diff --git a/fmcib/run.py b/fmcib/run.py
index 3da4711..558462e 100644
--- a/fmcib/run.py
+++ b/fmcib/run.py
@@ -9,12 +9,7 @@
 from .preprocessing import get_dataloader
 
 
-def get_features(
-    csv_path,
-    weights_path=None,
-    spatial_size=(50, 50, 50),
-    precropped=False,
-):
+def get_features(csv_path, weights_path=None, spatial_size=(50, 50, 50), precropped=False, **kwargs):
     """
     Extracts features from images specified in a CSV file.
 
@@ -23,13 +18,13 @@ def get_features(
         weights_path (str, optional): Path to the pre-trained weights file. Default is None.
         spatial_size (tuple, optional): Spatial size of the input images. Default is (50, 50, 50).
         precropped (bool, optional): Whether the images are already pre-cropped. Default is False.
-
+        **kwargs: Additional arguments to be passed to the dataloader.
     Returns:
         pandas.DataFrame: DataFrame containing the original data from the CSV file along with the extracted features.
     """
     logger.info("Loading CSV file ...")
     df = pd.read_csv(csv_path)
-    dataloader = get_dataloader(csv_path, spatial_size=spatial_size, precropped=precropped)
+    dataloader = get_dataloader(csv_path, spatial_size=spatial_size, precropped=precropped, **kwargs)
     device = "cuda" if torch.cuda.is_available() else "cpu"
 
     if weights_path is None: