t5-learning-mt-task-balanced

Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks

Using Transfer Learning for Code-Related Tasks

This is an unofficial reupload of t5-learning-mt-task-balanced based off the author's repo, in the SafeTensors format using transformers 4.40.1. I manually converted the checkpoints using the tf_2_pytorch_T5.py script and converted the tokenizers with my own script. The goal of this reupload is to prevent older models that are still relevant baselines from becoming stale as a result of changes in HuggingFace. Additionally, I may include minor corrections, such as model max length configuration.

Citation

@article{Mastropaolo2021StudyingTU,
  title={Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks},
  author={Antonio Mastropaolo and Simone Scalabrino and Nathan Cooper and David Nader-Palacio and Denys Poshyvanyk and Rocco Oliveto and Gabriele Bavota},
  journal={2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)},
  year={2021},
  pages={336-347}
}