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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}
}
```
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