description: <p>When combined with SD XL (sample images) results may look deep-fried. Results look better with DynaVision XL.</p><p>Most likely will not be retrained... again.</p><p>⚠Because Worms are niche and there isn't a dedicated negative model for them, expect to see flaws such as: bad hands, bad mouths, double tails, wrong number of eyebrows, 1 or no pupils and conjoined worms.</p><p>⚠The worm's face may get distorted and get human features when combined with LoRAs trained on human faces.</p><p></p><p>🖼 Trained on 53 images of Worms renders (all captioned), mainly those related to:</p><ul><li><p><em>Worms 3D</em> (caption: worms 3d render)</p></li><li><p><em>Worms Forts: Under Siege</em> (caption: worms forts under siege render)</p></li><li><p><em>Worms: Revolution / Clan Wars / Battlegrounds</em> (caption: worms g4 render)</p></li></ul><p>... so the way worms look in the dataset images have some variety. Some pictures have 2 or more worms which were confusing to tag, maybe I shouldn't have even included them 🤷‍♀️</p><p>❌ Dataset does NOT include:</p><ul><li><p>G1 material</p></li><li><p>G2 material</p></li><li><p><em>Worms Rumble</em> material</p></li><li><p>any in-game images</p></li><li><p>any fanmade models (all images are property of Team17)</p></li></ul><p>There's also a little bit of text in the images so you might want to exclude "text".</p>
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modelVersions.description: <p>This is actually a 2nd training attempt. From the test generations, it simultaneously looks raw and deep-fried (too much saturation and contrast), but the default 10 epochs I used for the 1st attempt was even more deformed. </p>
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name: (TEST) Worms Team17 render mix XL
tags: character videogame videogame character worms team17