Loss would be computed the same way - you get the tags and compare them against the ground truth. The only difference is that you help the network with representations of characters.
It’s still pretty unclear, though. The way it’s written in the exercise 14 is that you have to input characters into one LSTM, get the hidden state of it and input that into another LSTM along with words. The only thing I don’t understand is how you can pass both integer words, and hidden state that is of float type (from the previous model).