%0 Generic %1 https://doi.org/10.48550/arxiv.2203.10705 %A Tao, Chaofan %A Hou, Lu %A Zhang, Wei %A Shang, Lifeng %A Jiang, Xin %A Liu, Qun %A Luo, Ping %A Wong, Ngai %D 2022 %I arXiv %K %R 10.48550/ARXIV.2203.10705 %T Compression of Generative Pre-trained Language Models via Quantization %U https://arxiv.org/abs/2203.10705

@misc{https://doi.org/10.48550/arxiv.2203.10705, added-at = {2022-06-07T09:14:33.000+0200}, author = {Tao, Chaofan and Hou, Lu and Zhang, Wei and Shang, Lifeng and Jiang, Xin and Liu, Qun and Luo, Ping and Wong, Ngai}, biburl = {https://www.bibsonomy.org/bibtex/27ec06875d44f5a6e1d11e9a68cbba84f/tobias.koopmann}, copyright = {Creative Commons Attribution 4.0 International}, doi = {10.48550/ARXIV.2203.10705}, interhash = {e1b72fd436ecbc34a524dcdb5e5c2c58}, intrahash = {7ec06875d44f5a6e1d11e9a68cbba84f}, keywords = {}, publisher = {arXiv}, timestamp = {2022-06-07T09:14:33.000+0200}, title = {Compression of Generative Pre-trained Language Models via Quantization}, url = {https://arxiv.org/abs/2203.10705}, year = 2022 }