model.fit(train_features, train_weights, epochs=100, validation_split=0.2, verbose=0)


converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
open('./models/model.tflite', "wb").write(tflite_model)


model_size = os.path.getsize('./models/model.tflite')
print("TFLite model is {} bytes".format(model_size))


converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]
tflite_quant_model = converter.convert()


pip3 install https://dl.google.com/coral/python/tflite_runtime-2.1.0-cp37-cp37m-linux_armv7l.whl


import tflite_runtime.interpreter as tflite
interpreter = tflite.Interpreter(model_content=tflite_model_ffile)
interpreter.allocate_tensors()