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?

training is good for it replies with sarcasm or it replies with prepared and filtered responses. you're talking about embedding new data for unique results i think

i am starting with openai gpt but then others hence the name unbias