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LLM Fine-tuning and Model Merging for Cost-Effective Adaptation

“Training LLMs from scratch costs $ millions in compute. But LLMs can cheaply be adapted to new tasks via fine-tuning, leading to a proliferation of models that suit specific use cases. Fine-tuned models can be rapidly merged to combine capabilities and generalize to new skills.”

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