A problem with fine tuning based on organization data is that if the underlying data changes, you'd need to fine-tune the model again each change. This might be okay for one-off changes (such as the name of the model in the example) but if it costs $300 each time (not to mention the time spent) and you have 100s/1,000s of changes per month, it's not really viable.
Comments
A problem with fine tuning based on organization data is that if the underlying data changes, you'd need to fine-tune the model again each change. This might be okay for one-off changes (such as the name of the model in the example) but if it costs $300 each time (not to mention the time spent) and you have 100s/1,000s of changes per month, it's not really viable.