<h1 id="heading-69">Flabbergast </h1><h3 id="heading-70">the real one</h3><p><br />This is a realistic version of the Flabbergast checkpoint. It’s a merge in the first place, with some trained content (9744 steps). This had a whole bunch of amateur content added, but I’m not sure how much is left after a couple of merges.</p><p></p><p>It’s as ugly as the comic version. So limbs all over the place and constantly a finger in your eye! Can do a little bit of everything.</p><p><br />Don’t take it too seriously, there are so many SD 1.5 based checkpoints these days, that it’s hard to keep an overview.</p><p><br />The focus was mainly on creating realistic content without complicated and overbearing prompts while keeping a bit of the quirkiness of my comic model in place.</p><p>I’m lazy and I don’t want to write a whole list of prompts to get something. I also don’t really care for perfection that much, so if you want something extremely polished, this is probably not the right one for you. It might take a few tries to get the desired output.</p><p><br />It’s not glamorous, when you prompt for dirty, you get dirty!</p><p></p><p>Recommended settings are the same as my comic model:</p><p></p><h3 id="heading-71">CFG Scale:</h3><p>up to 7 worked well in my tests but stay below 10!</p><p><br /></p><h3 id="heading-72">Sampler:</h3><p><strong>DPM++ SDE Karras</strong> or <strong>DPM++ 2M SDE Exponential</strong> worked quite well. The Exponential one is adding more contrast to the images. Euler and Euler a work fine.</p><p>Stay away from LMS, which produced artifacts I my tests. DPM++ 2M SDE Heun, DPM++ 3M SDE Karras and PLMS were just bad. DPM fast was really horrific but DPM adaptive worked nicely.</p><p>Take a look at <strong>UniPC </strong>if your setup supports it. Nice results and very fast with a small number of steps. Already gets something done in 5 steps, but picks up the quality in the 10-15 steps range.</p><p><br /></p><h3 id="heading-73">Prompts:</h3><p>Not much needed, you can keep it simple</p>

Files with SHA256: 9bc61b338d459a7d1b1bf7787c313efb5634ff1590f1e5f9093131b275f9d267