The sample output is interesting - it has highly suggestive chapter titles which read like pretty normal story beats. It seems like it's guiding itself on these, then able to chunk out longer form writing per chapter.
For what it's worth, the writing is .. bland. In the way that only an LLMs writing can be -- relatively grammatically sound, and totally soulless. I will never think of the love story of Elizabeth and Thomas again, despite having read the entire thing.
In early days of GPT-3, I experimented a lot with getting it respond as certain authors, and it was really quite excellent at that. This is one of the many things that seem likely to have been nerfed over time, I'd guess partly because human preference training just asks for bland responses, and partly because the injected prompts from OpenAI strongly discourage doing things related to real people, and those preferences are carried through, subtlely or not, into the augmented training data most open models tune on.
For what it's worth, the writing is .. bland. In the way that only an LLMs writing can be -- relatively grammatically sound, and totally soulless. I will never think of the love story of Elizabeth and Thomas again, despite having read the entire thing.
In early days of GPT-3, I experimented a lot with getting it respond as certain authors, and it was really quite excellent at that. This is one of the many things that seem likely to have been nerfed over time, I'd guess partly because human preference training just asks for bland responses, and partly because the injected prompts from OpenAI strongly discourage doing things related to real people, and those preferences are carried through, subtlely or not, into the augmented training data most open models tune on.