fintuneing seems to be out of fashion (if it were really ever in fashion), but I still see folks like Karpathy mention reaching for it as a tool.
But is anyone in any business capacity on here doing that? Are you finetuning any remote LLM or something self-hosted? What for?
I’m just curious where the line is of “oh this is better encoded in the models weights rather than in RAG/thinking over context stuff it needs to figure out.
Also, is this something that's a pain in the ass to manage multiple versions of the model? One (maybe more in draft mode) for each client?
What we are mostly producing are LoRAs, and we put them through a staged training process. The first stage is all about the textures, the second stage focuses on the product itself, and the last stage dials in the exact perspectives we need.
Despite what the research out there says, we actually get better results sticking with LoRAs instead of LoKRs. The pain is generating the dataset because you have to adapt it for every product. The actual training is basically just fire and forget.