There is more material than you'd normally find, but it is very hard to even fine-tune at that volume, unfortunately. I think we might be able to bootstrap something like that with a shared corpus of related languages, though.
You can always fine tune with the corpus you have and then try in context on top the fine tuning even if it’s insufficient. Then with that - and perhaps augmenting with RAG against the corpus - you might be able to build a context that’s stable enough in the language that you can generate human mediated synthetic corpuses and other reinforcement to enrich the LORA.