diff --git a/llama_stack/providers/inline/post_training/common/validator.py b/llama_stack/providers/inline/post_training/common/validator.py
index b0aec6187..950b75f86 100644
--- a/llama_stack/providers/inline/post_training/common/validator.py
+++ b/llama_stack/providers/inline/post_training/common/validator.py
@@ -17,10 +17,8 @@ from llama_stack.apis.common.type_system import (
     DialogType,
     StringType,
 )
-from llama_stack.apis.datasets import Datasets
 from llama_stack.providers.utils.common.data_schema_validator import (
     ColumnName,
-    validate_dataset_schema,
 )
 
 EXPECTED_DATASET_SCHEMA: dict[str, list[dict[str, Any]]] = {
@@ -36,21 +34,3 @@ EXPECTED_DATASET_SCHEMA: dict[str, list[dict[str, Any]]] = {
         }
     ],
 }
-
-
-async def validate_input_dataset_schema(
-    datasets_api: Datasets,
-    dataset_id: str,
-    dataset_type: str,
-) -> None:
-    dataset_def = await datasets_api.get_dataset(dataset_id=dataset_id)
-    if not dataset_def:
-        raise ValueError(f"Dataset {dataset_id} does not exist.")
-
-    if not dataset_def.dataset_schema or len(dataset_def.dataset_schema) == 0:
-        raise ValueError(f"Dataset {dataset_id} does not have a schema defined.")
-
-    if dataset_type not in EXPECTED_DATASET_SCHEMA:
-        raise ValueError(f"Dataset type {dataset_type} is not supported.")
-
-    validate_dataset_schema(dataset_def.dataset_schema, EXPECTED_DATASET_SCHEMA[dataset_type])
diff --git a/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py b/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
index 04bf86b97..5cf15824d 100644
--- a/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
+++ b/llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
@@ -48,9 +48,6 @@ from llama_stack.apis.post_training import (
 from llama_stack.distribution.utils.config_dirs import DEFAULT_CHECKPOINT_DIR
 from llama_stack.distribution.utils.model_utils import model_local_dir
 from llama_stack.models.llama.sku_list import resolve_model
-from llama_stack.providers.inline.post_training.common.validator import (
-    validate_input_dataset_schema,
-)
 from llama_stack.providers.inline.post_training.torchtune.common import utils
 from llama_stack.providers.inline.post_training.torchtune.common.checkpointer import (
     TorchtuneCheckpointer,
@@ -348,11 +345,9 @@ class LoraFinetuningSingleDevice:
         all_rows = await fetch_rows(dataset_id)
         rows = all_rows.data
 
-        await validate_input_dataset_schema(
-            datasets_api=self.datasets_api,
-            dataset_id=dataset_id,
-            dataset_type=self._data_format.value,
-        )
+        # TODO (xiyan): validate dataset schema
+        # dataset_def = await self.datasets_api.get_dataset(dataset_id=dataset_id)
+
         data_transform = await utils.get_data_transform(self._data_format)
         ds = SFTDataset(
             rows,