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Efficient-AI-Backbones
huawei-noah/Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
★4.4kstars
Python
Updated: 5d ago
📋 Project at a Glance
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What's this?A open-source Models project, built with Python, focusing on convolutional-neural-networks and efficient-inference
Who made it?Maintained by huawei-noah team, 4.4K⭐ on GitHub, #332 out of 3201 in Models
Why does it exist?In the Models space, convolutional-neural-networks workflows faced efficiency bottlenecks. Efficient-AI-Backbones was built by huawei-noah to address these efficient-inference challenges.
What can it do?Key use cases: ghostnet, imagenet, model-compression
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/huawei-noah/Efficient-AI-Backbones
🔗 github.com/huawei-noah/Efficient-AI-Backbones
Topics
convolutional-neural-networksefficient-inferenceghostnetimagenetmodel-compressionpretrained-modelspytorchtensorflowtransformervision-transformer