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  "path": "/t/c-inf-soft-sparsity-engine-maths-and-code-from-1972/176964#post_8",
  "publishedAt": "2026-06-21T01:15:20.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "Ah, I see. In that case, I think a Model repo is fine.\n\nMore generally, my impression is that if the files are AI/ML-related, putting them somewhere on the Hub is usually reasonable. The difference between repo types is mostly about convenience and tooling, not strict correctness.\n\nFor example, a Dataset repo may give you dataset-related features, a Space is better for a demo, and a Bucket may be better for fast / temporary / mutable storage.\n\nFor this case, a Model repo sounds reasonable if you want to present it as an ML-facing computational artifact.\n\nThe main thing I would suggest is making the `README.md` clear. The YAML block at the top can handle repo metadata / categorization, and after that it is just normal Markdown explanation. If the README explains what the repo contains and how to use it, users will have a much easier time understanding and reusing it.\n\nOf course, many useful Hub repos have minimal README files too, so this is not a hard requirement. It would just be helpful for this kind of historical / mathematical code.",
  "title": "C-inf soft sparsity engine maths and code from 1972"
}