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.
fullcalendar-scheduler
properties.settings
multibox
regex
scjp
wep
aspx-user-control
xwpf
simple-peer
reportingservices-2005
ng-packagr
pktoolpicker
putchar
skitter-slider
nimbus-jose-jwt
boost-fiber
prompt
azure-backup-vault
defaulted-functions
watchkit
solus
pingfederate
hoppscotch
implode
conversion-tracking
typedef
picklist
photosframework
dokan
pygmentize