English(EN) TensorDex: A Compact, Tensor-Centric Storage System for Modern AI Models

TensorDex存储系统将AI模型占用空间缩减70%

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-16 04:00

研究人员开发了TensorDex，一种旨在减小AI模型巨大存储占用的新型存储系统。通过在张量级别执行增量压缩，TensorDex比以往的方法更有效地利用了跨模型冗余。在Hugging Face模型上的评估显示，TensorDex实现了70.5%的存储空间缩减，并且与现有的最先进系统相比，压缩和解压缩速度更快。 AI

影响可能显著降低AI模型存储库的存储成本并加速模型共享。

排序理由该集群描述了一篇关于AI模型新型存储系统的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Tingfeng Lan, Zirui Wang, Yunjia Zheng, Zhaoyuan Su, Juncheng Yang, Yue Cheng · 2026-10-16 04:00

TensorDex：面向现代AI模型的紧凑型、张量中心化存储系统

arXiv:2604.17104v3 Announce Type: replace-cross Abstract: Modern model hubs store hundreds of petabytes of large language models (LLMs), with fine-tuned variants dominating the storage footprint. These variants contain substantial cross-model redundancy that delta compression can…

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报道来源 [1]

TensorDex：面向现代AI模型的紧凑型、张量中心化存储系统

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