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.
contact-list
activesync
reset-password
rails-activejob
stdin
system.io.fileinfo
workflowservice
application-loader
dataframe-js
non-printable
mellon
bitwise-or
vaadin21
tern
gijgo-treeview
citations
sharepoint-jsom
gemini
add-member
findandmodify
stimulsoft
diskimage
tensorflow-extended
google-datalayer
connection-string
fsc
amazon-kinesis-analytics
webfont-loader
protocol-handler
recursive-templates