Or are you looking at some very specific definition / threshold for fine tuning here?
Or are you looking at some very specific definition / threshold for fine tuning here?
I'd describe them like "a bike with no handlebars" because they are incredibly difficult to steer to where you want.
For example if you look at the preview images like this one: https://civitai.com/images/3615715
The model seems to have completely ignored a good 35% of the text input, most egregiously I find the (flat chest:2.0), the parenthesis denoting a strengthening of that specific part of the prompt. The values I see people use with good general models range from 1.05~1.15. 2.0 in comparison is an extremely large value, that ended up _still not working at all_, if you take a look at the actual image.
> most egregiously I find the (flat chest:2.0)
The flat chest is fighting to compensate the also heavily weighted (hands on breasts:1.5) which not only affects hand placement but also the concept of "breasts", and the biases trained into many of the community models with that term mean that having that concept in the prompt and heavily weighted takes a lot to counteract. So, no, I don't think its ignoring that.
When I use a decent paid service, pretty much every prompt gives me a good response out of the box. Which is good, because otherwise I'd have no use for paid services, since I can run it all locally. This causes me to go to a paid service whenever I want something quick, but don't need full control. When I do want full control, I stick to my local solution, but that takes a lot more time.