I should have quoted you more specifically, my apologies. I was responding to the comment that there was some training of the "model on your chosen book".

There is no fine-tuning done specific to the corpus you own. I noted this in a sibling comment, but both the pretraining and fine-tuning objective uses a generic dataset (redpajama) which "aims to maximize the generation probability of the next token given the KV cache of the previous memory tokens" (quote from section 2.2 of the paper).

This is why I noted you could really use any long-context model that also has good retrieval performance. They're training their own draft model in lieu of using an existing model, but you could get similar/better outcomes using something like claude sonnet 3.5.