Your first one consists of a 100 neurons input layer connected to one single output neuron
Your second one consists of a 100 neurons input layer, one hidden layer of 32 neurons and one output layer of one single neuron.
You have to think of your first layer as your input layer (with the same number of neurons as the dimenson, so 100 for you) connected to another layer with as many neuron as you specify (1 in your first case, 32 in the second one)
In Keras what is useful is the command
model.summary()