microsoft/multi-fidelity-training-mlff

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The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at da01343
Licence files: No licence file at the top level of the repositoryEvidence: file list at da01343
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Citation text from the card

@online{Gardner2025Understanding,
  title = {Understanding Multi-Fidelity Training of Machine-Learned Force-Fields},
  author = {Gardner, John L. A. and Schulz, Hannes and Helie, Jean and Sun, Lixin and Simm, Gregor N. C.},
  date = {2025-06-17},
  eprint = {2506.14963},
  eprinttype = {arXiv},
  eprintclass = {physics},
  doi = {10.48550/arXiv.2506.14963},
  url = {http://arxiv.org/abs/2506.14963}
}

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dataset_licence({ "id": "microsoft/multi-fidelity-training-mlff" })
signal: "permissive"
stated_licence: "mit"
sources: 0