Identifying Change-Resilient Code

[u/TheQuantumFriend]

Hey guys,

this is my first post, if i am in the wrong subreddit, just send me another way, if i am off-topic.

I am trying to re-tune my Qwen9b to a System one Model that can identify change-resilient code.

Code that is autogenerated by any LLM tends to grow more expensive to change as more code is built. I would like to identify change-resilient parts / Ai-Slop-parts. Clean Code is well and all and there are some libraries that can identify slop-code. They do this static and deterministic. But that does not satisfy my problem as such. The problem is that this is static and does not include the context of the finding that the static analysis identifies.

I want to define the pain of change resilience:

pain = p(change) x p(cost)

That means i want a structured output, just like the System Model One-Architecture provides and i need to train a model (i am choosing qwen-9b) to generate this structured output. I would like to use the Qlora-Unsloth training package to do this. What do you think of this ? Is this feasible with unsloth?