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https://github.com/nvidia/digits
Deep Learning GPU Training System
https://github.com/nvidia/digits
caffe deep-learning gpu machine-learning torch
Last synced: about 1 month ago
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Deep Learning GPU Training System
- Host: GitHub
- URL: https://github.com/nvidia/digits
- Owner: NVIDIA
- License: bsd-3-clause
- Created: 2015-03-17T16:00:20.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2023-05-26T20:00:37.000Z (over 1 year ago)
- Last Synced: 2024-10-09T13:23:55.516Z (about 1 month ago)
- Topics: caffe, deep-learning, gpu, machine-learning, torch
- Language: HTML
- Homepage: https://developer.nvidia.com/digits
- Size: 48.8 MB
- Stars: 4,119
- Watchers: 318
- Forks: 1,376
- Open Issues: 626
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
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README
# DIGITS
[](https://travis-ci.org/NVIDIA/DIGITS)
DIGITS (the **D**eep Learning **G**PU **T**raining **S**ystem) is a webapp for training deep learning models.
The currently supported frameworks are: Caffe, Torch, and Tensorflow.
# Feedback
In addition to submitting pull requests, feel free to submit and vote on feature requests via [our ideas portal]( https://nvdigits.ideas.aha.io/).
# Documentation
Current and most updated document is availabel at
[NVIDIA Accelerated Computing, Deep Learning Documentation, NVIDIA DIGITS](https://docs.nvidia.com/deeplearning/digits/index.html).
# Installation
| Installation method | Supported platform[s] | Available versions | Instructions |
| --- | --- | --- | --- |
| Source | Ubuntu 14.04, 16.04 | [GitHub tags](https://github.com/NVIDIA/DIGITS/releases) | [docs/BuildDigits.md](docs/BuildDigits.md) |
Official DIGITS container is available at nvcr.io via docker pull command.
# Usage
Once you have installed DIGITS, visit [docs/GettingStarted.md](docs/GettingStarted.md) for an introductory walkthrough.
Then, take a look at some of the other documentation at [docs/](docs/) and [examples/](examples/):
* [Getting started with TensorFlow](docs/GettingStartedTensorflow.md)
* [Getting started with Torch](docs/GettingStartedTorch.md)
* [Fine-tune a pretrained model](examples/fine-tuning/README.md)
* [Creating a dataset using data from S3 endpoint](examples/s3/README.md)
* [Train an autoencoder network](examples/autoencoder/README.md)
* [Train a regression network](examples/regression/README.md)
* [Train a Siamese network](examples/siamese/README.md)
* [Train a text classification network](examples/text-classification/README.md)
* [Train an object detection network](examples/object-detection/README.md)
* [Learn more about weight initialization](examples/weight-init/README.md)
* [Use Python layers in your Caffe networks](examples/python-layer/README.md)
* [Download a model and use it to classify an image outside of DIGITS](examples/classification/README.md)
* [Overview of the REST API](docs/API.md)
# Get help
### Installation issues
* First, check out the instructions above
* Then, ask questions on our [user group](https://groups.google.com/d/forum/digits-users)
### Usage questions
* First, check out the [Getting Started](docs/GettingStarted.md) page
* Then, ask questions on our [user group](https://groups.google.com/d/forum/digits-users)
### Bugs and feature requests
* Please let us know by [filing a new issue](https://github.com/NVIDIA/DIGITS/issues/new)
* Bonus points if you want to contribute by opening a [pull request](https://help.github.com/articles/using-pull-requests/)!
* You will need to send a signed copy of the [Contributor License Agreement](CLA) to [email protected] before your change can be accepted.
# Notice on security
Users shall understand that DIGITS is not designed to be run as an exposed external web service.