Once For All
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
About
OFA is an efficient AutoML technique that decouples model training from architecture search. Train only once, specialize for many hardware platforms, from CPU/GPU to hardware accelerators. OFA achieves a new SOTA 80.0% ImageNet top1 accuracy under the mobile setting (<600M FLOPs).
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- 1,955
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- 345
- License
- MIT
- Last commit
- 3 years ago
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MIT HAN Lab
Efficient AI Computing. PI: Song Han
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