metadata
license: mit
tags:
- graphs
pipeline_tag: graph-ml
Model Card for pcqm4mv1_graphormer_base
The Graphormer is a graph classification model.
Model Details
Model Description
The Graphormer is a graph Transformer model, pretrained on PCQM4M-LSC, and which got 1st place on the KDD CUP 2021 (quantum prediction track).
- Developed by: Microsoft
- Model type: Graphormer
- License: MIT
Model Sources
Uses
Direct Use
This model should be used for graph classification tasks or graph representation tasks; the most likely associated task is molecule modeling. It can either be used as such, or finetuned on downstream tasks.
Bias, Risks, and Limitations
The Graphormer model is ressource intensive for large graphs, and might lead to OOM errors.
How to Get Started with the Model
See the Graph Classification with Transformers tutorial.
Citation [optional]
BibTeX:
@article{DBLP:journals/corr/abs-2106-05234,
author = {Chengxuan Ying and
Tianle Cai and
Shengjie Luo and
Shuxin Zheng and
Guolin Ke and
Di He and
Yanming Shen and
Tie{-}Yan Liu},
title = {Do Transformers Really Perform Bad for Graph Representation?},
journal = {CoRR},
volume = {abs/2106.05234},
year = {2021},
url = {https://arxiv.org/abs/2106.05234},
eprinttype = {arXiv},
eprint = {2106.05234},
timestamp = {Tue, 15 Jun 2021 16:35:15 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2106-05234.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}