DIGITS (the Deep Learning GPU Training System) is a webapp for training deep learning models.

Note: We are no longer adding features, fixing bugs, or supporting the NVIDIA Deep Learning GPU Training System (DIGITS) software. You may continue to use the software if it meets your needs. However:

• For developers creating vision AI applications, we suggest NVIDIA TAO, an open source toolkit for AI model training and customization. Learn more about NVIDIA TAO.
• For developers interested in NVIDIA Project DIGITS, to learn more, visit NVIDIA Project DIGITS.

In addition to submitting pull requests, feel free to submit and vote on feature requests via our ideas portal.

Current and most updated document is available at NVIDIA Accelerated Computing, Deep Learning Documentation, NVIDIA DIGITS.

Official DIGITS container is available at nvcr.io via docker pull command.

Once you have installed DIGITS, visit docs/GettingStarted.md for an introductory walkthrough.

Then, take a look at some of the other documentation at docs/ and examples/:

• Getting started with TensorFlow
• Getting started with Torch
• Fine-tune a pretrained model
• Creating a dataset using data from S3 endpoint
• Train an autoencoder network
• Train a regression network
• Train a Siamese network
• Train a text classification network
• Train an object detection network
• Learn more about weight initialization
• Use Python layers in your Caffe networks
• Download a model and use it to classify an image outside of DIGITS
• Overview of the REST API

• First, check out the instructions above
• Then, ask questions on our user group

• First, check out the Getting Started page
• Then, ask questions on our user group

• Please let us know by filing a new issue
• Bonus points if you want to contribute by opening a pull request!
  • You will need to send a signed copy of the Contributor License Agreement to digits@nvidia.com before your change can be accepted.

Users shall understand that DIGITS is not designed to be run as an exposed external web service.