  In this paper, we experiment with Large Vocabulary Trick and Feature-rich
encoding applied to the Transformer model for Text Summarization. We could not
achieve better results, than the analogous RNN-based sequence-to-sequence
model, so we tried more models to find out, what improves the results and what
deteriorates them.
