diff --git a/optimum/exporters/onnx/model_configs.py b/optimum/exporters/onnx/model_configs.py
index e77f649f69..9e97908464 100644
--- a/optimum/exporters/onnx/model_configs.py
+++ b/optimum/exporters/onnx/model_configs.py
@@ -72,7 +72,6 @@
 )
 from .constants import ONNX_DECODER_MERGED_NAME, ONNX_DECODER_NAME, ONNX_DECODER_WITH_PAST_NAME
 from .model_patcher import (
-    CLIPModelPatcher,
     FalconModelPatcher,
     MistralModelPatcher,
     MusicgenModelPatcher,
@@ -907,6 +906,7 @@ class CLIPNormalizedConfig(NormalizedTextAndVisionConfig):
 
 class CLIPVisionModelOnnxConfig(VisionOnnxConfig):
     NORMALIZED_CONFIG_CLASS = NormalizedVisionConfig
+    DEFAULT_ONNX_OPSET = 14  # now uses F.scaled_dot_product_attention by default for torch>=2.1.1.
 
     @property
     def inputs(self) -> Dict[str, Dict[int, str]]:
@@ -920,16 +920,10 @@ def outputs(self) -> Dict[str, Dict[int, str]]:
 
         return common_outputs
 
-    def patch_model_for_export(
-        self,
-        model: Union["PreTrainedModel", "TFPreTrainedModel", "ModelMixin"],
-        model_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> "ModelPatcher":
-        return CLIPModelPatcher(self, model, model_kwargs=model_kwargs)
-
 
 class CLIPOnnxConfig(TextAndVisionOnnxConfig):
     NORMALIZED_CONFIG_CLASS = CLIPNormalizedConfig
+    DEFAULT_ONNX_OPSET = 14  # now uses F.scaled_dot_product_attention by default for torch>=2.1.1.
 
     @property
     def inputs(self) -> Dict[str, Dict[int, str]]:
@@ -948,13 +942,6 @@ def outputs(self) -> Dict[str, Dict[int, str]]:
             "image_embeds": {0: "image_batch_size"},
         }
 
-    def patch_model_for_export(
-        self,
-        model: Union["PreTrainedModel", "TFPreTrainedModel", "ModelMixin"],
-        model_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> "ModelPatcher":
-        return CLIPModelPatcher(self, model, model_kwargs=model_kwargs)
-
 
 class SentenceTransformersCLIPOnnxConfig(CLIPOnnxConfig):
     @property
@@ -1000,13 +987,6 @@ def outputs(self) -> Dict[str, Dict[int, str]]:
 
         return common_outputs
 
-    def patch_model_for_export(
-        self,
-        model: Union["PreTrainedModel", "TFPreTrainedModel", "ModelMixin"],
-        model_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> "ModelPatcher":
-        return CLIPModelPatcher(self, model, model_kwargs=model_kwargs)
-
 
 class CLIPTextOnnxConfig(CLIPTextWithProjectionOnnxConfig):
     @property
@@ -1031,13 +1011,6 @@ def generate_dummy_inputs(self, framework: str = "pt", **kwargs):
             dummy_inputs["input_ids"] = dummy_inputs["input_ids"].to(dtype=torch.int32)
         return dummy_inputs
 
-    def patch_model_for_export(
-        self,
-        model: Union["PreTrainedModel", "TFPreTrainedModel", "ModelMixin"],
-        model_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> "ModelPatcher":
-        return CLIPModelPatcher(self, model, model_kwargs=model_kwargs)
-
 
 class UNetOnnxConfig(VisionOnnxConfig):
     ATOL_FOR_VALIDATION = 1e-3
diff --git a/optimum/exporters/onnx/model_patcher.py b/optimum/exporters/onnx/model_patcher.py
index 34ed5fcae4..4c1f845893 100644
--- a/optimum/exporters/onnx/model_patcher.py
+++ b/optimum/exporters/onnx/model_patcher.py
@@ -1138,20 +1138,3 @@ def __init__(
                 self._update_causal_mask_original = self._model.model._update_causal_mask
             else:
                 self._update_causal_mask_original = self._model._update_causal_mask
-
-
-class CLIPModelPatcher(ModelPatcher):
-    def __enter__(self):
-        super().__enter__()
-
-        if _transformers_version >= version.parse("4.43"):
-            from transformers.models.clip.modeling_clip import CLIPAttention, CLIPSdpaAttention
-
-            self.original_sdpa_forward, CLIPSdpaAttention.forward = CLIPSdpaAttention.forward, CLIPAttention.forward
-
-    def __exit__(self, exc_type, exc_value, traceback):
-        super().__exit__(exc_type, exc_value, traceback)
-        if _transformers_version >= version.parse("4.43"):
-            from transformers.models.clip.modeling_clip import CLIPSdpaAttention
-
-            CLIPSdpaAttention.forward = self.original_sdpa_forward