diff --git a/hi-ml-cpath/src/health_cpath/datamodules/base_module.py b/hi-ml-cpath/src/health_cpath/datamodules/base_module.py
index 3289b074..a002e637 100644
--- a/hi-ml-cpath/src/health_cpath/datamodules/base_module.py
+++ b/hi-ml-cpath/src/health_cpath/datamodules/base_module.py
@@ -25,7 +25,7 @@ from monai.data.dataset import CacheDataset, Dataset, PersistentDataset
 from monai.transforms import Compose
 
 
-_SlidesOrTilesDataset = TypeVar('_SlidesOrTilesDataset', SlidesDataset, TilesDataset)
+_SlidesOrTilesDataset = TypeVar("_SlidesOrTilesDataset", SlidesDataset, TilesDataset)
 
 
 class CacheMode(Enum):
@@ -57,6 +57,7 @@ class HistoDataModule(LightningDataModule, Generic[_SlidesOrTilesDataset]):
         pl_replace_sampler_ddp: bool = True,
         dataloader_kwargs: Optional[Dict[str, Any]] = None,
         dataframe_kwargs: Optional[Dict[str, Any]] = None,
+        class_weights: Optional[torch.Tensor] = None,
     ) -> None:
         """
         :param root_path: Root directory of the source dataset.
@@ -80,6 +81,7 @@ class HistoDataModule(LightningDataModule, Generic[_SlidesOrTilesDataset]):
         :param pl_replace_sampler_ddp: If True, replace the sampler with a DistributedSampler when using DDP.
         :param dataloader_kwargs: Additional keyword arguments for the training, validation, and test dataloaders.
         :param dataframe_kwargs: Keyword arguments to pass to `pd.read_csv()` when loading the dataset CSV.
+        :param class_weights: Class weights to use for the dataset. If None, will compute them from the dataset.
         """
 
         batch_size_inf = batch_size_inf or batch_size
@@ -97,7 +99,7 @@ class HistoDataModule(LightningDataModule, Generic[_SlidesOrTilesDataset]):
         self.test_dataset: _SlidesOrTilesDataset
         self.dataframe_kwargs = dataframe_kwargs or {}
         self.train_dataset, self.val_dataset, self.test_dataset = self.get_splits()
-        self.class_weights = self.train_dataset.get_class_weights()
+        self.class_weights = class_weights if class_weights is not None else self.train_dataset.get_class_weights()
         self.seed = seed
         self.dataloader_kwargs = dataloader_kwargs or {}
 
diff --git a/hi-ml-cpath/testhisto/testhisto/datamodules/test_histo_datamodule.py b/hi-ml-cpath/testhisto/testhisto/datamodules/test_histo_datamodule.py
index dd16b4fe..3f996267 100644
--- a/hi-ml-cpath/testhisto/testhisto/datamodules/test_histo_datamodule.py
+++ b/hi-ml-cpath/testhisto/testhisto/datamodules/test_histo_datamodule.py
@@ -182,3 +182,21 @@ def test_assertion_error_missing_seed(mock_panda_slides_root_dir: Path) -> None:
                     loading_params=get_loading_params(),
                 )
                 slides_datamodule._get_ddp_sampler(MagicMock(), ModelKey.TRAIN)
+
+
+def test_histo_module_class_weights(mock_panda_slides_root_dir: Path) -> None:
+    """Test if the class weights argument of the HistoDataModule is correctly set."""
+    datamodule = PandaSlidesDataModule(
+        root_path=mock_panda_slides_root_dir,
+        tiling_params=TilingParams(),
+        loading_params=get_loading_params(),
+    )
+    assert datamodule.class_weights.shape != (0,)
+    new_class_weights = torch.tensor([])
+    datamodule = PandaSlidesDataModule(
+        root_path=mock_panda_slides_root_dir,
+        tiling_params=TilingParams(),
+        loading_params=get_loading_params(),
+        class_weights=new_class_weights,
+    )
+    assert datamodule.class_weights.shape == new_class_weights.shape