The use of fastText is specifically to transform words and sentences into efficient vector representations. Although fastText is written in C++, there are community-written Python bindings to train and use the models. Along with that, Python is one of the most popular languages used for NLP, and hence there are many other popular libraries in Python that support fastText models and the training of fastText models. Gensim and Spacy are two popular libraries that make it easy to load these vectors, transform, lemmatize, and perform other NLP tasks efficiently. This chapter will focus on how to use fastText with Python and its popular libraries. This chapter will also focus on showing you some common tasks that the two libraries can do to work with fastText models.
The topics that are covered in this chapter are as follows:
- FastText official bindings
- PyBind
- Preprocessed...
