Difference between Gensim's FastText and Facebook's FastText

Question

I came upon the realization that there exists the original implementation of FastText here by which you can use fasttext.train_unsupervised in order to generate word vectors (see this link as an example). However, turns out that gensim also supports fasttext and its API is similar to that of word2vec. See example here.

I am wondering if there is a difference between the 2 implementations? The documentation was not clear but do they both mimic the paper Enriching Word Vectors with Subword Information? And if yes then why would one use gensim's fasttext over fasttext ?

Answer 1

I found 1 difference from the gensim's documentation:

word_ngrams (int, optional) – In Facebook’s FastText, “max length of word ngram” -
but gensim only supports the default of 1 (regular unigram word handling).

This means that gensim only supports unigrams, but no bigrams or trigrams.