CodeGeeX

CodeGeeX

AMiner
PanGu-α

PanGu-α

Huawei
+
+

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About

We introduce CodeGeeX, a large-scale multilingual code generation model with 13 billion parameters, pre-trained on a large code corpus of more than 20 programming languages. Based on CodeGeeX, we develop a VS Code extension (search 'CodeGeeX' in the Extension Marketplace) that assists the programming of different programming languages. Besides the multilingual code generation/translation abilities, we turn CodeGeeX into a custom programming assistant using its few-shot ability. It means that when a few examples are provided as extra prompts in the input, CodeGeeX will imitate what are done by these examples and generate codes accordingly. Some cool features can be implemented using this ability, like code explanation, summarization, generation with specific coding style, and more. For example, one can add code snippets with his/her own coding style, and CodeGeeX will generate codes in a similar way. You can also try prompts with specific formats to inspire CodeGeeX for new skills.

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.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and teams that want an AI coding assistant to help them write code, or want to leverage it by on-premise hosting due to privacy reasons

Audience

AI developers interested in a powerful large language model

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

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

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • CodeGeeX is a viable option to GitHub Copilot as it enables users to produce code blocks simply by entering their desired comments. It is compatible with over 20 programming languages and includes useful functionalities such as code completion, code translation, and code explanation. These features can enhance coding productivity significantly.

Cons

  • On occasion, there may be a delay in generating lengthy code.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

AMiner
China
codegeex.cn/

Company Information

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

Alternatives

Alternatives

PanGu-Σ

PanGu-Σ

Huawei
OPT

OPT

Meta
DeepSpeed

DeepSpeed

Microsoft

Categories

Categories

Integrations

C
C++
Go
Java
JavaScript
Python
Visual Studio Code

Integrations

C
C++
Go
Java
JavaScript
Python
Visual Studio Code
Claim CodeGeeX and update features and information
Claim CodeGeeX and update features and information
Claim PanGu-α and update features and information
Claim PanGu-α and update features and information