Autocomplete with deep learning
This can be easily worked out using a standard Seq2Seq word-level model without any modifications in the training process. During inference, in the decoder, just mask the vocabulary based on the partial word input which has been provided.

By masking, I mean to assign a very high score (inf) to words which don't start with the partial word input, thus constraining the decoder to predict words which only start with the partial word input.