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How many proper open-source LLMs are there?
(palaver.p3x.de)
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this post was submitted on 01 Sep 2026
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It would allow users to audit the dataset for ethical concerns, to interrogate the set to understand what a model does and does not "know", to identify weaknesses and biases, and to ensure that nothing has been inserted specifically to engineer prompt responses. Just examples off the top of my head.
Knowledge should be relatively impossible, though, if you just get the names and hashsums of the files? I mean I guess you could look up if a specific file you already have is in it. Might have some application. It needs to be very detailed, though. If they just call it GitHub-dump-timestamp or Wikipedia-dump-2026 with some overall hash, that doesn't tell us anything.
Most resources have a URI, Universal Resource Identifier. Related to a URL, except that it doesn't necessarily tell you how to locate the resource it identifies, URIs have dozens of schemas (eg isbn: for books) that can identify virtually any kind of media. Ideally they would tell us the URI, all metadata, source/provenance/licensing information, and the hash of the resource. If they truly are training on anonymous unattributed blobs that they just mysteriously found in their dataset, well that would be interesting to learn.