Generate thick painting style images similar to wlop.Trying to keep the original author's style

This version is the V2, the V1 link: https://huggingface.co/hhyxnh/WLOP-style_stable_diffusion

中文社区链接 Chinese link：https://bbs.cgkit.cn/forum.php?mod=viewthread&tid=8593&page=1#pid51146

Detailed description is in the huggingface.

below I will briefly describe the features of this version

1. 768 resolution is used for training, V1 is 512 ,so V2 will create more details. In v2 ,If the resolution settings is too small(below 768*768), the results will not be great.

2. Maybe due to the influence of training set,in V2, the logic of text2img is poor than V1. If you want to use text2img , you can try the V1, or use text2img then use img2img to improve quality

3. this model focuses on the generation of portraits. I have not trained for grand scenes. Too many elements are easy to cause training mismatch.

I will give a typical parameter. The quality in img2img will be good

***Too low resolution settings will affect the generation of head details. If you want to generate a bust,please set higher resolution .

Style word: wgz style

typical parameters;

Prompt :wgz style,portrait of a beautiful women highly detailed,perfect femine face,Classical oil painting,by masamune shirow, by William-tae Kim

Negative prompt: old,men,two poeple,Three dimensional facial features,deep shadows on the five senses,tall nose,Eye shadow,[High bridge], [narrow nose],Deep orbital fossa

Steps: 20, Sampler: DPM++ 2S a Karras, CFG scale: 9.5, Denoising strength: 0.51, Mask blur: 4

I hope you guys enjoy this model and create works that satisfied

If you have any doubts or want to communicate, you can contact me,welcome

PS:I try hard to achieve the painting style I want by using stable diffusion. I have tried a lot, with failures and successes. With my current technology, I can hardly find progress now. So this model will not be updated in a short time. If you have ideas or want to improve together, you can contact me,happy new year guys.

Telegram: https://t.me/hhhyxnh

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