A model that works in a notebook demo isn’t necessarily ready for production. Before deploying a model from the Hub, start with the model card: it describes intended use, known limitations, license terms, and sometimes training data notes.
Then test it on a sample of your own data rather than relying on leaderboard scores. Check how it handles long inputs, other languages, and out-of-scope requests, and measure latency and memory use under realistic load. Keep the previous version deployable so you can roll back if quality drops after a change.