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ease
features
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support

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Description

Palmier enables the activation of AI agents through GitHub events to autonomously create pull requests that are ready for merging, which can address bugs, produce documentation, and evaluate code without the need for human input. By linking triggers from GitHub or Slack—like the opening, updating, merging of pull requests, or changes in issue labels—to either pre-existing or customized agents, users can automatically implement features, conduct security assessments, refactor code, generate tests, and modify changelogs simultaneously, all within isolated environments that do not retain your code or utilize it for training purposes. With user-friendly drag-and-drop integrations available for platforms such as GitHub, Slack, Supabase, Linear, Jira, Sentry, and AWS, Palmier significantly enhances efficiency by delivering real-time, merge-ready pull requests with a 45 percent reduction in review latency and the capability for unlimited parallel executions. Its agents, licensed under MIT, function within secure, temporary environments governed by your permissions, thus ensuring complete data privacy and adherence to your operational protocols. This innovative approach not only streamlines your workflow but also empowers teams to focus on high-value tasks while the AI manages routine code-related activities.

Description

PanGu-α has been created using the MindSpore framework and utilizes a powerful setup of 2048 Ascend 910 AI processors for its training. The training process employs an advanced parallelism strategy that leverages MindSpore Auto-parallel, which integrates five different parallelism dimensions—data parallelism, operation-level model parallelism, pipeline model parallelism, optimizer model parallelism, and rematerialization—to effectively distribute tasks across the 2048 processors. To improve the model's generalization, we gathered 1.1TB of high-quality Chinese language data from diverse fields for pretraining. We conduct extensive tests on PanGu-α's generation capabilities across multiple situations, such as text summarization, question answering, and dialogue generation. Additionally, we examine how varying model scales influence few-shot performance across a wide array of Chinese NLP tasks. The results from our experiments highlight the exceptional performance of PanGu-α, demonstrating its strengths in handling numerous tasks even in few-shot or zero-shot contexts, thus showcasing its versatility and robustness. This comprehensive evaluation reinforces the potential applications of PanGu-α in real-world scenarios.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

No images available

Integrations

Amazon Web Services (AWS)
GitHub
Jira
Linear
Sentry
Slack
Supabase

Integrations

Amazon Web Services (AWS)
GitHub
Jira
Linear
Sentry
Slack
Supabase

Pricing Details

$30 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Palmier

Founded

2024

Country

United States

Website

www.palmier.io

Vendor Details

Company Name

Huawei

Founded

1987

Country

China

Website

arxiv.org/abs/2104.12369

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