If you don’t have a feedback feom output to next input, typically, you’d have a Linear (4, hidden_size) an RNN/GRU/LSTM with hidden_size input/output of sort and a Linear(hidden_size, 6).
Depending on the nature of the data, there are customerary models and/or preprocessing. For example Graves’ classic handwriting model uses offsets instead of coordinates to make the prediction targets more stationary and uses a Mixture Density Network to model the outputs.
I have implemented the handwriting generation in PyTorch here 20, but I’d highly recommend reading the original paper.
Best regards
Thomas