The code is based on [fairseq]. You just need to replace the corresponding code in [fairseq] with our code.
fairseq-train \ data/data-bin/fn2abbr \ --source-lang fzh --target-lang azh \ --save-dir checkpoints/fn2abbr \ --task translation_lev \ --criterion nat_loss \ --arch abbr_transformer_small \ --noise random_mask \ --share-all-embeddings \ --optimizer adam --adam-betas '(0.9,0.98)' \ --lr 0.0005 --lr-scheduler inverse_sqrt \ --stop-min-lr '1e-09' --warmup-updates 10000 \ --warmup-init-lr '1e-07' --label-smoothing 0.0 \ --dropout 0.3 --weight-decay 0.01 \ --decoder-learned-pos \ --encoder-learned-pos \ --apply-bert-init \ --log-format 'simple' --log-interval 1000 \ --fixed-validation-seed 7 \ --max-tokens 8000 \ --save-interval-updates 1000 \ --max-update 200000 \ --keep-last-epochs 5 \ --batch-size 8
fairseq-generate \ data/data-bin/fn2abbr \ --gen-subset test \ --task translation_lev \ --path checkpoints/fn2abbr/checkpoint_best.pt \ --iter-decode-max-iter 2 \ --iter-decode-eos-penalty 0 \ --beam 1 \ --print-step \ --batch-size 1 \ --results-path data/data-bin/result/fn2abbr \