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I did mean AI's in general, so I have edited my original post. > That’s what negative prompt is for. This is what I mean by it "not understanding negations" Y
by executesorder66 2y ago
I did mean AI's in general, so I have edited my original post.
> That’s what negative prompt is for.
This is what I mean by it "not understanding negations" You need whole separate prompt, just to say you want e.g. "ramen without egg" instead of just saying it in a single prompt that it understands.
- spywaregorilla 2y agoYou are not correct. LLMs understand "ramen without egg". Image gen models generally do not as this is not how images are described. If you want to generate ramen without egg, you'll want _negative weighted_ prompts. "eating ramen, (egg:-1)"
- Dwedit 2y agoNegative weighted tokens don't do what you think they do. Sometimes they act like a negative prompt, other times they don't. Likewise, zero-weight tokens don't act like the token is absent from the prompt.
- spywaregorilla 2y agoThey generally do. It is difficult to differentiate "negative tokens don't do that" and "prompt adherence is shaky in general". It's fully possible that the image model draws eggs in ramen but it doesn't know that the egg is an egg and therefore any attempts to interact with it via the egg token are futile. Generally speaking though thing:-1 should reduce the presence of thing for well understood concepts. It's a better tool on second pass alterations of an image.
- viraptor 2y agoYou're not correct about AIs in general. Both chat LLM models and sentence embeddings can handle negation just fine. (Ask any chat "what clothes would a person wear if they weren't wearing a hat") Here it was simply not trained for that purpose. Maybe it wasn't worth it, maybe the creators thought that the negative prompt is enough, maybe the time was better spent on other examples. They way, it's not AIs in general, and it's not a tech limitation.