3 ms·
You 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 ra
by spywaregorilla 2y ago
You 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.