# Interpretation of the weights returned by Flux in model zoo example

I’m trying to dig through the model zoo examples for Flux to learn.
One of these is FizzBuzz:
Github source here

The model is defined as
`m = Chain(Dense(3, 10), Dense(10, 4), NNlib.softmax)`

To me, this looks like 2 Dense layers (i.e. nodes with parameter weights) plus one softmax layer (i.e. has no trainable parameters.

However, when I call `params(m)` I get 4 sets of weights:

• a 10x3 (which I expected)
• a 10x1 (which I did not expect)
• a 4x10 (which I expected)
• a 4x1 (which I did not expect)

Can anyone please explain what the intepretation of the nx1 layers is? Why are they there?

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These look like bias vectors.

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Define a Dense layer and give it a name, say layer. Then do layer. to see what’s inside. You will find a W matrix and a b vector.