Add readme

README.md

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+[![test](https://github.com/takuseno/tensor-bridge/actions/workflows/test.yaml/badge.svg)](https://github.com/takuseno/tensor-bridge/actions/workflows/test.yaml)
+
+# tensor-bridge
+`tensor-bridge` is a light-weight library that achieves inter-library tensor transfer by native `cudaMemcpy` call for minimal overheads.
+
+```py
+import torch
+import jax
+from tensor_bridge import copy_tensor
+
+
+# PyTorch tensor
+torch_data = torch.rand(2, 3, 4, device="cuda:0")
+
+# Jax tensor
+jax_data = jax.random.uniform(jax.random.key(123), shape=(2, 3, 4))
+
+# Copy PyTorch tensor to Jax tensor
+copy_tensor(torch_data, jax_data)
+
+# And, other way around
+copy_tensor(jax_data, torch_data)
+```
+
+## Supported deep learning libraries
+- PyTorch
+- Jax
+
+
+## Installation
+Your macine needs to install `nvcc` to compile a native code.
+```
+pip install git+https://github.com/takuseno/tensor-bridge
+```
+Pre-built package release is in progress.
+
+
+## Unit test
+You machine needs to install NVIDIA's GPU and nvidia-driver to execute tests.
+```
+./bin/build-docker
+./bin/test
+```