数据是从nlpcc数据中进行分词并取其中词数小于600的作为训练和预测数据命名为sample，数据处理脚本详见data\sample.py
模型的rouge评分如图所示，或者core\eval.txt：
具体脚本详见core\eval.py ，decode是对greedy search的结果进行decode
模型服务返回结果如下图：
生成采用的beam search，并未进行细致调参
预训练模型使用的是追一科技开源的t5-pegasus pytorch small版本，以mT5为基础架构和初始权重，通过类似PEGASUS的方式进行预训练。
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