| | --- |
| | 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 |
| |
|
| | <!-- Provide the basic links for the model. --> |
| |
|
| | - **Repository:** [Github](https://github.com/microsoft/Graphormer) |
| | - **Paper:** [Paper](https://arxiv.org/abs/2106.05234) |
| | - **Documentation:** [Link](https://graphormer.readthedocs.io/en/latest/) |
| |
|
| | # 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] |
| |
|
| | <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
| |
|
| | **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} |
| | } |
| | ``` |
