The finetune would be an LLM where you say something like "my colors on the screen look to dark" and then it points you to Displays -> Brightness. It feels like a relatively constrained problem like finding the system setting that solves your problem is a good fit for a tiny LLM.
This would be a great experiment. I'm not sure how the OS integration would work, but as a first pass you could try finetuning the model to take natural language "my colors on the screen look to dark" and then have it output "Displays -> Brightness", then expand to the various other paths you would like the model to understand
32k context window so whatever fits in there. What is a finetune of mac system settings?
The finetune would be an LLM where you say something like "my colors on the screen look to dark" and then it points you to Displays -> Brightness. It feels like a relatively constrained problem like finding the system setting that solves your problem is a good fit for a tiny LLM.
This would be a great experiment. I'm not sure how the OS integration would work, but as a first pass you could try finetuning the model to take natural language "my colors on the screen look to dark" and then have it output "Displays -> Brightness", then expand to the various other paths you would like the model to understand
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It seems to dip into repeating itself pretty quickly on any task of actual complexity.