diff --git a/compressai/entropy_models/entropy_models.py b/compressai/entropy_models/entropy_models.py
index acb98333..e43538dd 100644
--- a/compressai/entropy_models/entropy_models.py
+++ b/compressai/entropy_models/entropy_models.py
@@ -196,7 +196,9 @@ def dequantize(
 
     @classmethod
     def _dequantize(cls, inputs: Tensor, means: Optional[Tensor] = None) -> Tensor:
-        warnings.warn("_dequantize. Use dequantize instead.", stacklevel=2)
+        warnings.warn(
+            "_dequantize is deprecated. Use dequantize instead.", stacklevel=2
+        )
         return cls.dequantize(inputs, means)
 
     def _pmf_to_cdf(self, pmf, tail_mass, pmf_length, max_length):
@@ -395,7 +397,7 @@ def _get_medians(self) -> Tensor:
 
     def update(self, force: bool = False, update_quantiles: bool = False) -> bool:
         # Check if we need to update the bottleneck parameters, the offsets are
-        # only computed and stored when the conditonal model is update()'d.
+        # only computed and stored when the conditional model is update()'d.
         if self._offset.numel() > 0 and not force:
             return False
 
@@ -437,7 +439,7 @@ def loss(self) -> Tensor:
         return loss
 
     def _logits_cumulative(self, inputs: Tensor, stop_gradient: bool) -> Tensor:
-        # TorchScript not yet working (nn.Mmodule indexing not supported)
+        # TorchScript not yet working (nn.Module indexing not supported)
         logits = inputs
         for i in range(len(self.filters) + 1):
             matrix = self.matrices[i]