I spent too much time puzzling out how to go from a Keras model written in Python, to having something deployed as a website with GitHub Pages. I will walk through what ended up working so you save time where I couldn't 😄

# ... the model variable should hold your trained model
import tensorflowjs as tfjs
tfjs.converters.save_keras_model(model, 'saved-model')

This will put a model.json file into the saved-model folder, along with shards that hold the weights. You will use this folder in a moment.

git clone https://github.com/tadeaspaule/tfjs-webpack-template.git

npm install

Check package.json if you want to see what's being installed. Basically, it's just @tensorflow/tfjs and then the required modules for webpack to run.

1. Copy-paste your model into build/assets/{directory-name}. You can see an example with build/assets/mnist-classifier
2. Change the code in index.js. Again, you can see it using the path to the example MNIST classifier.
3. You're good to go! Add some code that uses your trained model, like model.predict etc

npm start

You can check out deploy-example.bat and deploy-example.sh, and modify them so that they point to your repository. GitHub pages will run automatically, you just have to change the SSH url.