CyrilPKU/CrystalREPA-Models

AI model by CyrilPKU

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Pretrained checkpoints for CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models. Accepted at NeurIPS 2026. Paper · Code · Data CrystalREPA aligns atom-wise representations of crystal generative models with those of frozen machine-learning interatomic potentials (MLIPs), using an element-aware contrastive objective (EA-NCE). This release provides one MatterGen baseline and ten CrystalREPA models trained on MP-20. Sampling requires neither the teacher models nor their cached representations. Install the environment following the code repository. Run the following commands from its root directory. Download the model trained with DPA-3.1-3M as the teacher: Generate 1,024 crystals: Outputs include EXTXYZ structures and a ZIP archive of CIF files. For a quick trial, set --numbatches=1. Sampling does not require downloading the training dataset. If GPU memory is limited, reduce the batch size and increase the number of batches to preserve the total sample count. All checkpoints correspond to epoch 1899, after 1,900 training…

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CyrilPKU/CrystalREPA-Models is a task-unspecified model repository published by CyrilPKU on Hugging Face. A library was not reported.

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Task: Not reported
Library: Not reported
Recent downloads (30 days): 0
Cumulative likes: 0
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Architecture: Not reported
License: mit
Access: Not gated by Hugging Face
Created: 2026-10-26T06:04:08.000Z
Last modified: 2026-10-26T06:20:15.000Z

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