diff --git a/src/lmflow/args.py b/src/lmflow/args.py
index 480c6a8d..518957db 100644
--- a/src/lmflow/args.py
+++ b/src/lmflow/args.py
@@ -631,9 +631,6 @@ def __post_init__(self):
             if self.validation_file is not None:
                 extension = self.validation_file.split(".")[-1]
                 assert extension in ["csv", "json", "txt"], "`validation_file` should be a csv, a json or a txt file."
-                
-        if self.skip_dataset_check:
-            logger.warning("Skip dataset check is enabled. Make sure the datasets are in the correct format.")
 
 
 @dataclass
diff --git a/src/lmflow/models/hf_decoder_model.py b/src/lmflow/models/hf_decoder_model.py
index dd4fc9f9..0fd6da2f 100644
--- a/src/lmflow/models/hf_decoder_model.py
+++ b/src/lmflow/models/hf_decoder_model.py
@@ -234,7 +234,6 @@ def tokenize(
                 "load_from_cache_file": not data_args.overwrite_cache,
                 "desc": "Running tokenizer on dataset",
                 "new_fingerprint": fingerprint,
-                "max_length": data_args.block_size,
             }
 
         if data_args.block_size < self.tokenizer.model_max_length:
diff --git a/src/lmflow/pipeline/finetuner.py b/src/lmflow/pipeline/finetuner.py
index 34eb948c..ee9b67c7 100644
--- a/src/lmflow/pipeline/finetuner.py
+++ b/src/lmflow/pipeline/finetuner.py
@@ -33,7 +33,7 @@
 import numpy as np
 
 import lmflow.optim.optimizers as optim
-from lmflow.args import OptimizerNames
+from lmflow.args import OptimizerNames, DatasetArguments, ModelArguments, FinetunerArguments
 from lmflow.datasets.dataset import Dataset
 from lmflow.pipeline.base_tuner import BaseTuner
 from lmflow.pipeline.utils.peft_trainer import PeftTrainer, PeftSavingCallback
@@ -64,7 +64,14 @@ class Finetuner(BaseTuner):
         Keyword arguments.
 
     """
-    def __init__(self, model_args, data_args, finetuner_args, *args, **kwargs):
+    def __init__(
+        self, 
+        model_args: ModelArguments, 
+        data_args: DatasetArguments, 
+        finetuner_args: FinetunerArguments, 
+        *args, 
+        **kwargs
+    ):
 
         self.model_args = model_args
         self.data_args = data_args