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.
lichess
scala-maven-plugin
osgeo
f#-giraffe
cron-task
amazon-kcl
mysql-error-1364
anyconnect
const-char
system.exit
erlang-otp
content-for
typo3-10.x
sap-query
2048
love2d
automationpeer
connector
dbghost
system.net
.net-4.6.1
custom-post-type
pythonping
chronoforms
constant-time
winmerge
php-internals
robustness
localtunnel
capslock