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.
mc-dc
sonarlint-intellij
putimagedata
android-implicit-intent
query-planner
metpy
inverse-relationship
mat-option
astroquery
fedora-25
virtual-ip-address
ddl-trigger
python-pbr
file-pointer
guile
directxtk
winmain
photosphereviewer
android-jetpack-compose-text
sap-cloud-connector
custom-taxonomy
google-secret-manager
database-link
usedapp
cross-platform
concurrentmodificationexception
.net-core-2.1
vault
boxplot
autoencoder