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An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU

Yang, Ruijia et al.
arXiv (All) · Papers
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and-cluster-computingartificial-intelligencedistributedparallel
Fine-tuning Large Language Models (LLMs) has become essential for domain adaptation, but its memory-intensive property exceeds the capabilities of most GPUs. To address this challenge and democratize LLM fine-tuning, we present SlideFormer, a novel system designed for single-GPU environments. Our in
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