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- from keras.models import load_model
- # load model
- model = load_model('model.h5')
- # summarize model
- print(model.summary())
- # use model to predict something
- predicted = model.predict(...)
- # save model and architecture to single file
- model.save('model.h5')
- print('Saved model to disk')
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