- This repo contains interface to downstream NLP applications, as well as the implementations of them (which can either be a copy from respective author repositories or extensions to such a copy or totally written from scratch).
- The main purpose of this repo is to save time for current and future graduate students who work on areas related to NLP as it can help in performance testing of their upstream models. Also, as this repo is maintained by multiple students, there can be higher chances of the code being bug-free.
- Jupyter notebooks are highly discouraged. We strictly discourage commiting any of such notebooks into this repository. Also, we softly discourage the usage of it even for upstream experimentations (except for the case of Google Colab). If you disagree on our advise, we suggest you to read this slides from the Workshop on Reproducible AI, AAAI 2019.
- Currently, the plan is to have only one contributor who can control the master branch. Which means all other contributors should work on their branches and create a Pull Request against the master for the changes to get accepted.
- Communication between the contributors regarding the status of the project, ideas, backlogs etc., must be made only through features available within GitHub like Wiki, Issues, Projects, and Pull Requests. The reason for this is to preserve the history.