diff --git a/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py b/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py
index 1c25d1e621d43..c66fce3d4316a 100644
--- a/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py
+++ b/vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py
@@ -272,7 +272,7 @@ def create_weights(self, layer: torch.nn.Module, num_experts: int,
                        params_dtype: torch.dtype, **extra_weight_attrs):
 
         assert params_dtype == torch.float16, (
-            "float16 is required for MoE compressd models. Set dtype=torch.float16"  # noqa: E501
+            "float16 is required for MoE compressed models. Set dtype=torch.float16"  # noqa: E501
         )
 
         # Will transpose the loaded weight along the
@@ -306,7 +306,7 @@ def create_weights(self, layer: torch.nn.Module, num_experts: int,
         load_full_w2 = self.actorder and self.group_size != -1
         w2_scales_size = (intermediate_full
                           if load_full_w2 else intermediate_size)
-        # @eliza TODO: is this condition actually needed/is it doing anything?
+
         self.is_k_full = (not self.actorder) or (intermediate_size
                                                  == intermediate_full)
 
diff --git a/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w4a16_24.py b/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w4a16_24.py
index 61d1c911cd1ad..2e1b5e3c2d3b1 100644
--- a/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w4a16_24.py
+++ b/vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w4a16_24.py
@@ -62,7 +62,7 @@ def create_weights(self, layer: torch.nn.Module, input_size: int,
                        **kwargs):
 
         assert params_dtype == torch.float16, (
-            "float16 is required for marlin24 compressd models. Set dtype=torch.float16"  # noqa: E501
+            "float16 is required for marlin24 compressed models. Set dtype=torch.float16"  # noqa: E501
         )
 
         pack_factor = 32 // self.quant_type.size_bits