Abstract
In this paper, we release an open-source library, called TextBox, to provide a unified, modularized, and extensible text generation framework. TextBox aims to support a broad set of text generation tasks and models. In our library, we implement 21 text generation models on 9 benchmark datasets, covering the categories of VAE, GAN, and pretrained language models. Meanwhile, our library maintains sufficient modularity and extensibility by properly decomposing the model architecture, inference, and learning process into highly reusable modules, which allows users to easily incorporate new models into our framework. The above features make TextBox especially suitable for researchers and practitioners to quickly reproduce baseline models and develop new models. TextBox is implemented based on PyTorch, and released under Apache License 2.0 at the link https://github.com/RUCAIBox/TextBox.
Cite
CITATION STYLE
Li, J., Tang, T., He, G., Jiang, J., Hu, X., Xie, P., … Wen, J. R. (2021). TextBox: A unified, modularized, and extensible framework for text generation. In ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the System Demonstrations (pp. 30–39). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.acl-demo.4
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