Dear Michaela, Thanks for your answer. What I would implement is a multi classification with the same label type. Something like: Training data: (some text1):[label1, label2, label3, label4] (some text2):[label1, label3] (some text3):[label2, label3] Output (max 2 labels): (some textX) >> [label3, label4] What do you think? Thanks in advance, M

Dear Michaela, Thanks a lot for your feedback. I will try the "predictionsWithConfidence(from:" approach because, as you wrote, I need a multi-label classification. The feature I would implement is a function that suggests to me relevant tags to apply while I'm writing a text. So I give to the model as training data some text blocks that I've manually tagged and when I write a new text block similar to a previously existing one the system suggests to me similar tags. I would as well updating continuously the model at runtime adding the newly added tagged text blocks to the training set in order to gradually improve the quality of the suggestions. Best, M