Dear, happy new year!

I have read the tutorial:

Computing gradients in parallel with Amazon Braket

Is it possible to customise it so someone can run a hybrid model?

In my case my qnode is defined as:

```
@qml.qnode(dev, interface="tf", grad_method="backprop")
def qnode(inputs, weights):
for i in range(blocks):
qml.templates.AngleEmbedding(inputs, wires=range(n_qubits))
qml.templates.StronglyEntanglingLayers(weights[i], wires=range(n_qubits))
return [qml.expval(qml.PauliZ(i)) for i in range(n_qubits)]
```

And i also have two classical keras layers and a hybrid model defined as:

`modelh = tf.keras.models.Sequential([clayer1,qlayer,clayer2])`

Thanks in advance!