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    "info": {
        "author": "Jiahuan Li, Tong Pu, Huiyun Yang, Yu Bao",
        "author_email": "lijh@nlp.nju.edu.cn",
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            "Programming Language :: Python :: 3",
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        "description": "\n.. contents::\n\n1 Installation and Usage\n------------------------\n\n1.1 Installation\n~~~~~~~~~~~~~~~~\n\nInstallation through pip:\n\n.. code:: shell\n\n    pip install njuseg\n\n1.2 Usage\n~~~~~~~~~\n\n.. code:: python\n\n    from njuseg import Segmenter\n    segmenter = Segmenter.load_model(model_pth,use_gpu=True)\n    sentences = ['\u7f8e\u56fd\u8054\u90a6\u50a8\u5907\u59d4\u5458\u4f1a 16 \u65e5\u53d1\u5e03\u7684\u5168\u56fd\u7ecf\u6d4e\u5f62\u52bf\u8c03\u67e5\u62a5\u544a\u663e\u793a\uff0c\u53bb\u5e74 12 \u6708\u521d\u81f3\u4eca\u5e74 1 \u6708\u4e0a\u65ec\uff0c\u7f8e\u56fd\u7ecf\u6d4e\u7ee7\u7eed\u6e29\u548c\u6269\u5f20\uff0c\u4f46\u7f8e\u56fd\u4f01\u4e1a\u5bf9\u7ecf\u6d4e\u524d\u666f\u7684\u4e50\u89c2\u7a0b\u5ea6\u6709\u6240\u4e0b\u964d\u3002','\u7f8e\u8054\u50a8\u6ce8\u610f\u5230\u4e86\u5e02\u573a\u5bf9\u5168\u7403\u7ecf\u6d4e\u653e\u7f13\u7b49\u98ce\u9669\u56e0\u7d20\u7684\u62c5\u5fc3\uff0c\u4f46\u5f53\u524d\u7f8e\u56fd\u7ecf\u6d4e\u53d1\u751f\u8870\u9000\u7684\u98ce\u9669\u5e76\u672a\u4e0a\u5347\u3002']\n    segmented_sentences = segmenter.seg(sentences)\n\n2 Performance\n-------------\n\n2.1 In domain:\n~~~~~~~~~~~~~~\n\nwith pretrained unigram + bigram embedding\n\n.. table::\n\n    +-------+-------+-------+-------+-------+\n    |   PKU |   MSR |  CTB5 |  CTB6 | NLPCC |\n    +=======+=======+=======+=======+=======+\n    | 96.63 | 96.52 | 98.14 | 96.13 | 95.82 |\n    +-------+-------+-------+-------+-------+\n\n3 Speed\n-------\n\nOn CPU: 20 k characters per second\nOn single NVIDIA GTX 1080 GPU: 160 k characters per second\n\n\n",
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        "license": "MIT",
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        "name": "njuseg",
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        "summary": "Chinese Word Segmenter developed by Nanjing University NLP Group",
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