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GPT-based Generation for Classical Chinese Poetry
论文
论文
发布时间2019-06-29
发表arXiv:1907.00151
作者:Xin Jiang,Qun Liu,Yi Liao,Yasheng Wang
详细介绍
We present a simple yet effective method for generating high quality classical Chinese poetry with Generative Pre-trained Language Model (GPT). The method adopts a simple GPT model, without using any human crafted rules or features, or designing any additional neural components. While the proposed model learns to generate various forms of classical Chinese poems, including Jueju, L\"{u}shi, various Cipai and Couples, the generated poems are of very high quality. We also propose and implement a method to fine-tune the model to generate acrostic poetry. To the best of our knowledge, this is the first to employ GPT in developing a poetry generation system. We have released an online mini demonstration program on Wechat to show the generation capability of the proposed method for classical Chinese poetry.
代码仓库 (3)
huawei-noah/Pretrained-Language-Model/tree/master/NEZHA-Gen-TensorFlow官方TensorFlow
pwc-1/Paper-5/tree/main/nezhaMindSpore
MindSpore-paper-code-2/code399/tree/main/GPTMindSpore
