Python Word2vec using well-trained models to generate word vectors

#text file must be utf-8 no BOM format fromGensim.models.deprecated.word2vecImportWord2vecmodel=Word2vec.load ('./model/word60.model')#3 files in one place: Word60.model Word60.model.syn0.npy Word60.model.syn1neg.npyPrint("Read model Successful") Word_list= ['the',            'words that don't exist',            'of the',            'I'm',            'You're',            'his',            'a',            '1',            'Complete',            'Eat',            'Apple',            'Banana',            'Glossary',            'Physical',            'Earth',            'Black Death',            'plague',            "', ] forWordinchword_list:ifWordinchModel.index2word:vec=Model[word]Print(Word,vec)Else:        Print(Word +'\t\t\t--not in the glossary'+'\ n')

The model files are as follows:

Link: https://pan.baidu.com/s/1c7V91VcWbHPBFIfmtWGb2g Password: MGPs

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Python Word2vec using well-trained models to generate word vectors