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Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material discovery, drug discovery, etc. [Project website](https://www.microsoft.com/en-us/research/project/graphormer/).
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Advanced pre-trained versions of Graphormer are available exclusively on [Azure Quantum Elements](https://quantum.microsoft.com/en-us/our-story/quantum-elements-overview).
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Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material discovery, drug discovery, etc. [Project website](https://www.microsoft.com/en-us/research/project/graphormer/).
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The model checkpoints for our paper [Predicting equilibrium distributions for molecular systems with deep learning](https://www.nature.com/articles/s42256-024-00837-3) is available under directory [Distributional-Graphormer](https://huggingface.co/microsoft/Graphormer/tree/main/Distributional-Graphormer).
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Advanced pre-trained versions of Graphormer are available exclusively on [Azure Quantum Elements](https://quantum.microsoft.com/en-us/our-story/quantum-elements-overview).
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