gensim加载词向量文件

# -*- coding: utf-8 -*-

# author: huihui

# date: 2020/1/31 7:58 下午

'''

根据语料训练词向量，并保存向量文件

'''

import os

import sys

import gensim

os.reload(sys)

sys.setdefaultencoding('utf-8')

# 需要提前分词

input_file = "corp_seg.txt"

sentences = gensim.models.word2vec.Text8Corpus(input_file)

# 训练词向量

model = gensim.models.word2vec.Word2Vec(sentences, sg=1, size=100, window=5, min_count=1, negative=3, sample=0.001,

                                        hs=1, workers=40)

# 保存词向量文件

model.save("corp_word2vec.model")

model.wv.save_word2vec_format("corp_word2vec.txt")

# 加载词向量文件

model = gensim.models.word2vec.Word2Vec.load("corp_word2vec.model")

model = gensim.models.KeyedVectors.load_word2vec_format("corp_word2vec.txt")