doc(hansbug): Add readme

README.md

 # DI-treetensor
-Tree Nested PyTorch Tensor Lib
+
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+
+`treetensor` is a generalized tree-based tensor structure mainly developed by [OpenDILab Contributors](https://github.com/opendilab).
+
+Almost all the operation can be supported in form of trees in a convenient way to simplify the structure processing when the calculation is tree-based.
+
+## Installation
+
+You can simply install it with `pip` command line from the official PyPI site.
+
+```shell
+pip install di-treetensor
+```
+
+For more information about installation, you can refer to [Installation](https://opendilab.github.io/DI-treetensor/main/tutorials/installation/index.html#).
+
+## Documentation
+
+The detailed documentation are hosted on [https://opendilab.github.io/DI-treetensor](https://opendilab.github.io/DI-treetensor/).
+
+Only english version is provided now, the chinese documentation is still under development.
+
+## Quick Start
+
+You can easily create a tree value object based on `FastTreeValue`.
+
+```python
+import os
+
+import treetensor.torch as torch
+
+if __name__ == '__main__':
+    t = torch.randn({'a': (2, 3), 'b': {'x': (3, 4)}})
+    print(t)  # tree based tensors
+
+    # some calculations
+    print('t ** 2:', t ** 2, sep=os.linesep)
+    print('torch.sin(t).cos()', torch.sin(t).cos(), sep=os.linesep)
+
+    t.requires_grad_(True)
+    t.std().arctan().backward()
+    print('grad of t:', t.grad, sep=os.linesep)  # backward
+
+```
+
+The result should be
+
+```text
+<Tensor 0x7fcb33e922b0>
+├── a --> tensor([[-0.1105, -1.0873, -1.8016],
+│                 [-1.2290,  0.1401, -2.5237]])
+└── b --> <Tensor 0x7fcb33e92370>
+    └── x --> tensor([[ 0.1579,  0.9740,  0.3076,  0.2183],
+                      [ 0.5574,  0.4028, -2.2795,  1.5523],
+                      [-0.3870, -1.1649,  0.0314, -0.2728]])
+
+t ** 2:
+<Tensor 0x7fcb33e92730>
+├── a --> tensor([[0.0122, 1.1822, 3.2456],
+│                 [1.5105, 0.0196, 6.3691]])
+└── b --> <Tensor 0x7fcb33e92610>
+    └── x --> tensor([[2.4920e-02, 9.4863e-01, 9.4633e-02, 4.7653e-02],
+                      [3.1067e-01, 1.6226e-01, 5.1961e+00, 2.4097e+00],
+                      [1.4976e-01, 1.3571e+00, 9.8400e-04, 7.4414e-02]])
+
+torch.sin(t).cos()
+<Tensor 0x7fcb33ead1c0>
+├── a --> tensor([[0.9939, 0.6330, 0.5624],
+│                 [0.5880, 0.9903, 0.8368]])
+└── b --> <Tensor 0x7fcb33ead040>
+    └── x --> tensor([[0.9877, 0.6770, 0.9545, 0.9766],
+                      [0.8633, 0.9241, 0.7254, 0.5404],
+                      [0.9296, 0.6068, 0.9995, 0.9639]])
+
+grad of t:
+<Tensor 0x7fcb33f08d60>
+├── a --> tensor([[ 0.0060, -0.0174, -0.0345],
+│                 [-0.0208,  0.0120, -0.0518]])
+└── b --> <Tensor 0x7fcb33f08dc0>
+    └── x --> tensor([[ 0.0125,  0.0320,  0.0160,  0.0139],
+                      [ 0.0220,  0.0183, -0.0460,  0.0459],
+                      [-0.0006, -0.0192,  0.0094,  0.0021]])
+```
+
+For more quick start explanation and further usage, take a look at:
+
+* [Quick Start](https://opendilab.github.io/DI-treetensor/main/tutorials/quick_start/index.html)
+
+## Contribution
+
+We appreciate all contributions to improve DI-treetensor, both logic and system designs. Please refer to CONTRIBUTING.md for more guides.
+
+And users can join our [slack communication channel](https://join.slack.com/t/opendilab/shared_invite/zt-v9tmv4fp-nUBAQEH1_Kuyu_q4plBssQ), or contact the core developer [HansBug](https://github.com/HansBug) for more detailed discussion.
+
+## License
+
+`DI-treetensor` released under the Apache 2.0 license.