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  TITLE
  Addition of Swin Transformer for Computer Vision
  
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  # 🌟 Addition Swin Transformer
  
  ## Model description
  Swin Transformer (the name Swin stands for Shifted window) is initially described in arxiv, which capably serves as a general-purpose backbone for computer vision. It is basically a hierarchical Transformer whose representation is computed with shifted windows. The shifted windowing scheme brings greater efficiency by limiting self-attention computation to non-overlapping local windows while also allowing for cross-window connection.
  
  Swin Transformer achieves strong performance on COCO object detection (58.7 box AP and 51.1 masks AP on test-dev) and ADE20K semantic segmentation (53.5 mIoU on Val), surpassing previous models by a large margin.
  
  ## Open source status
  
  * [x] the model implementation is available: https://github.com/microsoft/Swin-Transformer
  * [x] the model weights are available: https://github.com/microsoft/Swin-Transformer
  * [x] who are the authors: [Swin Transformer](https://arxiv.org/pdf/2103.14030.pdf)
  
  ## Possible Task Support:
  Opensource Version Supports below tasks
  * Image Classification
  * Object Detection
  * Instance Segmentation
  * Semantic Segmentation
  * Video Recognition
  