To get the outcome you want, RAG (retrieval augmented generation) would be the way to go, not fine-tuning. Fine-tuning doesn't make the model memorize specific content like a book. It teaches new behaviors or styles. RAG allows the model to access and reference the book during inference. Our platform focuses on fine-tuning with structured datasets, so data needs to be in a specific format.

This is a very common topic, so I wrote a blog post that explains the difference between fine-tuning and RAG if you're interested: https://finetunedb.com/blog/fine-tuning-vs-rag