[Enhance] Improve Swin Doc and Add Tabs enxtation

[Ezra-Yu]

Motivation

Improve Swin Doc

Modification

1. Add Tabs enxtation
   

2. folded the abstract

3. improve the readme of swin and swinv2.

Use cases (Optional)

<!-- [TABS-BEGIN] -->

**Predict image**  # tab1

Content1  without "**xxxx**"

**Use the model**    # tab2

Content2  without "**xxxx**"

**Command**          # tab3

Content3 without "**xxxx**"

<!-- [TABS-END] -->

Checklist

Before PR:

• Pre-commit or other linting tools are used to fix the potential lint issues.
• Bug fixes are fully covered by unit tests, the case that causes the bug should be added in the unit tests.
• The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• The documentation has been modified accordingly, like docstring or example tutorials.

After PR:

• If the modification has potential influence on downstream or other related projects, this PR should be tested with those projects, like MMDet or MMSeg.
• CLA has been signed and all committers have signed the CLA in this PR.

[codecov]

Codecov Report

Base: 0.02% // Head: 91.29% // Increases project coverage by +91.27% 🎉

Coverage data is based on head (b53dbd0) compared to base (b8b31e9).
Patch has no changes to coverable lines.

❗ Current head b53dbd0 differs from pull request most recent head aedd1cd. Consider uploading reports for the commit aedd1cd to get more accurate results

Additional details and impacted files

@@             Coverage Diff              @@
##           dev-1.x    #1145       +/-   ##
============================================
+ Coverage     0.02%   91.29%   +91.27%     
============================================
  Files          121      136       +15     
  Lines         8217     9988     +1771     
  Branches      1368     1577      +209     
============================================
+ Hits             2     9119     +9117     
+ Misses        8215      660     -7555     
- Partials         0      209      +209     

Flag	Coverage Δ
unittests	91.29% <ø> (+91.27%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
mmcls/apis/inference.py	0.00% <0.00%> (ø)
mmcls/datasets/transforms/compose.py
mmcls/models/backbones/deit3.py	94.52% <0.00%> (ø)
mmcls/structures/utils.py	77.77% <0.00%> (ø)
mmcls/models/backbones/swin_transformer_v2.py	89.47% <0.00%> (ø)
mmcls/models/backbones/mobilevit.py	91.15% <0.00%> (ø)
mmcls/models/backbones/mvit.py	92.46% <0.00%> (ø)
mmcls/models/retrievers/__init__.py	100.00% <0.00%> (ø)
mmcls/models/backbones/mobileone.py	94.47% <0.00%> (ø)
mmcls/models/retrievers/base.py	100.00% <0.00%> (ø)
... and 126 more

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[tonysy]

LGTM