diff --git a/docs/source-pytorch/advanced/model_parallel.rst b/docs/source-pytorch/advanced/model_parallel.rst
index 2408ca9376..04f8fc2d2a 100644
--- a/docs/source-pytorch/advanced/model_parallel.rst
+++ b/docs/source-pytorch/advanced/model_parallel.rst
@@ -187,12 +187,10 @@ Here's an example using that uses ``wrap`` to create your model:
 
 
     class MyModel(pl.LightningModule):
-        def __init__(self):
-            super().__init__()
+        def configure_model(self):
             self.linear_layer = nn.Linear(32, 32)
             self.block = nn.Sequential(nn.Linear(32, 32), nn.Linear(32, 32))
 
-        def configure_model(self):
             # modules are sharded across processes
             # as soon as they are wrapped with `wrap`.
             # During the forward/backward passes, weights get synced across processes