Let's say you have a corpus of text — 10 million words — about a specific topic.

1. What's the best way to "train a model" on that text?

2. Is that even the right term? Or is it using an existing foundational model and then augmenting it? Fine-tuning it? Something else?

It depends on how you want to use it.  if you need to ask an AI questions about it or come up with new ideas from it will require a different approaches.

asking questions is just a general AI that has a huge memory that you can load it all in.