Add model card and metadata

Hi there! I'm Niels, part of the community science team at Hugging Face.

I've opened this PR to improve the model card for PatchAlign3D. This includes adding metadata such as the pipeline tag, linking the paper, project page, and GitHub repository, and providing a sample usage snippet for inference derived from the official code.

Please feel free to merge if this looks good to you!

README.md

@@ -1,3 +1,37 @@
----
-license: mit
----
+---
+license: mit
+pipeline_tag: other
+---
+
+# PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding
+
+PatchAlign3D is an encoder-only 3D model that produces language-aligned patch-level features directly from point clouds. It enables zero-shot 3D part segmentation with fast single-pass inference without requiring test-time multi-view rendering.
+
+- **Paper:** [PatchAlign3D: Local Feature Alignment for Dense 3D Shape understanding](https://huggingface.co/papers/2601.02457)
+- **Project Page:** [https://souhail-hadgi.github.io/patchalign3dsite](https://souhail-hadgi.github.io/patchalign3dsite)
+- **Repository:** [https://github.com/souhail-hadgi/PatchAlign3D](https://github.com/souhail-hadgi/PatchAlign3D)
+
+## Sample Usage
+
+You can run inference on a single shape and save per-point predictions using the following command from the official repository:
+
+```bash
+python patchalign3d/inference/infer.py \
+  --ckpt /path/to/stage2_last.pt \
+  --input /path/to/shape.npz \
+  --labels "seat,back,leg,arm"
+```
+
+## Citation
+
+```bibtex
+@misc{hadgi2026patchalign3dlocalfeaturealignment,
+  title={PatchAlign3D: Local Feature Alignment for Dense 3D Shape understanding},
+  author={Souhail Hadgi and Bingchen Gong and Ramana Sundararaman and Emery Pierson and Lei Li and Peter Wonka and Maks Ovsjanikov},
+  year={2026},
+  eprint={2601.02457},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV},
+  url={https://arxiv.org/abs/2601.02457},
+}
+```