Add SwiftFormer

### Model description 'SwiftFormer' paper introduces a novel efficient additive attention mechanism that effectively replaces the quadratic matrix multiplication operations in the self-attention computation with linear element-wise multiplications. A series of models called 'SwiftFormer' is built based on this, which achieves state-of-the-art performance in terms of both accuracy and mobile inference speed. Even their small variant achieves 78.5% top-1 ImageNet1K accuracy with only 0.8 ms latency on iPhone 14, which is more accurate and 2× faster compared to MobileViT-v2. I would like to add this model to Huggingface. ### Open source status - [X] The model implementation is available - [X] The model weights are available ### Provide useful links for the implementation Paper: https://arxiv.org/abs/2303.15446 Original code and weights: https://github.com/Amshaker/SwiftFormer Author: @Amshaker