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.
sa-mp
lucid
typed-lambda-calculus
swinject
adehabitathr
core-video
restangular
polish-notation
ruby-hash
readdirectorychangesw
runge-kutta
cvat
sorl-thumbnail
pgadmin-4
timedelta
validation
iota
react-localization
fastavro
django-1.6
android-preferences
yattag
calabash
purely-functional
instruction-set
oauth-provider
jobrunr
replication-factor
dbconnection
cjson