Hey Dmitry!

Good to meet you -- I'm a big fan of DVC. In our implementation, we've taken the approach of conforming to the standards (typically open-source) set by the frameworks for serialization (for example https://www.tensorflow.org/guide/saved_model). In our API design, it was important to integrate at the framework level (e.g. a tf.keras.models.Model object) for our client libraries. If you're using one of the widely available frameworks that we support, this results in a simple API where the serialization / deserialization is more of an implementation detail. If you're using a custom or rarer ML framework with an unstandardized serialization format, an open-source approach might work better.

Hope that was helpful!