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| import gradio as gr | |
| from mindformers.trainer import Trainer | |
| # 初始化trainer | |
| trainer = Trainer( | |
| task='token_classification', | |
| model='tokcls_bert_base_chinese', | |
| ) | |
| # examples | |
| warm_input_data = ["结果上周六他们主场0：3惨败给了中游球队瓦拉多利德，近7个多月以来西甲首次输球。", "清华大学座落于首都北京"] | |
| # warm_up | |
| trainer.predict( | |
| predict_checkpoint= | |
| './tokcls_bert_base_chinese_cluener.ckpt', | |
| input_data=warm_input_data) | |
| # 数据后处理，将数据转成gr.HighlightedText需要的数据 | |
| def post_procces(text, text_list): | |
| res = [] | |
| cur_index = 0 | |
| for item in text_list: | |
| res.append((text[cur_index:item["start"]], None)) | |
| res.append((text[item["start"]:(item["end"] + 1)], | |
| " ".join([item["entity_group"], | |
| str(item["score"])]))) | |
| cur_index = item["end"] + 1 | |
| res.append((text[cur_index:], None)) | |
| return res | |
| # 预测 | |
| def token_classification(text): | |
| res_list = trainer.predict(input_data=text) | |
| res = post_procces(text, res_list[0]) | |
| print(res) | |
| return res, res_list | |
| # gradio接口 | |
| gr.Interface( | |
| token_classification, | |
| gr.Textbox( | |
| label="Text", | |
| info="Enter sentence here..xt", | |
| lines=3, | |
| value="结果上周六他们主场0：3惨败给了中游球队瓦拉多利德，近7个多月以来西甲首次输球。", | |
| ), | |
| # ["highlight", "json"], | |
| [ | |
| gr.HighlightedText( | |
| label="Token Classification", | |
| combine_adjacent=True, | |
| ), | |
| gr.JSON() | |
| ], | |
| examples=[*warm_input_data], | |
| ).launch() | |