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试了一个百科预料生成的此向量,用gensim进行load(之所以用load方式,是因为想用gensim做增量学习),gensim.models.Word2Vec.load("sgns.baidubaike.bigram-char") 报错,
The text was updated successfully, but these errors were encountered:
你试试这样:
from gensim.models.keyedvectors import KeyedVectors w2v = KeyedVectors.load_word2vec_format('sgns.baidubaike.bigram-char', binary=False, unicode_errors='ignore')
Sorry, something went wrong.
多谢,可以load了。但还有个小问题,比之前word2vec的word embedding文件load消耗的时间明显要长,不知道什么原因。。。
因为:文件大。。。
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试了一个百科预料生成的此向量,用gensim进行load(之所以用load方式,是因为想用gensim做增量学习),gensim.models.Word2Vec.load("sgns.baidubaike.bigram-char") 报错,
The text was updated successfully, but these errors were encountered: