Keras Js
Run Keras models in the browser, with GPU support using WebGL
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
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| GPU Accelerated JavaScript | ||||||||||
| Keras Js | 4,879 | | 31 | 6 | a year ago | 7 | February 09, 2018 | 83 | mit | JavaScript |
| Run Keras models in the browser, with GPU support using WebGL | ||||||||||
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| PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer | ||||||||||
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| :memo: a list of graphic programming resources | ||||||||||
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Readme
**This project is no longer active. Please check out TensorFlow.js.**
The Keras.js demos still work but is no longer updated.
Run Keras models in the browser, with GPU support using WebGL
Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc.
Library version compatibility: Keras 2.1.2
Interactive Demos
Check out the demos/ directory for real examples running Keras.js in VueJS.
- Basic Convnet for MNIST
- Convolutional Variational Autoencoder, trained on MNIST
- Auxiliary Classifier Generative Adversarial Networks (AC-GAN) on MNIST
- 50-layer Residual Network, trained on ImageNet
- Inception v3, trained on ImageNet
- DenseNet-121, trained on ImageNet
- SqueezeNet v1.1, trained on ImageNet
- Bidirectional LSTM for IMDB sentiment classification
Documentation
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Javascript
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Keras
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Webgl
Mnist
Imagenet
Keras Models