What hardware platforms does 昇思MindSpore support?

昇思MindSpore supports Ascend, CPU, and GPU hardware platforms.

How can I install 昇思MindSpore?

You can install 昇思MindSpore using Pip, Conda, Source, or Docker. Refer to the installation guide on the website for detailed instructions.

What are some of the key features of 昇思MindSpore?

Key features include automatic differentiation, automatic distributed parallel training, support for full-scenario deployment (edge, cloud, device), and a rich set of toolkits and model zoos for various AI tasks.

Mindspore.cn

Name: Mindspore.cn
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Huawei's open-source AI framework for full-scenario deep learning.

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Mindspore.cn Introduction

What is Mindspore.cn?

昇思MindSpore is a full-scenario AI framework developed by Huawei. It is an open-source deep learning framework that supports automatic differentiation and parallel processing, enabling training once and deployment across multiple scenarios. It supports deep learning training and inference in edge, cloud, and device scenarios, and is mainly used in AI fields such as computer vision and natural language processing. It is designed for data scientists and algorithm engineers and features source code transformation-based automatic differentiation, automatic distributed parallel training, data processing, and a graph execution engine. The framework is open source, fostering an AI development ecosystem.

How to use Mindspore.cn?

To use 昇思MindSpore, you can install it via Pip, Conda, Source, or Docker. The website provides installation guides and tutorials for learning the framework. You can explore various modules, toolkits, and model zoos for different AI tasks. The community offers forums and Gitee for support and collaboration.

Why Choose Mindspore.cn?

Choose Mindspore.cn if you want a versatile, open-source AI framework that works across edge, cloud, and devices. It’s great for deep learning tasks with features like automatic differentiation and distributed training, making it a solid choice for AI devs looking for flexibility and power.