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AI 算法学习笔记
使用预训练语言模型ALBERT做中文NER
基于轻量级的albert实现albert+BiLstm+CRF
A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型
中文医学NLP公开资源整理:术语集/语料库/词向量/预训练模型/知识图谱/命名实体识别/QA/信息抽取/模型/论文/etc
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
Based on https://github.com/macanv/BERT-BiLSTM-CRF-NER
基于BERT的中文命名实体识别
使用预训练语言模型BERT做中文NER
Fine-grained named entity recognition using BERT
BERT-NER-as-service includes training, evaluation and docker service deployment. The code is organized from https://github.com/macanv/BERT-BiLSTM-CRF-NER.
a sklearn wrapper for Google's BERT model
Named Recognition Entity based on BERT and CRF 基于BERT+CRF的中文命名实体识别
bert-ner for chinese with BiLSTM+CRF model
(分类)The word2vec-BiLSTM-CRF model for CCKS-2019 task on Chinese clinical named entity recognition.
IN CCKS2019 relation extraction
CCKS 2019 中文短文本实体链指比赛技术创新奖解决方案
ccks baidu entity link 实体链接 第一名
(分类)CCKS2019 面向中文电子病历的命名实体识别
使用深度学习方法解析问题 知识图谱存储 查询知识点 基于医疗垂直领域的对话系统
CCKS2019中文命名实体识别任务。从医疗文本中识别疾病和诊断、解剖部位、影像检查、实验室检验、手术和药物6种命名实体。现已实现基于jieba和AC自动机的baseline构建、基于BiLSTM和CRF的序列标住模型构建。bert的部分代码主要源于https://github.com/charles9n/bert-sklearn.git 感谢作者。 模型最终测试集得分0.81,还有较大改进空间。可以当做一个baseline。
中文实体识别 bert/xlnet/albert ...预训练模型 +bilstm+crf / +crf
Keras实现简单的BiLSTM-CRF
面向中文电子病历的命名实体识别
高质量中文预训练模型集合:最先进大模型、最快小模型、相似度专门模型
达观算法比赛ner任务,从训练bert到预测。
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