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Question 1 of 140

Which of the following are valid reasons to use parameter-efficient finetuning methods (like LoRA, adapters) in enterprise LLM deployments? Select all that apply.

(Select all that apply.)

Enabling faster deployment turnaround with smaller update sizes

Increasing the number of model parameters significantly with every additional task

Avoiding the need for training from scratch

Reducing GPU memory consumption during training

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