diff --git a/colossalai/shardformer/layer/normalization.py b/colossalai/shardformer/layer/normalization.py
index 5aa21260..01453a05 100644
--- a/colossalai/shardformer/layer/normalization.py
+++ b/colossalai/shardformer/layer/normalization.py
@@ -165,7 +165,7 @@ class LayerNorm(BaseLayerNorm):
         Raises:
             AssertionError: If the provided module is not an instance of nn.LayerNorm.
         """
-        assert isinstance(module, nn.LayerNorm), "Only support conversion from nn.LayerNorm."
+        # assert isinstance(module, nn.LayerNorm), "Only support conversion from nn.LayerNorm."
 
         LazyInitContext.materialize(module)
 
@@ -174,7 +174,7 @@ class LayerNorm(BaseLayerNorm):
             # aggregation of these gradients is necessary during backpropagation.
             # Therefore, we annotate these parameters in advance to indicate the need for gradient aggregation.
             SeqParallelUtils.marked_as_sp_partial_derived_param(module.weight)
-            SeqParallelUtils.marked_as_sp_partial_derived_param(module.bias)
+            # SeqParallelUtils.marked_as_sp_partial_derived_param(module.bias)
 
         return module
 
@@ -209,9 +209,12 @@ class FusedLayerNorm(BaseLayerNorm):
 
         LazyInitContext.materialize(module)
         # get the attributes of the module
-        normalized_shape = module.normalized_shape
-        eps = module.eps
-        elementwise_affine = module.elementwise_affine
+        # normalized_shape = module.normalized_shape
+        # eps = module.eps
+        # elementwise_affine = module.elementwise_affine
+        normalized_shape = module.weight.size(0)
+        eps = module.variance_epsilon
+        elementwise_affine = True
         dtype = module.weight.dtype
         device = module.weight.device
 
@@ -244,7 +247,7 @@ class FusedLayerNorm(BaseLayerNorm):
             # aggregation of these gradients is necessary during backpropagation.
             # Therefore, we annotate these parameters in advance to indicate the need for gradient aggregation.
             SeqParallelUtils.marked_as_sp_partial_derived_param(layernorm.weight)
-            SeqParallelUtils.marked_as_sp_partial_derived_param(layernorm.bias)
+            # SeqParallelUtils.marked_as_sp_partial_derived_param(layernorm.bias)
 
         return layernorm
 
diff --git a/tests/test_shardformer/test_model/test_shard_command.py b/tests/test_shardformer/test_model/test_shard_command.py
index 6075f836..a7166e38 100644
--- a/tests/test_shardformer/test_model/test_shard_command.py
+++ b/tests/test_shardformer/test_model/test_shard_command.py
@@ -210,6 +210,7 @@ def check_forward_backward(model_fn, data_gen_fn, output_transform_fn, loss_fn,
     ],
 )
 def run_command_test(test_config):
+    print(test_config)
     sub_model_zoo = model_zoo.get_sub_registry("transformers_command",  "transformers_command_for_casual_lm")
 
     for name, (model_fn, data_gen_fn, output_transform_fn, loss_fn, _) in sub_model_zoo.items():