My current project, which really helped me “level up” is using a frontier model to train a local model. I had the AI select the best model (it did research on hugging face - it really likes hugging face lmfao) for my hardware. It chose qwen 9B & it’s totally free. Use the frontier model to train it to your specs. I’m on the v6 training run of my local qwen model. It costs a monstrous amount of compute to train (several hundred dollars or lots of weekly resets). It’s gone from solving 2/8 of my quantum mechanics questions to 7/8. It’s gotten demonstrably better at visual IQ tests (ravens progressive matrices) - V0 could solve 1/60 questions correctly on an IQ test. V5 just solved 28/60. Having a frontier model train a local AI is how I really started to understand this shit. I’ve gone from ‘using it as an automated assistant’ to ‘I actually understand what an “adapter” is’. Anyone done similar projects and have advice? Or just done something similar? submitted by /u/SouthernRow2710
Originally posted by u/SouthernRow2710 on r/ArtificialInteligence
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