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English(EN) HoliBench: A Cross-Platform Benchmarking and Deployment Toolkit for Foundation Models in CPS-IoT Applications

HoliBench工具包支持基础模型的跨平台评估

一个名为HoliBench的新工具包已被开发出来,旨在解决在资源受限的CPS-IoT应用上部署基础模型(包括大型语言模型)所面临的挑战。该工具包提供了一个统一的工作流程,用于在从单板计算机到GPU服务器的各种设备上评估模型的准确性、延迟和能耗。HoliBench的平台抽象层以及对多种模型模态和推理引擎的支持,实现了全面的跨设备测量,揭示了传统工具所忽略的权衡。该开源基础设施旨在促进面向部署的基础模型评估。 AI

影响 通过提供统一的评估框架,能够更有效地在边缘设备上部署基础模型。

排序理由 该项目是一篇研究论文,详细介绍了一个用于评估基础模型的新工具包。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

HoliBench工具包支持基础模型的跨平台评估

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该项目是一篇研究论文,详细介绍了一个用于评估基础模型的新工具包。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Inesh Chakrabarti, Zejun Xiong, Pragya Sharma, Mani Srivastava ·

    HoliBench:面向CPS-IoT应用的基座模型跨平台基准测试与部署工具包

    arXiv:2609.12412v1 Announce Type: cross Abstract: Foundation models, including large language models, vision-language models, and time-series foundation models, are increasingly deployed on embedded and edge platforms for CPS and IoT applications, where energy, latency, and memor…