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cs.LG2024
3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability
Baohao Liao, Christof Monz
Parameter-efficient finetuning (PEFT) methods effectively adapt large language models (LLMs) to diverse downstream tasks, reducing storage and GPU memory demands. Despite these adv…
cs.LG2024★ 1 cited
ApiQ: Finetuning of 2-Bit Quantized Large Language Model
Baohao Liao, Christian Herold, Shahram Khadivi +1
Memory-efficient finetuning of large language models (LLMs) has recently attracted huge attention with the increasing size of LLMs, primarily due to the constraints posed by GPU me…