Determined is an open-source deep learning training platform that makes building models fast and easy. Determined enables you to:
- Train models faster using state-of-the-art distributed training, without changing your model code
- Automatically find high-quality models with advanced hyperparameter tuning from the creators of Hyperband
- Get more from your GPUs with smart scheduling and cut cloud GPU costs by seamlessly using preemptible instances
- Track and reproduce your work with experiment tracking that works out-of-the-box, covering code versions, metrics, checkpoints, and hyperparameters
Determined integrates these features into an easy-to-use, high-performance deep learning environment — which means you can spend your time building models instead of managing infrastructure.
To use Determined, you can continue using popular DL frameworks such as TensorFlow and PyTorch; you just need to update your model code to integrate with the Determined API.
For a brief introduction to using Determined, start with the Quick Start Guide.
To use an existing deep learning model with Determined, follow the tutorial for your preferred deep learning framework:
The documentation for the latest version of Determined can always be found here.
If you need help, want to file a bug report, or just want to keep up-to-date with the latest news about Determined, please join the Determined community!
- Slack is the best place to ask questions about Determined and get support. Click here to join our Slack.
- You can also join the community mailing list to ask questions about the project and receive announcements.
- To report a bug, file an issue on GitHub.
- To report a security issue, email
[email protected].