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README.md

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Original PyTorch implementation of [GraphAny].
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Authored by [Jianan Zhao], [Hesham Mostafa], [Michael Galkin], [Michael Bronstein],
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Authored by [Jianan Zhao], [Hesham Mostafa], [Mikhail Galkin], [Michael Bronstein],
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[Zhaocheng Zhu], and [Jian Tang].
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[Jianan Zhao]: https://andyjzhao.github.io/
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[Hesham Mostafa]: https://www.linkedin.com/in/hesham-mostafa-79ba93237
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[Zhaocheng Zhu]: https://kiddozhu.github.io
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[Michael Galkin]: https://migalkin.github.io/
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[Mikhail Galkin]: https://migalkin.github.io/
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[Michael Bronstein]: https://www.cs.ox.ac.uk/people/michael.bronstein/
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[Jian Tang]: https://jian-tang.com/
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[GraphAny]: https://github.com/AndyJZhao/GraphAny
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Links to be updated later.
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## Overview ##
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![Foundation Model on Node Classification](assets/fm_on_node_classification.png)
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choose to use our provided datasets, you can skip this step and proceed directly to
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Step 3.
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**Step 3**: Inference using pre-trained model using command:
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**Step 3**: Run inference with pre-trained model using command:
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```bash
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python graphany/run.py prev_ckpt=checkpoints/graph_any_arxiv.pt total_steps=0 dataset=CoraCiteInference
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```bibtex
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@article{zhao2024graphany,
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title={GraphAny: A Foundation Model for Node Classification on Any Graph},
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author={Jianan Zhao and Hesham Mostafa and Michael Galkin and Michael Bronstein and Zhaocheng Zhu and Jian Tang},
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author={Jianan Zhao and Hesham Mostafa and Mikhail Galkin and Michael Bronstein and Zhaocheng Zhu and Jian Tang},
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year={2024},
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eprint={2405.20445},
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archivePrefix={arXiv},

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