戈乔莫的回答是对的
<p><code>gensim.models.KeyedVectors.load_word2vec_format("GoogleNews-vectors-negative300.bin.gz", binary=True)</code></p>
<p>如果仍有以下错误,请尝试升级gensim的所有依赖项(例如smart_open)</p>
<p><code>pip install --upgrade gensim</code></p>
<p><i>文件“/home/liann/PythonProjects/DeepRecommendation/Algorithm/Word2Vec.py”,第18行,在<strong>init中
self.model=gensim.models.KeyedVectors.load\u word2vec\u格式(w2v\u path,binary=True)</i></p>
<p>文件“/home/liann/PythonProjects/venvLiang/lib/python2.7/site packages/gensim/models/keyedvorts.py”,第191行,以加载word2vec_格式,utils.smart_open(fname)作为fin:</p>
<p>文件“/home/liann/PythonProjects/venvLiang/lib/python2.7/site packages/smart-open/smart-open-lib.py”,第138行,smart-open
返回文件_smart_open(解析的_uri.uri_路径,模式)</p>
<p>文件“/home/liann/PythonProjects/venvLiang/lib/python2.7/site packages/smart-open/smart-open-lib.py”,第642行,在文件“smart-open”中
返回压缩包装(打开(fname,mode),fname,mode)</p>
<p>文件“/home/liann/PythonProjects/venvLiang/lib/python2.7/site packages/smart-open/smart-open-lib.py”,第630行,压缩包装中
返回make_closing(gzip文件)(文件_obj,模式)</p>
<p>文件“/usr/lib64/python2.7/gzip.py”,第94行,在<strong>init中
fileobj=self.myfileobj=<strong>内置</strong>。打开(文件名、模式或“rb”)</p>
<p><strong>类型错误:强制使用Unicode:需要字符串或缓冲区,找到文件</strong></p>