Exploring RAFT: The Future of AI with Retrieval-Augmented Fine-Tuning



Less Error Rates Merging

Augmenting fine-tuned development causes RAFT to remarkably improve the accuracy of specialized tasks. Instead, its performance in many benchmarks, such as TorchHub, earned gains of up to 76% against ordinary fine-tuning techniques.