Recently I found a little trick you can use to minimise the amount of training data required but still get the results you’re looking for. This is an example case, but applies to much more complex prompts aswell.
The idea is that you can supply training data by clearing specifying the number of data points your supplying. When you go to query for a completion, simply specify the larger number of results you’re looking for (6 in the case of this example) and it will return that quantity.
Why is this important?
I found myself supplying for example 6 training samples in order to get 6 back. The ability to then reduce that by 60ish% is a huge save on tokens when prompts are 500-700 tokens.
This only works on the instruct series (as per my testing) especially with more complex prompts.
Hope this helps somebody save tokens!