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README.pcqm4mv2-3d.md

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+---
+language: []
+pretty_name: PCQM4Mv2 3D
+config_name: pcqm4mv2-3d
+dataset_size: 562677714
+size_categories: n>1M
+license: mit
+license_link: https://github.com/snap-stanford/ogb/blob/master/LICENSE
+tags:
+  - graphs
+  - molecules
+  - chemistry
+  - parquet
+  - torch-geometric
+  - ogb
+task_categories:
+  - graph-regression
+homepage: https://ogb.stanford.edu/docs/lsc/pcqm4mv2/
+---
+
+# pcqm4mv2-3d
+
+PCQM4Mv2 train split with 3D conformations aligned to OGB indices for HOMO-LUMO regression.
+
+**License:** MIT License (OGB)
+
+## Splits
+
+| Split | Rows | File | Size (MB) |
+| --- | ---: | --- | ---: |
+| train | 3,195,733 | `train.parquet` | 562.68 |
+
+## Features
+
+- **mol_id**: int64 unique identifier per molecule
+- **x**: list[int64[9]], shape (num_nodes, 9), atom feature vector
+- **edge_index**: int64[2, num_edges], COO adjacency
+- **edge_attr**: list[int64[3]], shape (num_edges, 3), bond features
+- **pos**: list[float32[3]], shape (num_nodes, 3), 3D coordinates
+- **num_nodes**: int64 number of atoms
+- **smiles**: string canonical SMILES
+- **target**: float32 HOMO-LUMO gap
+
+## Citation
+
+```
+@article{hu2021ogblsc,
+  title={OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs},
+  author={Hu, Weihua and Fey, Matthias and Ren, Hongyu and Nakata, Maho and Dong, Yuxiao and Leskovec, Jure},
+  journal={arXiv preprint arXiv:2103.09430},
+  year={2021}
+}
+```