| > I'm interested to know if anyone is using fine-tuning to train a model on proprietary or in-house codebases and documentation. I've done it, 1/2 the team though it was great 20% of the time, 1/2 the team hated it from day 0. I used roughly 500K lines of code. > How much effort is required to turn code into something one can use for fine-tuning? Very little to moderate, less than 200 lines of python, QWEM FIM, HF, LLAMA.CPP, LLAMA.CPP code extension. > RAG solutions seem to have their limitations, and fine-tuning might be a more effective approach. The only problem either way is keeping the information up to date, RAG just adds more cost to the inference process (which at my dev speed is pretty important). > How much effort is required to turn code into something one can use for fine-tuning? Fine tuning "fill in the middle" process is the process of taking a file, cutting out a some text in the middle and asking AI to guess what was there - there is a hugging face example that will have you doing it in an hour or less - your OPs team saying "No you cant litreally copy all code to a single folder" is probably the biggest hurdle (advise them you'll do it in CI and then they can stand up a FIM training endpoint that accepts a csv, pretty easy) |