diff --git a/torch_sim/models/sevennet.py b/torch_sim/models/sevennet.py
index d21449d4..82353ec4 100644
--- a/torch_sim/models/sevennet.py
+++ b/torch_sim/models/sevennet.py
@@ -77,12 +77,13 @@ def __init__(
             neighbor_list_fn (Callable): Neighbor list function to use.
                 Default is vesin_nl_ts.
             device (torch.device | str | None): Device to run the model on
-            dtype (torch.dtype | None): Data type for computation
+            dtype (torch.dtype): Data type for computation
 
         Raises:
             ValueError: the model doesn't have a cutoff
             ValueError: the model has a modal_map but modal is not given
             ValueError: the modal given is not in the modal_map
+            ValueError: the model doesn't have a type_map
         """
         super().__init__()
 
@@ -92,7 +93,7 @@ def __init__(
         if isinstance(self._device, str):
             self._device = torch.device(self._device)
 
-        if torch.dtype is not torch.float32:
+        if dtype is not torch.float32:
             warnings.warn(
                 "SevenNetModel currently only supports"
                 "float32, but received different dtype",
@@ -100,6 +101,10 @@ def __init__(
                 stacklevel=2,
             )
 
+        if not model.type_map:
+            raise ValueError("type_map is missing")
+        model.eval_type_map = torch.tensor(data=True)
+
         self._dtype = dtype
         self._memory_scales_with = "n_atoms_x_density"
         self._compute_stress = True
@@ -108,9 +113,6 @@ def __init__(
         if model.cutoff == 0.0:
             raise ValueError("Model cutoff seems not initialized")
 
-        model.eval_type_map = torch.tensor(
-            data=True,
-        )  # TODO: from sevenn not sure if needed
         model.set_is_batch_data(True)
         model_loaded = model
         self.cutoff = torch.tensor(model.cutoff)