Fine tuning is generally not worth it over RAG with newer models unless you have a niche data set that's very different from the pretraining data. LoRAs/contro

Fine tuning is generally not worth it over RAG with newer models unless you have a niche data set that's very different from the pretraining data. LoRAs/control vectors are also generally better as they don't induce forgetting or hallucinations, and they're usually "good enough" with RAG.