> Or is there a way to get better results by fine tuning? It seems that the general wisdom around LLMs is that you can get very good performance on small model

> Or is there a way to get better results by fine tuning? It seems that the general wisdom around LLMs is that you can get very good performance on small models if you fine tune for a specific task. In the case of code generation, I think you might get a good performance by fine tuning it on a specific programming language + codebase or architectural pattern. The main problem with fine tuning is getting a good dataset, so a cheap alternative would be to put a few examples of what you want to generate in the prompt. Then you would save these prompts as task specific "fine tunes" that you would select when you need to accomplish something. You might find this discussion helpful: https://news.ycombinator.com/item?id=37813806 https://news.ycombinator.com/item?id=37813806