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Named Recognition Entity based on BERT and CRF 基于BERT+CRF的中文命名实体识别

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你好,我有一些疑问 `back_points, index_points = [self.transitions[self.start_tag, :self.start_tag].cpu()], [torch.LongTensor([-1]).expand_as(forward)]` 在这里back_points初始化时只考虑了start_tag到各个tag的转移概率,是不是少加了1st word到各个tag的发射概率 还有就是 ```python for i in range(1, time_steps): # START_TAG -> 1st word -> 2nd word ->...->END_TAG emission_start = forward.expand(self.num_tag, self.num_tag).t() emission_end...

没看到forward 里边有用到self.crf; 感觉你只是再用bert跑。

![image](https://user-images.githubusercontent.com/55276343/91175468-7154d000-e713-11ea-90bd-bf5da9d5b62d.png) 为什么这个日志老是出错 找了好久也没找到原因 初学者 不好意思呀

/home/csx/remote_workdir/Bert_people_paper_2014_pytorch/preprocessing/data_processor.py line 244-247 ` ## Notes: label_id中不包括[CLS]和[SEP]` ` label_id = [label_map[l] for l in labels]` ` label_padding = [-1] * (max_seq_length-len(label_id))` ` label_id += label_padding` 考虑到input第一个字符是CLS,最后一个字符是SEP,label在padding时应该和input对齐,开头结尾分别是CLS,SEP,置为-1 `label_id = [-1]+label_id +[-1]...

# Patching CVE-2007-4559 Hi, we are security researchers from the Advanced Research Center at [Trellix](https://www.trellix.com). We have began a campaign to patch a widespread bug named CVE-2007-4559. CVE-2007-4559 is a...