document round_trip in Json type documentation

docs/usage/types/json.md

@@ -1,11 +1,10 @@
 `Json`
 : a special type wrapper which loads JSON before parsing
 
-You can use `Json` data type to make Pydantic first load a raw JSON string.
-It can also optionally be used to parse the loaded object into another type base on
-the type `Json` is parameterised with:
+You can use the `Json` data type to make Pydantic first load a raw JSON string before
+validating the loaded data into the parametrized type:
 
-```py
+```py group='json'
 from typing import Any, List
 
 from pydantic import BaseModel, Json, ValidationError
@@ -23,6 +22,7 @@ print(AnyJsonModel(json_obj='{"b": 1}'))
 #> json_obj={'b': 1}
 print(ConstrainedJsonModel(json_obj='[1, 2, 3]'))
 #> json_obj=[1, 2, 3]
+
 try:
     ConstrainedJsonModel(json_obj=12)
 except ValidationError as e:
@@ -55,3 +55,15 @@ except ValidationError as e:
       Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='b', input_type=str]
     """
 ```
+
+When you dump the model using `model_dump` or `model_dump_json`, the dumped value will be the result of validation,
+not the original JSON string. However, you can use the argument `round_trip=True` to get the original JSON string back:
+
+```py group='json'
+print(ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json())
+#> {"json_obj":[1,2,3]}
+print(
+    ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json(round_trip=True)
+)
+#> {"json_obj":"[1,2,3]"}
+```