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.
couchdb-futon
grafana-dashboard
systemevent
pymatgen
minute
ng2-pdfjs-viewer
qjsonobject
libgcrypt
ropensci
caniuse
database-metadata
fogbugz
crypto.com-exchange-api
sinon
rails-sprockets
webauthn
dynamicresource
monomac
echo-server
google-contacts-api
react-daterange-picker
insets
re-frame
py2neo
spark-java
android-billing
swift
nt
maven-indexer
git-tower