PanGu-α

PanGu-α

Huawei
+
+

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About

PanGu-α is developed under the MindSpore and trained on a cluster of 2048 Ascend 910 AI processors. The training parallelism strategy is implemented based on MindSpore Auto-parallel, which composes five parallelism dimensions to scale the training task to 2048 processors efficiently, including data parallelism, op-level model parallelism, pipeline model parallelism, optimizer model parallelism and rematerialization. To enhance the generalization ability of PanGu-α, we collect 1.1TB high-quality Chinese data from a wide range of domains to pretrain the model. We empirically test the generation ability of PanGu-α in various scenarios including text summarization, question answering, dialogue generation, etc. Moreover, we investigate the effect of model scales on the few-shot performances across a broad range of Chinese NLP tasks. The experimental results demonstrate the superior capabilities of PanGu-α in performing various tasks under few-shot or zero-shot settings.

About

Through its Native Parallel Graph™ technology, the TigerGraph™ graph platform represents what’s next in the graph database evolution: a complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time. Combining the best ideas (MapReduce, Massively Parallel Processing, and fast data compression/decompression) with fresh development, TigerGraph delivers what you’ve been waiting for: the speed, scalability, and deep exploration/querying capability to extract more business value from your data.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI developers interested in a powerful large language model

Audience

Enterprise businesses looking for a complete Graph Database solution

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Not Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

No images available

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • The response time of a query is RealTime and the GSQL as a language is easy to learn.And there is a lot of data loaders like Kafka, CSV, Node Red and many other connectors. And did i mention that TigerGraph is the Graph db Leader.

Cons

  • - Fast - Light - Extensible - Scalable - ML AI - AML

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Huawei
Founded: 1987
China
arxiv.org/abs/2104.12369

Company Information

TigerGraph
United States
www.tigergraph.com

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PanGu-Σ

PanGu-Σ

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OPT

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DeepSpeed

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Grakn

Grakn

Grakn Labs

Categories

AI Models Supported

Categories

Database Supported
Graph Databases Supported

Integrations

Data Sentinel Not Supported
Hackolade Not Supported
MapWeave Not Supported
Peaka Not Supported
Salesforce Data 360 Not Supported
StarfishETL Not Supported

Integrations

Data Sentinel Supported
Hackolade Supported
MapWeave Supported
Peaka Supported
Salesforce Data 360 Supported
StarfishETL Supported
Claim PanGu-α and update features and information
Claim PanGu-α and update features and information
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