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huolongshe 1b79b468df | 2 months ago | |
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requirements.txt | 9 months ago | |
run_model_server.py | 9 months ago |
中文分词任务就是把连续的汉字分隔成具有语言语义学意义的词汇。中文的书写方式不像英文等日耳曼语系语言词与词之前显式的用空格分隔。为了让计算机理解中文文本,通常来说中文信息处理的第一步就是进行文本分词。
目前提供通用新闻领域的分词模型, 采用无监督统计特征增强的StructBERT+softmax序列标注模型,序列标注标签体系(B、I、E、S),四个标签分别表示单字处理单词的起始、中间、终止位置或者该单字独立成词。
模型来源: https://www.modelscope.cn/models/damo/nlp_structbert_word-segmentation_chinese-base/summary
本模型基于 ServiceBoot微服务引擎 进行服务化封装,参见: 《CubeAI模型开发指南》
$ sh pip-install-reqs.sh
$ serviceboot start
或
$ python3 run_model_server.py
一键式本地容器化部署和运行,参见: 《CubeAI模型独立部署指南》 或 CubeAI Docker Builder
本模型服务可一键发布至 CubeAI智立方平台 进行共享和部署,参见: 《CubeAI模型发布指南》
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Python Shell Text Dockerfile
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》