Description
Run trained Keras models in your browser, GPU-powered using WebGL. Models are serialized directly from the Keras JSON-format configuration file and associated HDF5 weights.
Keras.js alternatives and similar libraries
Based on the "Machine Learning" category.
Alternatively, view Keras.js alternatives based on common mentions on social networks and blogs.
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ConvNetJS
Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser. -
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m2cgen
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TensorFlow.js
A JavaScript library for training and deploying ML models in the browser and on Node.js.
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* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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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This project is no longer active. Please check out TensorFlow.js.The Keras.js demos still work but is no longer updated.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
Interactive Demos | Documentation
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
*Note that all licence references and agreements mentioned in the Keras.js README section above
are relevant to that project's source code only.