Developed by Maxime Méloux and Van Duy Ngo for the Terminology class of the NLP Master in IDMC, Nancy.
- Install the required packages by using
pip install -r requirements.txtandpython -m spacy download en_core_web_sm. - Download the required additional files and move them into the folders
embeds/(forenglish_fasttext_2017_10.vectors.npyandenglish_fasttext_2017_10) andoutput/(forfinal-model.pt). - The full training and inference process can be triggered by running
main.py. - Alternatively,
sandbox.pycan be run as a standalone program to play with TARS' capabilities.
Warning: TARS requires a lot of VRAM for training. We recommend using Grid5k or any other similar resource. However, inference can be performed using common resources such as a personal computer or laptop.
The results of running the fine-tuned TARS tagger on the test set can be found in output/tars_results.txt.