What role does transfer learning play in LLMs?

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Transfer learning plays a crucial role in LLMs by allowing models to leverage pre-trained knowledge for new tasks. This process involves taking a model trained on a large dataset and fine-tuning it on a smaller, task-specific dataset. Transfer learning improves efficiency and performance, as the model already understands basic language patterns. It reduces the need for extensive data and computational resources, making it a cost-effective approach for deploying powerful language models tailored to specific applications.

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