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• What Is MindSpore Hub
  • Features
• Environment Requirements
  • System Requirements and Software Dependencies
• Installation
  • Installation for development
  • Binaries
• Quickstart
• Docs
• Community
  • Governance
  • Communication
• Contributing
• Release Notes
• License

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.

Environment Requirements

System Requirements and Software Dependencies

• When the network is connected, dependency items in the setup.py file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.

Installation

Installation for development

1. Download source code from Gitee.

   git clone https://gitee.com/mindspore/hub.git

2. Compile and install in MindSpore Hub directory.

   cd hub
   python setup.py install

Binaries

Install MindSpore Hub using pip command. hub depends on the MindSpore version used in current environment.

1. Please download whl package from MindSpore Hub download page.

   pip install mindspore_hub-{version}-py3-none-any.whl

2. 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", num_classes=10)

Quickstart

See the Loading the Model from Hub to implement model loading and fine-tuning.

Docs

For more information about installation guide, tutorials and APIs, please check out the Loading the Model from Hub and Publishing Models using MindSpore Hub.

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。

License

Apache License 2.0

FAQ

• What to do when SSL: CERTIFICATE_VERIFY_FAILED occurs?
  When you behind a proxy, it sometimes will have some ssl verification fail problems. You can add the certificate into system to fix this problem. The fastest method is to disable python's ssl verification. Before import mindspore_hub, please add the codes.

import ssl
ssl._create_default_https_context = ssl._create_unverified_context

import mindspore_hub as mshub
model = mshub.load("mindspore/ascend/0.7/googlenet_v1_cifar10", num_classes=10)