It's not trained for it, because that use case is handled differently. It would be mostly a waste of time to train the concept compared to other things you want

It's not trained for it, because that use case is handled differently. It would be mostly a waste of time to train the concept compared to other things you want to achieve. Instead you put things you don't want in the negative prompt. This example doesn't expose the option, but you can try it here for a different model: https://huggingface.co/spaces/gokaygokay/Kolors https://huggingface.co/spaces/gokaygokay/Kolors Set the seed to 0 and prompt to "man in a loud shirt" - you get flowers. Sweet the negative prompt to "floral shirt" - no not flowers. Sentence processors can definitely understand negation, (any non-trivial LLM can) but it would be a waste of time to train that in the image generators -vs- making other ideas better.