The ViT model consists of multiple Transformer blocks, which use the layers.MultiHeadAttention layer as a self-attention mechanism applied to the sequence of patches. The Transformer blocks produce a [batch_size, num_patches, projection_dim] tensor, which is processed via an classifier head with softmax to produce the final class probabilities output.