minosvasilias
commented
1 year ago That looks interesting! I'd say for cases like this where existing code utilizing that structure only exists in a single private codebase, finetuning is probably not the ideal way to go about it.
Instead, i'd suggest either using embeddings to retrieve relevant examples to inject into prompts (llama_index-style) or just dumping as much example code as possible into the prompt as context for the model to follow. For the latter, larger context length for the used model would be very beneficial.
Both could still be done on top of a GDScript-finetuned model like godot-dodo of course. But larger GPT models might perform better at zero-shot learning as would be required in this case.
SeanR26
In my game, I wrote a library that allows me to build logic by composing objects, so I could customize it and subscribe to any step
Then I wrote higher-level presets and operators to describe character's skills and perks So the code mostly looks like this:
Actions
Perks
How presets/operators are made
I understand that this approach is kinda different from how people usually write code (and without explanation might be frustrating even for human haha), so the question is - what do you think, can fine-tuning with common data help me get better predictions for this approach?