Testing whether the fast version is installed:
>>> from gensim.models import word2vec >>> assert word2vec.FAST_VERSION > -1
This model detects multi-word phrases that can be grouped, such as
new_york_times. Can be used as a preprocessor for word2vec or doc2vec models.
>>> bigram_transformer = gensim.models.Phrases(sentences) >>> model = Word2Vec(bigram_transformed[sentences], size=100, ...)
Let V as the size of the vocabulary and N as the dimension of the hidden layer (vector dimension).
model.syn0: \( V \times N \) matrix.
model.syn0[wordindex]returns the word vector.