harvardnlp/seq2seq-attn

Torch implementation of a standard sequence-to-sequence model with attention where the encoder-decoder are LSTMs. Also has the option to use characters (instead of input word embeddings) by running a convolutional neural network followed by a highway network over character embeddings to use as inputs. The attention model is from Effective Approaches to Attention-based Neural Machine Translation, Luong et al. We use the global-attention model with the input-feeding approach from the paper. The character model is from Character-Aware Neural Language Models, Kim et al.