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nzl-thu/Deep-Incubation
Deep-Incubation is a machine learning model from nzl-thu. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository contains the pre-trained models for Deep Incubation.
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Updated Mar 16, 2023
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From the Hugging Face model README
This repository contains the pre-trained models for Deep Incubation.
Title: Deep Incubation: Training Large Models by Divide-and-Conquering
Authors: Zanlin Ni, Yulin Wang, Jiangwei Yu, Haojun Jiang, Yue Cao, Gao Huang (Corresponding Author)
Institute: Tsinghua University and Beijing Academy of Artificial Intelligence (BAAI)
Publish: arXiv preprint (arXiv 2212.04129)
Contact: nzl22 at mails dot tsinghua dot edu dot cn
| model | image size | #param. | top-1 acc. | checkpoint |
|---|---|---|---|---|
| ViT-B | 224x224 | 87M | 82.4% | 🤗 HF link |
| ViT-B | 384x384 | 87M | 84.2% | 🤗 HF link |
| ViT-L | 224x224 | 304M | 83.9% | 🤗 HF link |
| ViT-L | 384x384 | 304M | 85.3% | 🤗 HF link |
| ViT-H | 224x224 | 632M | 84.3% | 🤗 HF link |
| ViT-H | 392x392 | 632M | 85.6% | 🤗 HF link |
data
├── train
│ ├── folder 1 (class 1)
│ ├── folder 2 (class 1)
│ ├── ...
├── val
│ ├── folder 1 (class 1)
│ ├── folder 2 (class 1)
│ ├── ...
If you find our work helpful, please star🌟 this repo and cite📑 our paper. Thanks for your support!
@article{Ni2022Incub,
title={Deep Incubation: Training Large Models by Divide-and-Conquering},
author={Ni, Zanlin and Wang, Yulin and Yu, Jiangwei and Jiang, Haojun and Cao, Yue and Huang, Gao},
journal={arXiv preprint arXiv:2212.04129},
year={2022}
}
Our implementation is mainly based on deit. We thank to their clean codebase.
If you have any questions or concerns, please send mail to [email protected].