This is a pytorch implementation of the Transformer model like tensorflow/tensor2tensor.
I tested it with PyTorch 1.0.0 and Python 3.6.8.
It's using SpaCy to tokenize languages for wmt32k
dataset. So, if you want to run wmt32k problem which is a de/en translation
dataset, you should download language models first with the following command.
$ pip install spacy
$ python -m spacy download en
$ python -m spacy download de
- Train a model.
$ python train.py --problem wmt32k --output_dir ./output --data_dir ./wmt32k_data
or
$ python train.py --problem lm1b --output_dir ./output --data_dir ./lm1b_data
If you want to try fast_transformer, give a model argument after installing
tcop-pytorch.
$ python train.py --problem lm1b --output_dir ./output --data_dir ./lm1b_data --model fast_transformer
- You can translate a single sentence with the trained model.
$ python decoder.py --translate --data_dir ./wmt32k_data --model_dir ./output/last/models