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.
tfs
fmc
libfuzzer
html-injections
wicket-1.6
redmine-api
superview
android-dark-theme
naudio
trimesh
wear-os-tiles
textflow
wcf-wshttpbinding
treetable
dremel
sift-tool
uikit-dynamics
qscrollbar
checkmark
primer3
android-cursoradapter
white-labelling
angularjs-ng-href
hdrimages
react-codemirror
inbound
inbound-security-rule
inspect
square-flow
django-i18n