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Description

Ascend AI Cloud Service delivers immediate access to substantial and affordable AI computing capabilities, serving as a dependable platform for both training and executing models and algorithms, while also providing comprehensive cloud-based toolchains and a strong AI ecosystem that accommodates all leading open-source foundation models. With its remarkable computing resources, it facilitates the training of trillion-parameter models and supports long-duration training sessions lasting over 30 days without interruption on clusters with more than 1,000 cards, ensuring that training tasks can be auto-recovered in less than half an hour. The service features fully equipped toolchains that require no configuration and are ready for use right out of the box, promoting seamless self-service migration for common applications. Furthermore, Ascend AI Cloud Service boasts a complete ecosystem tailored to support prominent open-source models and grants access to an extensive collection of over 100,000 assets found in the AI Gallery, enhancing the user experience significantly. This comprehensive offering empowers users to innovate and experiment within a robust AI framework, ensuring they remain at the forefront of technological advancements.

Description

Recent breakthroughs in natural language processing, comprehension, and generation have been greatly influenced by the development of large language models. This research presents a system that employs Ascend 910 AI processors and the MindSpore framework to train a language model exceeding one trillion parameters, specifically 1.085 trillion, referred to as PanGu-{\Sigma}. This model enhances the groundwork established by PanGu-{\alpha} by converting the conventional dense Transformer model into a sparse format through a method known as Random Routed Experts (RRE). Utilizing a substantial dataset of 329 billion tokens, the model was effectively trained using a strategy called Expert Computation and Storage Separation (ECSS), which resulted in a remarkable 6.3-fold improvement in training throughput through the use of heterogeneous computing. Through various experiments, it was found that PanGu-{\Sigma} achieves a new benchmark in zero-shot learning across multiple downstream tasks in Chinese NLP, showcasing its potential in advancing the field. This advancement signifies a major leap forward in the capabilities of language models, illustrating the impact of innovative training techniques and architectural modifications.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

Huawei Cloud ModelArts Yes 
MindSpore Yes 
PanGu Chat No 

Integrations

Huawei Cloud ModelArts No 
MindSpore No 
PanGu Chat Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Huawei Cloud

Founded

1987

Country

China

Website

www.huaweicloud.com/intl/en-us/product/modelarts/ascendaicloud.html

Vendor Details

Company Name

Huawei

Founded

1987

Country

China

Website

huawei.com

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