diff --git a/doctr/models/modules/transformer/pytorch.py b/doctr/models/modules/transformer/pytorch.py
index 63ad346c2f..190a12da63 100644
--- a/doctr/models/modules/transformer/pytorch.py
+++ b/doctr/models/modules/transformer/pytorch.py
@@ -37,7 +37,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         Returns:
             positional embeddings (batch, max_len, d_model)
         """
-        x = x + self.pe[:, : x.size(1)]  # type: ignore
+        x = x + self.pe[:, : x.size(1)]
         return self.dropout(x)
 
 
diff --git a/doctr/models/recognition/crnn/pytorch.py b/doctr/models/recognition/crnn/pytorch.py
index b1e50f1ad9..daf0e56e58 100644
--- a/doctr/models/recognition/crnn/pytorch.py
+++ b/doctr/models/recognition/crnn/pytorch.py
@@ -249,7 +249,7 @@ def _crnn(
     _cfg["input_shape"] = kwargs["input_shape"]
 
     # Build the model
-    model = CRNN(feat_extractor, cfg=_cfg, **kwargs)  # type: ignore[arg-type]
+    model = CRNN(feat_extractor, cfg=_cfg, **kwargs)
     # Load pretrained parameters
     if pretrained:
         # The number of classes is not the same as the number of classes in the pretrained model =>