Model Merging for Fine-Tuned LLMs: SLERP, TIES and DARE

1Key Takeaways

• Originally published on AI Tech Connect .
• What model merging actually solves Say you have fine-tuned the same base model twice: once on a coding dataset, once on a customer-support transcript set.
• Each fine-tune is good at its own job and mediocre at the other.
• The obvious fix is to deploy both and route requests between them, but that means two GPUs, two sets of weights to keep patched, and a routing layer to maintain.