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.
grunt-contrib-watch
rust-chrono
qwik
sonarscanner
mopub
constraint-validation
pascal
pcap4j
lastpass
submit-button
huobi
usb-otg
mysqlconnection
jsqlparser
azure-bicep
azure-boards
jcifs
accumulator
cookiecutter
libgsl
swagger-core
double-click
jetbrains-hub
ibm-sbt
debugging
data-ingestion
backbone.js-collections
azure-devops-server-2020
tobject
linux-mint-19