What is MindSpore Hub
MindSpore Hub is a pre-trained model application tool of the MindSpore ecosystem, serving as a channel for model developers and application developers.
- Provide model developers with a convenient and fast channel for model release and submission.
- Provide application developers with high-quality pre-trained models, and complete the work of model migration to deployment quickly using model loading and fine-tuning APIs.
Current pre-trained models in MindSpore Hub mainly cover four mainstream task scenarios including image classification, object detection, semantic segmentation and recommendation. You can check more models in MindSpore Hub Website.
Features
- Flexible model loading: Access and experience pre-trained models quickly by searching models of interest on MindSpore Hub Website.
- Easy-to-use transfer learning: Achieve transfer learning in one step via MindSpore's flexbile interface.
Installation
Binaries
Install MindSpore Hub using pip
command. hub
depends on the MindSpore version used in current environment.
-
Please download whl package from MindSpore Hub download page.
pip install #TODO
-
Run the following command in a network-enabled environment to verify the installation.
import mindspore_hub as mshub model = mshub.load("mindspore/ascend/0.7/googlenet_v1_cifar10")
Quickstart
See the Quick Start to implement model loading and fine-tuning.
Docs
For more information about installation guide, tutorials and APIs, please check out the User Documentation.
Community
As one part of MindSpore community, the following information in MindSpore Hub including governance, communication and contributing is consistent with the content in MindSpore community.
Governance
Check out how MindSpore Open Governance works.
Communication
- MindSpore Slack - Communication platform for developers.
- IRC channel at
#mindspore
(only for meeting minutes logging purpose) - Video Conference:TBD
- Mailing-list:https://mailweb.mindspore.cn/postorius/lists
Contributing
Welcome contributions. See our Contributor Wiki for more details。
Release Notes
The release notes, see our RELEASE。