FastText

Luckily for us, there is an extension of the word2vec model that can approximate the unknown tokens – FastText. We can use it in a very similar way as we use word2vec:

from gensim.models import FastText
# create the instance of the model
model = FastText(vector_size=4,
                 window=3,
                 min_count=1)
# build a vocabulary
model.build_vocab(corpus_iterable=tokenized_sentences)
# and train the model
model.train(corpus_iterable=tokenized_sentences,
            total_examples=len(tokenized_sentences),
            epochs=10)

In the preceding code fragment, the model is trained on the same set of data as word2vec. model = FastText(vector_size=4, window=3, min_count...