Decentralized AI Model Training Infrastructure
DeCenter AI is a PaaS infrastructure that empowers machine learning engineers to train AI models more quickly and affordably through decentralized parallel training mechanisms.
DeCenter AI functions as a PaaS infrastructure, empowering machine learning engineers to expedite and make the training of AI models more cost-effective through decentralized parallel training methods.
The core objective of DeCenter AI is to democratize and decentralize AI model training. By offering a distributed training platform, it allows data scientists, machine learning engineers, researchers, and AI specialists to collaboratively contribute to the training of AI models. Structured around a distributed parallel training mechanism, DeCenter AI has been designed to facilitate the training of various ML and DL models in a significantly reduced time frame and cost compared to the current norms. Our platform incorporates a built-in incentive system, fueled by DCEN Tokens. This system not only rewards contributors and participants but also encourages them to undertake tasks such as reviewing, testing, and rating AI models.
- Decenter teams
- Model repository
- Model customization
- Auto training and testing
- Incentivisation and governance View our Features List.
- Data scientists
- Machine learning engineers
- AI Engineers View our Customer profile.
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Rapid iteration
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Cost effective
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Automated resource management
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Seamless deployment and scalability
We welcome contributions from the community! To get started, follow these steps:
- Fork the repository on GitHub.
- Clone your fork of the repository to your local machine.
- Create a new branch for your changes:
git checkout -b <your-username>/your-feature-branch. - Make your changes and commit them to your branch.
- Push your changes to your fork on GitHub.
- Open a pull request from your fork's branch to the main repository.
Please make sure to follow the Code of Conduct when contributing to this project.
DeCenter AI is released under the MIT License.
For any inquiries or assistance, please contact our support team at [email protected] or visit our website.