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| # -*- coding: utf-8 -*- | |
| """ | |
| @author:XuMing([email protected]) | |
| @description: pip install gradio | |
| """ | |
| import gradio as gr | |
| from nerpy import NERModel | |
| # 中文实体识别模型(BertSoftmax) | |
| ner_model = NERModel(model_type='bert', model_name='shibing624/bert4ner-base-chinese') | |
| def ai_text(sentence): | |
| predictions, raw_outputs, entities = ner_model.predict([sentence]) | |
| print("{} \t Entity: {}".format(sentence, entities)) | |
| return entities | |
| if __name__ == '__main__': | |
| examples = [ | |
| ['常建良,男,1963年出生,工科学士,高级工程师,北京物资学院客座副教授'], | |
| ['在国家物资局、物资部、国内贸易部金属材料流通司从事调拨分配工作'], | |
| ] | |
| input = gr.inputs.Textbox(lines=4, placeholder="Enter Sentence") | |
| output_text = gr.outputs.Textbox() | |
| gr.Interface(ai_text, | |
| inputs=[input], | |
| outputs=[output_text], | |
| theme="grass", | |
| title="Chinese Named Entity Recognition(NER) Model shibing624/bert4ner-base-chinese", | |
| description="Copy or input Chinese text here. Submit and the machine will calculate the NER entity.", | |
| article="Link to <a href='https://github.com/shibing624/nerpy' style='color:blue;' target='_blank\'>Github REPO</a>", | |
| examples=examples | |
| ).launch() | |