusion.py
@@ -121,7 +121,6 @@ def callback_fn(step: int, timestep: int, latents: np.ndarray) -> None:
         self.assertEqual(callback_fn.number_of_steps, inputs["num_inference_steps"])
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES)
-    @require_diffusers
     def test_shape(self, model_arch: str):
         height, width, batch_size = 128, 64, 1
         pipeline = self.MODEL_CLASS.from_pretrained(MODEL_NAMES[model_arch], export=True)