The in_features define the input features of your tensor for this linear layer, while out_features define the output features.
E.g. if you are working with 2 input features for each sample (let’s say height and weight for a dog classifier), you would define in_features=2 in your first linear layer. The number of output features depends on your architecture and you could chose any valid value, which “works”.
Have a look at CS231n 3 to get an example of the weight matrix and the mentioned names.