The problem is that those embeddings that we produce again, they're trained with this contrast of loss. So when we train with the contrast of loss it's good for that sort of retrieval stuff. But then the promise again those those representations may not necessarily match a regular clip image embedding. Again, it's useful for doing the sort of call sign similarity, getting similarities to existing embeddings, but they match those sort of existing embedDings directly.

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