readme: ---
  license: mit
  tags:
  - graphs
  ---
  
  # Model Card for pcqm4mv2_graphormer_base
  
  The Graphormer is a graph classification model.
  
  # Model Details
  
  ## Model Description
  
  The Graphormer is a graph Transformer model, pretrained on PCQM4M-LSCv2.
  
  
  - **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}
  }
  ```