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.
in-operator
resource-id
scriptblock
idisposable
angular2-form-validation
clever-cloud
cygwin
multiway-tree
linguistics
sl4a
sizetofit
timeit
dotnet-monitor
env
nstimezone
razorpay-andoid-sdk
instantclient
datatables-1.10
vb-like-operator
azure-function-async
copy-initialization
gulp-file-include
intern
perl5.8
glfw
preemptive
suman
limiting
photo-management
del