Update README.md

README.md

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 license: mit
+metrics:
+- accuracy
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+
+# OpenShape Inference Library
+
+## Installation
+
+First, you have to install a recent version of [torch](//pytorch.org/get-started/locally/) and [dgl](//www.dgl.ai/pages/start.html).
+
+Then install the following extra dependencies:
+```bash
+pip install torch.redstone einops huggingface_hub
+```
+
+Finally, install OpenShape by cloning the repository and running
+```bash
+pip install -e .
+```
+
+## Usage
+
+### Loading an OpenShape model
+
+```python
+import openshape
+pc_encoder = openshape.load_pc_encoder('openshape-pointbert-vitg14-rgb')
+
+# Available models:
+# openshape-pointbert-vitb32-rgb, trained against CLIP ViT-B/32
+# openshape-pointbert-vitl14-rgb, trained against CLIP ViT-L/14
+# openshape-pointbert-vitg14-rgb, trained against OpenCLIP ViT-bigG/14 (main model in paper)
+```
+
+Models accept point clouds of shape [B, 6, N] (XYZ-RGB) and trained with N = 10000.
+
+Point clouds should be centered at centroid and normalized into the unit ball, and RGB values should have range [0, 1].
+If you don't have RGB available in your point cloud, fill with [0.4, 0.4, 0.4].
+
+**Note:** B/32 and L/14 models has gravity axis Y; G/14 model has gravity axis Z.
+
+### Applications
+
+Various downstream applications can be found in the demo directory.
+Check the code at https://huggingface.co/spaces/OpenShape/openshape-demo/tree/main for usage.