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We’ve released Letterweave, a small AI model that identifies what an email is for, from receipts and newsletters to invitations and personal correspondence. The model and training dataset are public on Hugging Face. Try it and let us know what you think. huggingface.co/Groktopus/Le...

huggingface.coGroktopus/Letterweave-1.0-E2B · Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.

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Nice release. For email-purpose classifiers, a useful dataset card detail is whether labels are message-level or thread-level, plus how you handle multi-purpose emails like receipt + shipping update or invite + newsletter footer.

Thanks for pointing this out. I’ve updated all three model cards and both dataset cards to clarify message-level labeling and overlapping purposes, with examples showing how substantive content differs from footers and quoted history. That was a useful distinction to make explicit.

Thanks for making that explicit. The substantive-content vs quoted-history examples are especially helpful: they let users tell a labeling error from a different definition of the task.