diff --git a/pts/model/n_beats/n_beats_estimator.py b/pts/model/n_beats/n_beats_estimator.py
index 42b1af8..6c067fc 100644
--- a/pts/model/n_beats/n_beats_estimator.py
+++ b/pts/model/n_beats/n_beats_estimator.py
@@ -121,12 +121,9 @@ class NBEATSEstimator(PTSEstimator):
         else:
             return new_value
 
-    # here we do only a simple operation to convert the input data to a form
+    # Here we do only a simple operation to convert the input data to a form
     # that can be digested by our model by only splitting the target in two, a
     # conditioning part and a to-predict part, for each training example.
-    # for a more complex transformation example, see the `gluonts.model.deepar`
-    # transformation that includes time features, age feature, observed values
-    # indicator, ...
     def create_transformation(self) -> Transformation:
         return Chain(
             [
diff --git a/pts/model/n_beats/n_beats_network.py b/pts/model/n_beats/n_beats_network.py
index 6676ea9..78b7cab 100644
--- a/pts/model/n_beats/n_beats_network.py
+++ b/pts/model/n_beats/n_beats_network.py
@@ -210,7 +210,7 @@ class NBEATSNetwork(nn.Module):
         self.prediction_length = prediction_length
         self.context_length = context_length
 
-        self.net_blocks: nn.ModuleList[NBEATSBlock] = nn.ModuleList()
+        self.net_blocks = nn.ModuleList()
         for stack_id in range(num_stacks):
             for block_id in range(num_blocks[stack_id]):
                 if self.stack_types[stack_id] == "G":