What kind of data is needed to train a RAG model effectively?
To train a Retrieval-Augmented Generation (RAG) model effectively, you need a large and diverse dataset that includes a wide array of high-quality, relevant textual information, ensuring the model can retrieve and generate context-rich content. This dataset should ideally encompass a variety of sources related to the specific domain of interest, enabling the model to understand and synthesize information accurately within the targeted context.