Cut 90% of Fine-Tuning Cost—Still Beat Baselines on Text and Vision Benchmarks
探讨模型调优方法,结合参数高效微调、多模态迁移学习等技术,提升预训练语言模型在视觉语言任务中的性能。 2025-9-9 09:13:23 Author: hackernoon.com(查看原文) 阅读量:4 收藏

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Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

September 9th, 2025

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    Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

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Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

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