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chinese-word2vec's Issues

glove-utf8无法使用

请问glove-utf8的语料库能提供所训练的词吗,词向量中貌似只有权重。。。

very useful model, How to fine tune?

thanks so much for the model, it's been very useful.
I'd like to apply your model in my application, but I don't know how to fine tune it, Can you help me out?
Thks a lot

读取cn.skipgram.bin.tar.gz错误

model = gensim.models.KeyedVectors.load_word2vec_format(fdir + 'cn.skipgram.bin.tar.gz', binary=True)

ValueError: invalid literal for int() with base 10: 'cn.skipgram.bin\x00\x00。。。。。。

你好,读取cn.skipgram.bin.tar.gz文件出现这个错误,查了很久都不知道原因

能详细介绍下训练过程吗?

这个训练之前有对文本进行分词吗?用的是什么分词工具?
关于训练参数,训练数据之类的详细说明一下?

unpickling stack underflow

Hi, recently I'm using your model for an NLP project. But it occurs some bugs.

In [2]: model = models.Word2Vec.load('cn.cbow.bin')
---------------------------------------------------------------------------
UnpicklingError                           Traceback (most recent call last)
<ipython-input-2-01c34d25b411> in <module>()
----> 1 model = models.Word2Vec.load('cn.cbow.bin')

/usr/local/lib/python2.7/dist-packages/gensim/models/word2vec.pyc in load(cls, *args, **kwargs)
   1760     @classmethod
   1761     def load(cls, *args, **kwargs):
-> 1762         model = super(Word2Vec, cls).load(*args, **kwargs)
   1763         # update older models
   1764         if hasattr(model, 'table'):

/usr/local/lib/python2.7/dist-packages/gensim/utils.pyc in load(cls, fname, mmap)
    246         compress, subname = SaveLoad._adapt_by_suffix(fname)
    247
--> 248         obj = unpickle(fname)
    249         obj._load_specials(fname, mmap, compress, subname)
    250         logger.info("loaded %s", fname)

/usr/local/lib/python2.7/dist-packages/gensim/utils.pyc in unpickle(fname)
    910     with smart_open(fname) as f:
    911         # Because of loading from S3 load can't be used (missing readline in smart_open)
--> 912         return _pickle.loads(f.read())
    913
    914

UnpicklingError: unpickling stack underflow

Platform:
Ubuntu 15.10/ Python2.7.9

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