OK perhaps I used slightly the wrong term. The docs[1] say that code-davinci-002 is "optimized for code completion tasks" though so it seems unlikely to fulfil the OPs purpose of playing around with an unaligned/sweary model which was my main point. Some of the uncensored models from huggingface would probably serve that purpose much better.
The reason you want a base model for code completion has nothing to do with code itself, it has to do with the fact that it completes text unlike all the instruction tuned models, which expect instructions. When you have code, there aren't necessarily any instructions present. You basically want autocomplete. That's what a base model does. But that doesn't mean it doesn't work with other things apart from code. After all, all other GPT-3.5 models are just code-davinci-002 with additional instruction and RLHF fine-tuning added, and they know countless other subject areas apart from code.
It's not hard to understand. We just have a disagreement about something that you think is very important probably partly because you know more about this than I do. Have a nice day. Thanks for explaining.
That's irrelevant because these are all fine-tuned.
> Code-davinci-002 is a code-tuned model
No, "code-tuned" isn't even a thing. It is a foundation model, which consists purely of pretreating. No fine-tuning is involved.
> Or the official source is
The official source says exactly what I just said.