diff --git a/docs/source/notes/mps.rst b/docs/source/notes/mps.rst
index 6ad44ba97714..cc2a781b590e 100644
--- a/docs/source/notes/mps.rst
+++ b/docs/source/notes/mps.rst
@@ -14,27 +14,31 @@ capabilities to setup and run operations on GPU.
 
 To get started, simply move your Tensor and Module to the ``mps`` device:
 
-.. code::
+.. code:: python
 
-    # Make sure the current PyTorch binary was built with MPS enabled
-    print(torch.backends.mps.is_built())
-    # And that the current hardware and MacOS version are sufficient to
-    # be able to use MPS
-    print(torch.backends.mps.is_available())
+    # Check that MPS is available
+    if not torch.backends.mps.is_available():
+        if not torch.backends.mps.is_built():
+            print("MPS not available because the current PyTorch install was not "
+                  "built with MPS enabled.")
+        else:
+            print("MPS not available because the current MacOS version is not 12.3+ "
+                  "and/or you do not have an MPS-enabled device on this machine.")
 
-    mps_device = torch.device("mps")
+    else:
+        mps_device = torch.device("mps")
 
-    # Create a Tensor directly on the mps device
-    x = torch.ones(5, device=mps_device)
-    # Or
-    x = torch.ones(5, device="mps")
+        # Create a Tensor directly on the mps device
+        x = torch.ones(5, device=mps_device)
+        # Or
+        x = torch.ones(5, device="mps")
 
-    # Any operation happens on the GPU
-    y = x * 2
+        # Any operation happens on the GPU
+        y = x * 2
 
-    # Move your model to mps just like any other device
-    model = YourFavoriteNet()
-    model.to(mps_device)
+        # Move your model to mps just like any other device
+        model = YourFavoriteNet()
+        model.to(mps_device)
 
-    # Now every call runs on the GPU
-    pred = model(x)
+        # Now every call runs on the GPU
+        pred = model(x)