[AnarchismIsCool]

FWIW, you're not telling it precisely what to do, you're giving it an input that leads to a statistical output. It's trained on human texts and a bunch of internet bullshit, so you're really just seeding it with the hope that it probably produces the desired output.

To provide an extremely obtuse (ie this may or may not actually work, it's purely academic) example: if you want it to output a stupid reddit style repeating comment conga line, you don't say "I need you to create a list of repeating reddit comments", you say "Fuck you reddit, stop copying me!"

[astrange]

This isn't true for an instruction-tuned model. They are designed so you actually do tell it what to do.

[AnarchismIsCool]

Sure, but it's still a statistical model, it doesn't know what the instructions mean, it just does what those instructions statistically link to in the training data. It's not doing perfect forward logic and never will in this paradigm.

[astrange]

The fine tuning process isn't itself a statistical model, so that principle doesn't work on it. You beat the model into shape until it does what you want (DPO and varieties of that) and you can test that it's doing that.

[AnarchismIsCool]

Yeah but you're still beating up a statistical model that's gonna do statistical things.

Also we're talking about prompt engineering more than fine-tune