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.
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heritrix
django-postgresql
test-project
angular-routing-parameter
url-routing
tree-conflict
dnf
runtime.exec
mysql-connect
page-setup
arduino-ide
dllexport
benthos
google-workspace-add-ons
kendo-ui-mvc
procedural-generation
uipath-apps
aws-aurora-serverless
tournament
seam3
hyperledger-fabric-orderer
fiware-orion
appcompatdelegate
librosa
outlook.application
anagram
elm
taskfactory
direct-line-botframework