Incrementally transferring PyTorch weights over a limited channel

I am looking for a way to distribute a new version of PyTorch weights file to multiple computers doing inference. The connections are relatively slow, so reducing an amount of data could bring a great improvement. So I am wondering - if there is a way to create a "diff" between the previous and new sets of weights and transmit only it instead of sending the whole file - especially considering the fact that only few layers are trainable.