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.
mqttnet
plumber
animatedimagedrawable
vtable
card
edgedb
foundry-contour
baidu
bnd
angular-services
webpack-2
react-native-macos
geogebra
streamingmarkupbuilder
logback-classic
java-nio
mikroc
chat
user-input
tsyringe
bexio
database-normalization
fatbin
netbeans6.8
racf
cgcolorspace
google-optimize
sublimemerge
redistimeseries
inversion-of-control