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- This is an *unofficial* reupload of t5-learning-no-pretraining-bf-task in the `SafeTensors` format using `transformers` `4.40.1`. 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.
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ arxiv: 2102.02017
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+ language:
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+ - code
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+ ---
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+ # Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks
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+ ## Using Transfer Learning for Code-Related Tasks
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+ 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.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @article{Mastropaolo2021StudyingTU,
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+ title={Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks},
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+ author={Antonio Mastropaolo and Simone Scalabrino and Nathan Cooper and David Nader-Palacio and Denys Poshyvanyk and Rocco Oliveto and Gabriele Bavota},
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+ journal={2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)},
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+ year={2021},
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+ pages={336-347}
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+ }
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+ ```