https://github.com/huawei-noah/Efficient-Computing

Efficient computing methods developed by Huawei Noah's Ark Lab
https://github.com/huawei-noah/Efficient-Computing

binary-neural-networks knowledge-distillation model-compression pruning quantization self-supervised

Last synced: 11 months ago
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Efficient computing methods developed by Huawei Noah's Ark Lab

Host: GitHub
URL: https://github.com/huawei-noah/Efficient-Computing
Owner: huawei-noah
Created: 2019-09-04T10:39:36.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2024-04-08T09:17:21.000Z (almost 2 years ago)
Last Synced: 2024-05-22T01:01:24.258Z (over 1 year ago)
Topics: binary-neural-networks, knowledge-distillation, model-compression, pruning, quantization, self-supervised
Language: Jupyter Notebook
Homepage:
Size: 98.7 MB
Stars: 1,119
Watchers: 21
Forks: 198
Open Issues: 14
Metadata Files:
- Readme: README.md

StarryDivineSky - huawei-noah/Efficient-Computing - Computing项目，专注于开发高效计算方法。该项目可能包含多种优化计算性能的技术和工具。具体实现细节和适用场景需要查阅项目文档。项目目标是提升计算效率，可能涉及算法优化、硬件加速或其他创新技术。该项目可能包含代码示例、基准测试和相关研究论文。如需了解更多信息，请查阅项目中的README.md和其他文档。项目特色可能包括高性能、低功耗或特定领域的优化。项目工作原理可能涉及并行计算、分布式计算或异构计算。该项目可能面向开发者、研究人员和对高效计算感兴趣的从业者。请注意，具体功能和性能取决于项目的最新版本和配置。 (其他_机器学习与深度学习)

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