into the thousands of categories used in the imagenet competition we'll also use a file that doesn't include the weights for that last layer we hand this argument pooling equals average that says that if we had extra channels in our tensor at the end of this step we want to collapse them to a 1d tensor by taking an average across channels we'll come back to intricacies of pooling in a later lesson but now we have a pre-trained model that creates the layer you saw in the graphic will add a dense layers to make predictions