diff --git a/recipes_source/distributed_device_mesh.rst b/recipes_source/distributed_device_mesh.rst
index cf87ecf16a9..3a04b8de4bf 100644
--- a/recipes_source/distributed_device_mesh.rst
+++ b/recipes_source/distributed_device_mesh.rst
@@ -121,7 +121,7 @@ users would not need to manually create and manage shard group and replicate gro
     import torch.nn as nn
 
     from torch.distributed.device_mesh import init_device_mesh
-    from torch.distributed.fsdp import FullyShardedDataParallel as FSDP, ShardingStrategy
+    from torch.distributed.fsdp import fully_shard as FSDP
 
 
     class ToyModel(nn.Module):
@@ -136,9 +136,9 @@ users would not need to manually create and manage shard group and replicate gro
 
 
     # HSDP: MeshShape(2, 4)
-    mesh_2d = init_device_mesh("cuda", (2, 4))
+    mesh_2d = init_device_mesh("cuda", (2, 4), mesh_dim_names=("dp_replicate", "dp_shard"))
     model = FSDP(
-        ToyModel(), device_mesh=mesh_2d, sharding_strategy=ShardingStrategy.HYBRID_SHARD
+        ToyModel(), device_mesh=mesh_2d
     )
 
 Let's create a file named ``hsdp.py``.