diff --git a/coremltools/converters/mil/backend/mil/load.py b/coremltools/converters/mil/backend/mil/load.py
index 051f88fa0..27aaeda84 100644
--- a/coremltools/converters/mil/backend/mil/load.py
+++ b/coremltools/converters/mil/backend/mil/load.py
@@ -619,7 +619,7 @@ def _decouple_state_and_input(
         List["proto.Model_pb2.FeatureDescription"], List["proto.Model_pb2.FeatureDescription"]
     ]:
         """
-        Utils seperates state input from non-state input features.
+        Utils separates state input from non-state input features.
         """
         state_features = []
         non_state_input_features = []
diff --git a/coremltools/converters/mil/backend/mil/test_load.py b/coremltools/converters/mil/backend/mil/test_load.py
index d6f0ac41d..de120c4ac 100644
--- a/coremltools/converters/mil/backend/mil/test_load.py
+++ b/coremltools/converters/mil/backend/mil/test_load.py
@@ -964,7 +964,7 @@ def func_1(y):
         # main function is the default function
         self.verify_stateful_model(mlmodel, np.zeros((3,)))
 
-        # save the mlmodel on disk, and load "main" and "func_1" seperately
+        # save the mlmodel on disk, and load "main" and "func_1" separately
         package_path = tempfile.mkdtemp(suffix=".mlpackage")
         mlmodel.save(package_path)
 
diff --git a/coremltools/converters/mil/mil/passes/defs/optimize_repeat_ops.py b/coremltools/converters/mil/mil/passes/defs/optimize_repeat_ops.py
index dbb61d290..1d7f3f864 100644
--- a/coremltools/converters/mil/mil/passes/defs/optimize_repeat_ops.py
+++ b/coremltools/converters/mil/mil/passes/defs/optimize_repeat_ops.py
@@ -575,7 +575,7 @@ def _fuse_casts_ops_across_blocks(self, block: Block, ops_to_fused: Tuple[Operat
     def _fuse_or_cancel_consecutive_casts_block_wrapper(self, block):
         def _fuse_or_cancel_consecutive_casts_block(block, cast_ops_across_blocks):
             # We first make sure all the inner blocks are optimized
-            # It is important to do it seperately in the very beginning, to ensure the last step of optimization cast ops across the block boundary is correct.
+            # It is important to do it separately in the very beginning, to ensure the last step of optimization cast ops across the block boundary is correct.
             for op in block.operations:
                 for b in op.blocks:
                     self._fuse_or_cancel_consecutive_casts_block_wrapper(b)