Comment by andy12_
15 hours ago
You can achieve open-vocabulary classification by making the final weights in the softmax come from a category encoder instead of being fixed learned weights. So instead of
softmax(encode(input)*learned_weights)
You have
softmax(encode(input)*encode(categories))
I'm not sure if Jev does it this way, but it's how you get open-vocabulary zero-shot image classification with models like CLIP [1].
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