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"歇业":[ 1.3860583 -0.81409717 -0.92763036 1.1122825 1.3357894 0.6043483
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0.875147 0.9869669 0.30925655 1.5207604 1.2042233 -1.8157089
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0.5142326 -1.8477277 -2.9161847 -0.567281 ]
"优先":[-5.4119444e-01 8.9504033e-01 -8.8243032e-01 5.3190738e-01
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1.2463185e+00 1.2747017e+00 3.9090326e-01 3.8641423e-01
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1.7237800e+00 -2.3636038e+00 -9.2975068e-01 2.9409796e-01
2.1566468e-01 9.3920481e-01 1.4659067e+00 -5.5749136e-01
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3.7490240e-01 -5.8155227e-01 -5.7184803e-01 1.0103072e+00
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9.9064380e-01 -5.8218714e-02 1.1785209e+00 6.2218654e-01]
"风波":[ 7.8848386e-01 1.3680700e+00 -8.5051060e-01 5.1331776e-01
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7.7446318e-01 6.9196695e-01 -1.0193858e+00 -8.0304646e-01
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3.5896277e-01 4.6627247e-01 1.2830055e+00 1.2674654e+00
1.9956338e-01 5.4379392e-01 -3.9895391e-01 -1.9290178e+00
2.3297289e-01 8.6174864e-01 6.2228894e-01 -1.7814378e+00
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8.5435176e-01 5.4415133e-02 -1.7413380e+00 8.7488675e-01
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-6.1883569e-01 -6.3656038e-01 -4.2385101e-01 -2.0263801e+00]
"错":[ 0.4096561 -1.5421077 -1.0132842 -0.02988318 -0.29011375 0.15273792
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0.41869944 2.252377 0.9381602 1.4255418 1.5092423 0.10553967
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1.8582369 -1.0917038 0.7630498 0.22739567 -1.4562818 1.704166
-3.268372 0.4745843 -2.1142685 -1.500847 1.0689963 1.4403657
0.5070863 0.83499116 1.1752889 -0.3413542 -0.38762814 0.547683
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-1.1906353 1.3272747 -2.1989286 0.28598177 -0.20033404 -2.534048
-1.585244 0.21658897 -0.1435779 1.4275544 ]
"阮国琴":[ 1.6374144e-01 -3.1603837e-01 1.2847790e-01 -5.2807993e-01
1.0837826e+00 7.2738886e-01 5.7700241e-01 5.3723150e-01
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5.1906109e-01 1.3394655e+00 -2.3951042e-01 -6.7795523e-02
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1.8025443e-02 1.4144819e+00 -1.7436783e+00 1.1263551e-01
4.5222524e-01 3.1564084e-01 -6.8977201e-01 -2.8300184e-01
3.5535029e-01 -6.5655529e-01 6.7510164e-01 1.2905830e+00
2.8767842e-01 1.1313210e+00 -2.2122171e-03 -2.3506628e-01
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3.4712619e-01 1.1959279e+00 5.0833143e-02 -2.4047368e+00
6.6362804e-01 -3.9694160e-01 4.0534201e-01 3.4108096e-01
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-6.3659257e-01 -8.8901126e-01 5.9732974e-01 -6.1935890e-01
1.2093543e+00 8.0956542e-01 -3.7246260e-01 -5.3340948e-01
-4.9947879e-01 3.9951932e-02 -7.8101671e-01 3.1953606e-01
8.2160246e-01 8.6405110e-01 4.9131820e-01 4.4526055e-0
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中英文语料训练CBOW模型获得词向量(pytorch实现) 自
共13个文件
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xml:4个
gitignore:1个
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中英文语料训练CBOW模型获得词向量(pytorch实现) 自然语言处理第二次作业: data文件夹中存储语料(中文语料以及英文语料由老师提供,另一份为中文停用词语料) output文件夹中存储输出的词向量文件 script文件夹中为CBOW的脚本,同时处理中文语料与英文语料 运行步骤:在脚本中确定训练中文或者是英语后,直接运行即可
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中英文语料训练CBOW模型获得词向量(pytorch实现) 自然语言处理第二次作业: data文件夹中存储语料(中文语料以及英文语料由老师提供,另一份为中文停用词语料) output文件夹中存储输出的词向量文件 script文件夹中为CBOW的脚本,同时处理中文语料与英文语料 运行步骤:在脚本中确定训练中文或者是英语后,直接运行即可 .zip (13个子文件)
word2vec
data
zh.txt 846KB
en.txt 1.04MB
stopwords.txt 5KB
output
zh_wordvec.txt 15.69MB
en_wordvec.txt 14.8MB
script
CBOW_ENandZH.py 9KB
.idea
word2vec.iml 495B
workspace.xml 9KB
misc.xml 198B
inspectionProfiles
profiles_settings.xml 174B
modules.xml 275B
.gitignore 50B
a.txt 19B
共 13 条
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