thank for taking the time to read my questions. I have recently begun researching LSTM networks as I have finished my GA and am looking to progress to something more difficult. I believe I am using the classic LSTM (if that makes any sense) and have a few questions:

Do I need LSTM cells in all cell location? Or would I only use them in the input and output cells and use simple feedforward for the hidden neurons?

How do I go about implementing Bias values into a LSTM?

Assuming I create a Network that predicts the next few words of a sentence, does that mean my outputs should be every possible word that the network could conceivably use?

Any and all information is helpful!