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---
arxiv: 2102.02017
language:
- code
---
# 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-no-pretraining-bf-task` based off the [author's repo](https://github.com/antonio-mastropaolo/TransferLearning4Code), 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
```bibtex
@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}
}
``` |