Ok, so for those you were keen for the latest Nostr spam ML models and training data, I've updated the GitHub repo. 92k examples with 13k labelled as spam. Sits around 98% accuracy - in practise I’ve found it eliminates all effective spam for kinds 1/42.

I still review high scoring non-spam, but under 90% to help expand the training set.

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