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.
nscollectionviewflowlayout
pythagorean
azure-xplat-cli
pitch
laravel-models
jxloginpane
falco
rastervis
state
azure-database-mysql
mariadb-10.2
scraper
log4net-appender
ui-grid
boxapiv2
dlq
machinekey
extended-sql
array-comparison
firebase-app-indexing
languagetool
canopen
3gp
nestjs-passport
booleanquery
documentviewer
android-universal-link
resources
tfx
file-monitoring