This model was contributed by heytanay. The original code can be found here.
Usage tips

PoolFormer has a hierarchical architecture, where instead of Attention, a simple Average Pooling layer is present. All checkpoints of the model can be found on the hub.
One can use [PoolFormerImageProcessor] to prepare images for the model.
As most models, PoolFormer comes in different sizes, the details of which can be found in the table below.