bert_text_pretty 是一个bert 文本特征化和文本后处理解码的包，用于bert工程推理
# -*- coding:utf-8 -*-
import numpy as np
from bert_text_pretty import cls,ner,relation,tokenization
text_list = ["你是谁123456"]
tokenizer = tokenization.FullTokenizer(vocab_file=r'F:\pretrain\chinese_L-12_H-768_A-12\vocab.txt',do_lower_case=True)
feat = cls.cls_text_feature(tokenizer,text_list,max_seq_len=128,with_padding=None)
print(feat)
feat = ner.ner_text_feature(tokenizer,text_list,max_seq_len=128,with_padding=None)
print(feat)
feat = relation.re_text_feature(tokenizer,text_list,max_seq_len=128,with_padding=None)
print(feat)
labels = ['标签1','标签2']
print(cls.load_labels(labels))
print(ner.load_label_bio(labels))
# logits 为bert 预测结果
# ner.ner_decoding(text_list,logits,labels,logits)
# logits 为bert 预测结果
# cls.cls_decoding(text_list,logits,labels,logits)
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Release files for bert-text-pretty 0.0.4
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| Tags | Python 3 |
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