Official Pytorch implementation of Group-Transformer that adapts group-wise computations rather than reduces feature dimension or network depth. Please refer to the paper, "Scale down Transformer by Grouping Features for a Lightweight Character-level Language Model (COLING-2020)", for more details.
- This work has been done with PyTorch 0.4.1, CUDA 9.0, python 3.6 and Ubuntu 16.04.
pip3 install torch==0.4.1
- Download enwik8 dataset
sh download_enwik8.sh
- Train Group-Transformer
sh enwik_model_train.sh
Check the parameters and options in the file.
Feel free to contact me if there is any question (Sungrae Park sungrae.park@navercorp.com).
This repository contains the code originally forked from the transformer-xl.
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