Could someone explain in simple terms exactly what fine-tuning does?
Does it show the model how to answer questions, or does it give it new information, or both? Is there a way to restrict answers to the fine-tuned data?
For example, if one would want to use an LLM to answer questions regarding a large, private knowledge base, would it make sense to fine-tune a model on this knowledge base?
If yes, how does one reduce hallucination? And would that perform better than feeding possible source documents as part of the prompt every time?
Does it show the model how to answer questions, or does it give it new information, or both? Is there a way to restrict answers to the fine-tuned data?
For example, if one would want to use an LLM to answer questions regarding a large, private knowledge base, would it make sense to fine-tune a model on this knowledge base?
If yes, how does one reduce hallucination? And would that perform better than feeding possible source documents as part of the prompt every time?