DOC Fix documentation on pickle portability
@@ -77,12 +77,11 @@ additional metadata should be saved along the pickled model:
This should make it possible to check that the cross-validation score is in the
same range as before.
-Since a model internal representation may be different on two different
-architectures, dumping a model on one architecture and loading it on
-another architecture is not a supported behaviour, even if it might work
-on some cases.
-To overcome the issue of portability, pickle models are often deployed in
-production using containers, like docker.
+Aside for a few exceptions, pickled models should be portable across
+architectures assuming the same versions of dependencies and Python are used.
+If you encounter an estimator that is not portable please open an issue on
+GitHub. Pickled models are often deployed in production using containers, like
+Docker, in order to freeze the environment and dependencies.
If you want to know more about these issues and explore other possible
serialization methods, please refer to this
