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.
rmariadb
android-websettings
protobuf-net.grpc
node-odbc
dylib
spooler
stylet
gitweb
custom-fields
wordpress-plugin-creation
cps
tfs-2019
digital-signature
request.form
appassembler
qt4
azure-china
ionide
azure-appservice
modalviewcontroller
deploy-keys
heremaps-ios-sdk
graphicscontext
viewwillappear
junit5-extension-model
color-thief
simics
coremidi
pelican
excel-addins