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README.md

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 TCMNER is a fine-tuned BERT model that is ready to use for Named Entity Recognition of Traditional Chinese Medicine and achieves state-of-the-art performance for the NER task. It has been trained to recognize six types of entities: prescription (方剂), herb (本草), source (来源), disease (病名), symptom (症状) and syndrome（证型）.
 
-Specifically, this model is a TCMRoBERTa model, a fine-tuned model of RoBERTa for Traditional Chinese medicine, that was fine-tuned on the Chinese version of the [Haiwei AI Lab](https://github.com/huangxinping)'s Named Entity Recognition dataset.
+Specifically, this model is a TCMRoBERTa model, a fine-tuned model of RoBERTa for Traditional Chinese medicine, that was fine-tuned on the Chinese version of the [Haiwei AI Lab](https://www.haiweikexin.com/)'s Named Entity Recognition dataset.
 
 **Currently, TCMRoBERTa is only a closed-source model for my own company, and I will open source it in the future.**