| --- |
| language: |
| - en |
| - vi |
| license: bsl-1.0 |
| datasets: |
| - neuralwork/arxiver |
| metrics: |
| - accuracy |
| base_model: |
| - Freepik/flux.1-lite-8B-alpha |
| new_version: microsoft/OmniParser |
| pipeline_tag: translation |
| library_name: allennlp |
| tags: |
| - finance |
| - legal |
| - text-generation-inference |
| --- |
| # CodeReviewer |
|
|
| ## Model description |
|
|
| CodeReviewer is a model pre-trained with code change and code review data to support code review tasks. |
|
|
| [CodeReviewer: Pre-Training for Automating Code Review Activities.](https://arxiv.org/abs/2203.09095) Zhiyu Li, Shuai Lu, Daya Guo, Nan Duan, Shailesh Jannu, Grant Jenks, Deep Majumder, Jared Green, Alexey Svyatkovskiy, Shengyu Fu, Neel Sundaresan. |
| [GitHub](https://github.com/microsoft/CodeBERT/tree/master/CodeReviewer) |
|
|
| ## Citation |
|
|
| If you user CodeReviewer, please consider citing the following paper: |
|
|
| ``` |
| @article{li2024codereviewer, |
| title={CodeReviewer: Pre-Training for Automating Code Review Activities}, |
| author={Li, Zhiyu and Lu, Shuai and Guo, Daya and Duan, Nan and Jannu, Shailesh and Jenks, Grant and Majumder, Deep and Green, Jared and Svyatkovskiy, Alexey and Fu, Shengyu and others}, |
| journal={arXiv preprint arXiv:2203.09095}, |
| year={2024} |
| } |
| ``` |
