diff --git a/mshub_res/assets/noah-cvlab/gpu/1.8/ofakd_v1.0_imagenet2012.md b/mshub_res/assets/noah-cvlab/gpu/1.8/ofakd_v1.0_imagenet2012.md new file mode 100644 index 0000000000000000000000000000000000000000..42d9b562cbd3fb76e9b70cf56279255d640d6e0f --- /dev/null +++ b/mshub_res/assets/noah-cvlab/gpu/1.8/ofakd_v1.0_imagenet2012.md @@ -0,0 +1,64 @@ +# OFAKD + +--- + +model-name: OFAKD + +backbone-name: resnet + +module-type: cv-classification + +fine-tunable: True + +input-shape: [224, 224, 3] + +model-version: 1.0 + +train-dataset: imagenet2012 + +accuracy: resnet50: 81.27 + +author: Noah's Ark Lab + +update-time: 2023-3-2 + +resnet-repo-link: https://gitee.com/mindspore/models/tree/master/official/cv/ResNet + +user-id: Noah's Ark Lab + +used-for: inference + +train-backend: gpu/ascend + +infer-backend: gpu/ascend + +mindspore-version: 1.8 + +asset: + +- file-format: ckpt + + asset-link: https://download.mindspore.cn/models/r1.8/ofakd_resnet_v180_imagenet2012_research_cv_top1acc81.27.ckpt + + +license: Apache2.0 + +summary: Masked Image Modeling with Local Multi-Scale Reconstruction for imagenet classification. + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on above repo link. + +## Citation + +1. Zhiwei Hao, Jianyuan Guo, Kai Han, Tang Yehui, Han Hu, Yunhe Wang, Chang Xu. **One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation**. NeurIPS 2023. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. \ No newline at end of file diff --git a/mshub_res/assets/noah-cvlab/gpu/1.8/vanillakd_v1.0_imagenet2012.md b/mshub_res/assets/noah-cvlab/gpu/1.8/vanillakd_v1.0_imagenet2012.md new file mode 100644 index 0000000000000000000000000000000000000000..f76b5f306f2293e401514611bc101cab584bde1d --- /dev/null +++ b/mshub_res/assets/noah-cvlab/gpu/1.8/vanillakd_v1.0_imagenet2012.md @@ -0,0 +1,64 @@ +# VanillaKD + +--- + +model-name: VanillaKD + +backbone-name: resnet + +module-type: cv-classification + +fine-tunable: True + +input-shape: [224, 224, 3] + +model-version: 1.0 + +train-dataset: imagenet2012 + +accuracy: resnet50: 83.08 + +author: Noah's Ark Lab + +update-time: 2023-3-2 + +resnet-repo-link: https://gitee.com/mindspore/models/tree/master/official/cv/ResNet + +user-id: Noah's Ark Lab + +used-for: inference + +train-backend: gpu/ascend + +infer-backend: gpu/ascend + +mindspore-version: 1.8 + +asset: + +- file-format: ckpt + + asset-link: https://download.mindspore.cn/models/r1.8/vanillakd_resnet_v180_imagenet2012_research_cv_top1acc83.08.ckpt + + +license: Apache2.0 + +summary: Masked Image Modeling with Local Multi-Scale Reconstruction for imagenet classification. + +--- + +## Introduction + +This MindSpore Hub model uses the implementation of resnet from the MindSpore model zoo on above repo link. + +## Citation + +1. Zhiwei Hao, Jianyuan Guo, Kai Han, Han Hu, Chang Xu, Yunhe Wang. **VanillaKD: Revisit the Power of Vanilla Knowledge Distillation from Small Scale to Large Scale**. NeurIPS 2023. + +## Disclaimer + +MindSpore ("we") do not own any ownership or intellectual property rights of the datasets, and the trained models are provided on an "as is" and "as available" basis. We make no representations or warranties of any kind of the datasets and trained models (collectively, “materials”) and will not be liable for any loss, damage, expense or cost arising from the materials. Please ensure that you have permission to use the dataset under the appropriate license for the dataset and in accordance with the terms of the relevant license agreement. The trained models provided are only for research and education purposes. + +To Dataset Owners: If you do not wish to have a dataset included in MindSpore, or wish to update it in any way, we will remove or update the content at your request. Please contact us through GitHub or Gitee. Your understanding and contributions to the community are greatly appreciated. + +MindSpore is available under the Apache 2.0 license, please see the LICENSE file. \ No newline at end of file