Instruction-tuned models (e.g., GPT-4, Claude, Mixtral) perform well on many tasks out of the box. However, fine-tuning still has a place in specific domains. When and why would you still opt for fine-tuning over prompt engineering or RAG (retrieval-augmented generation)? Share your insights or examples.
Instruction-tuned models (e.g., GPT-4, Claude, Mixtral) perform well on many tasks out of the box. However, fine-tuning still has a place in specific domains. When and why would you still opt for fine-tuning over prompt engineering or RAG (retrieval-augmented generation)? Share your insights or examples.
