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cs.CL2024
S2D: Sorted Speculative Decoding For More Efficient Deployment of Nested Large Language Models
Parsa Kavehzadeh, Mohammadreza Pourreza, Mojtaba Valipour +5
Deployment of autoregressive large language models (LLMs) is costly, and as these models increase in size, the associated costs will become even more considerable. Consequently, di…
cs.LG2024★ 2 cited
QDyLoRA: Quantized Dynamic Low-Rank Adaptation for Efficient Large Language Model Tuning
Hossein Rajabzadeh, Mojtaba Valipour, Tianshu Zhu +5
Finetuning large language models requires huge GPU memory, restricting the choice to acquire Larger models. While the quantized version of the Low-Rank Adaptation technique, named…