FastText official bindings
The steps to install the official bindings for Python are covered in the first chapter. In this section, we will cover how to use the official fastText Python package to train, load, and use the models.
Using the Python fastText library, you will be able to implement all the necessary features that can be done using the command line. Lets take a look at the ways to implement unsupervised and supervised learning using Python fastText.
Note
Note: In this chapter, we will be using Python3 and so the code examples will be in that. For users who are using Python2, please take a look at the Appendix for notes on the considerations that you need to bear in mind when using Python2.
PyBind
Python bindings for fastText are made using the excellent PyBind library. PyBind is a lightweight library meant to expose C++ types in Python and vice versa, making it an excellent choice for creating the Python bindings for fastText. It supports almost all the popular C++ compilers such as...