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操作系统是Linux,python3.5,pyltp0.2.1 代码是: import os from pyltp import CustomizedSegmentor,Segmentor LTP_datadir = 'ltp_data' cws_model_path = os.path.join(LTP_datadir, 'cws.model') train_model_path = os.path.join(LTP_datadir, 'train.model') customized_segmentor = CustomizedSegmentor() customized_segmentor.load(cws_model_path, train_model_path) words = customized_segmentor.segment('2014年是公司发展任务繁重、挑战突出的一年,也是攻坚克难、创新发展的一年') print('\t'.join(words)) customized_segmentor.release()
使用otcws的customize-learn训练得到的train.model,在用customized_segmentor.loa加载模型之后结果完全不分词,但是使用learn训练得到的模型就可以正常分词,请问为什么呢?
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操作系统是Linux,python3.5,pyltp0.2.1
代码是:
import os
from pyltp import CustomizedSegmentor,Segmentor
LTP_datadir = 'ltp_data'
cws_model_path = os.path.join(LTP_datadir, 'cws.model')
train_model_path = os.path.join(LTP_datadir, 'train.model')
customized_segmentor = CustomizedSegmentor()
customized_segmentor.load(cws_model_path, train_model_path)
words = customized_segmentor.segment('2014年是公司发展任务繁重、挑战突出的一年,也是攻坚克难、创新发展的一年')
print('\t'.join(words))
customized_segmentor.release()
使用otcws的customize-learn训练得到的train.model,在用customized_segmentor.loa加载模型之后结果完全不分词,但是使用learn训练得到的模型就可以正常分词,请问为什么呢?
The text was updated successfully, but these errors were encountered: