gensim之word2vec增量训练

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word2vec增量训练
python word2vec_add.py patent.model new_patent.txt patent_new.model patent_new.vector

import logging
import os.path
import sys
from gensim.models import Word2Vec
from gensim.models.word2vec import LineSentenceif __name__ == '__main__':program = os.path.basename(sys.argv[0])logger = logging.getLogger(program)logging.basicConfig(format='%(asctime)s: %(levelname)s: %(message)s')logging.root.setLevel(level=logging.INFO)logging.info('running %s' % ' '.join(sys.argv))if len(sys.argv) < 5:print(globals()['__doc__'] % locals())'''model_path:已有模型对，对应patent.modelinp:增加分好词的数据，对应new_patent.txtoutput_model:新保存的模型，对应patent_new.modeloutput_txt:保存的词向量，对应patent_new.vector'''model_path, inp, output_model, output_txt = sys.argv[1:4]sentences = LineSentence(inp)model = Word2Vec.load(model_path)model.build_vocab(sentences, update=True)model.train(sentences, total_examples=2000000, epochs=5)model.save(output_model)model.wv.save_word2vec_format(output_txt, binary=False)

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