Comments (2)
Can the same training recipe of CoCoOp or CoOp be used by training all examples of the base classes
The key advantage of those methods is that they are data-efficient (i.e. with only a few shots the model can be adapted to a new task). Certainly you can use all data for tuning.
Data/parameter-efficient fine-tuning (or transfer learning) is more appealing than full-data fine-tuning (the latter has been commonly used) when it comes to adapting large vision foundation models like CLIP
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I got the point. Thank you for your response.
kind regards.
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Related Issues (20)
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