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by petercooper 136 days ago
One possible trick could be to search and replace them all with nonsense alternatives then see if it extracts those.
2 comments

That might actually boost performance since attention pays attention to stuff that stands out. If I make a typo, the models often hyperfixate on it.
A fine instruction following task but if harry potter is in the weights of the neural net, it's going to mix some of the real ones with the alternates.