diff --git a/src/otx/core/model/base.py b/src/otx/core/model/base.py
index f23b1ad268a..84f8cd15de8 100644
--- a/src/otx/core/model/base.py
+++ b/src/otx/core/model/base.py
@@ -19,6 +19,7 @@
 from jsonargparse import ArgumentParser
 from lightning import LightningModule
 from openvino.model_api.models import Model
+from openvino.model_api.tilers import Tiler
 from torch import Tensor, nn
 from torch.optim.lr_scheduler import ConstantLR
 from torch.optim.sgd import SGD
@@ -816,9 +817,11 @@ def transform_fn(self, data_batch: T_OTXBatchDataEntity) -> np.array:
         """Data transform function for PTQ."""
         np_data = self._customize_inputs(data_batch)
         image = np_data["inputs"][0]
-        resized_image = self.model.resize(image, (self.model.w, self.model.h))
-        resized_image = self.model.input_transform(resized_image)
-        return self.model._change_layout(resized_image)  # noqa: SLF001
+        # NOTE: Tiler wraps the model, so we need to unwrap it to get the model
+        model = self.model.model if isinstance(self.model, Tiler) else self.model
+        resized_image = model.resize(image, (model.w, model.h))
+        resized_image = model.input_transform(resized_image)
+        return model._change_layout(resized_image)  # noqa: SLF001
 
     def _read_ptq_config_from_ir(self, ov_model: Model) -> dict[str, Any]:
         """Generates the PTQ (Post-Training Quantization) configuration from the meta data of the given OpenVINO model.