Get bigrams and trigrams in word2vec Gensim

Question

I am currently using uni-grams in my word2vec model as follows.

def review_to_sentences( review, tokenizer, remove_stopwords=False ):
    #Returns a list of sent         


        

Answer 1

Phrases and Phraser are those you should looking for

bigram = gensim.models.Phrases(data_words, min_count=1, threshold=10) # higher threshold fewer phrases.
trigram = gensim.models.Phrases(bigram[data_words], threshold=100) 

Once you are enough done with adding vocabs then use Phraser for faster access and efficient memory usage. Not mandatory but useful.

bigram_mod = gensim.models.phrases.Phraser(bigram)
trigram_mod = gensim.models.phrases.Phraser(trigram)

Thanks,