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  license: mit
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+ This is the 25 MB compressed version of GraphCodeBERT that has been fine-tuned for the Clone Detection task using [BigCloneBench](https://github.com/clonebench/BigCloneBench.git) dataset.
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+ The compression is based on our ASE 2022 paper named ["**Compressing Pre-trained Models of Code into 3 MB**"](https://arxiv.org/abs/2208.07120).
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+ If you are interested in using this model, please check our **GitHub repository: https://github.com/soarsmu/Compressor.git**. If you use the model or any code from our repo in your paper, please kindly cite:
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+ ```
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+ @inproceedings{shi2022compressing,
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+ author = {Shi, Jieke and Yang, Zhou and Xu, Bowen and Kang, Hong Jin and Lo, David},
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+ title = {Compressing Pre-Trained Models of Code into 3 MB},
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+ year = {2023},
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+ isbn = {9781450394758},
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+ publisher = {Association for Computing Machinery},
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+ address = {New York, NY, USA},
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+ url = {https://doi.org/10.1145/3551349.3556964},
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+ doi = {10.1145/3551349.3556964},
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+ booktitle = {Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering},
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+ articleno = {24},
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+ numpages = {12},
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+ keywords = {Pre-Trained Models, Model Compression, Genetic Algorithm},
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+ location = {Rochester, MI, USA},
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+ series = {ASE '22}
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+ }
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+ ```