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    • SymPy: Symbolic Computing in Python

    PeerJ Computer Science（2017）SCI 4区

    Univ South Carolina

    Cited 1098|Views131
    Abstract
    SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become the standard symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select domain specific submodules. The supplementary materials provide additional examples and further outline details of the architecture and features of SymPy.
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
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    Chat Paper
    【要点】：论文介绍了开源的纯Python编写的符号计算系统SymPy，强调了其可扩展性和易用性，并讨论了其架构和功能，为科学Python生态提供了流行的符号库。
    

    【方法】：通过互动和程序化应用，构建了专注于可扩展性和易用性的SymPy。
    

    【实验】：论文描述了SymPy的架构，讨论了其功能和部分子模块，补充材料提供了更多示例和详细信息。