[scarecrow112]

This is interesting and could be a savior for Machine Learning(ML) engineering teams. In a typical ML workflow, there are three main entities to be managed: 1. Code 2. Data 3. Models Systems like Data Version Control(DVC) [1], are useful for versioning 2 & 3. DVC improves on usability by residing inside the project's main git repo while maintaining versions of the data/models that reside on a remote. With Git partial clone, it seems like the gap could still be reduced between 1 & 2/3.

[1] - https://dvc.org/