None of the use cases you are describing require training a new model. You really don't want to train a new model, that's not a good way of getting them to learn reliable facts and do so without losing other knowledge. The fine tuning for GPT 3.5 suggests something like under a hundred examples.
What you want is to get an existing model to search a well built index of your data and use that information to reason about things. That way you also always have entirely up to date data.
People aren't missing the use cases you describe, they're disagreeing as to how to achieve those.
What you want is to get an existing model to search a well built index of your data and use that information to reason about things. That way you also always have entirely up to date data.
People aren't missing the use cases you describe, they're disagreeing as to how to achieve those.