That could work, but I'd expect the following issues: * For a lot of prompts every fine tuned model will make the same mistakes (they mostly share the same wei

That could work, but I'd expect the following issues: * For a lot of prompts every fine tuned model will make the same mistakes (they mostly share the same weights after all) and so you aren't getting nearly as much benefit as e.g. GPT-4 gets. * It's going to be really expensive at inference time, since you have to run multiple models even though in most cases they won't help much * Normally when people talk about hobbyists doing finetuning they mean <1M tokens, whereas Code Llama Python was finetuned on 100B tokens, way outside most people's price range. For the finetuning that you can afford, you can't teach it new knowledge, just show it how to apply the knowledge it already has.