When using the scikit-learn library in Python, I can use the CountVectorizer to create ngrams of a desired length (e.g. 2 words) like so: from sklearn.metrics.
composition
asp.net-web-api2
servant-multipart
typography
accurev
android-vertical-seekbar
jsdom
totem
nsepy
temporal-database
flutter-canvas
jsonstream
multicol
dets
bootstrap-themes
wack
jrules
asp.net-core-3.1
adobe-connect
rds
loginview
incoming-call
vcloud-director-rest-api
simulte
dokuwiki
google-text-to-speech
qmessagebox
gulp-nunjucks-render
mysql-json
code-assist