github.com/ekzhu/go-fasttext (go): Package fasttext provides a simple wrapper for Facebook fastText dataset (https://fasttext.cc/docs/en/crawl-vectors.html). It allows fast look-up of word embeddings from persistent data store (SQLite3).  Installation  After downloading a .vec data file from the fastText project, you can initialize the SQLite3 database (in your code):  This will create a new file on your disk for the SQLite3 database. Once the above step is finished, you can start looking up word embeddings (in your code):  Each word embedding vector is a slice of float32 with length of 300.  Note that you only need to initialize the SQLite3 database once. The next time you use it you can skip the call to BuildDB.  For faster querying during runtime, you can use an in-memory database.  This creates an in-memory SQLite3 database which is a copy of the on-disk one. Using the in-memory version makes query time much faster, but takes a few minutes to load the database.
Keywords: facebook|fasttext|golang|sqlite|wordembedding