Update README.md

README.md

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 license: openrail
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-ITRobo2022 model. Trained on SD 1.5.
+<h1>ITRobo2022 model. Trained on SD 1.5.</h1>
 
 I really like the Robo-Diffusion model (https://huggingface.co/nousr/robo-diffusion), but most of what you can get with it is robot heads. :)
 In my model I tried to emphasize full-length images of robots. I also get good results on a homogeneous background, which makes it easier to cut out objects for further work.
 However, good results are also obtained with mixed queries. Try it. Good luck!
 
-!!! Use this token at the beginning of the prompt: 'itrobo2022'
-
-Example:
-
-Prompt: ITRobo2022 (a full body photo of pug)+, isolated, high resolution photo, cinematic lighting, trending on artstation, DOF, high resolution, 4 k, 8 k, solid background
-
-Negative prompt: (duplicate)+++, deformed, no leg, blurry, no head, headless, watermarks, writings, text, marks, ugly, a lot of fingers, mutation, too many legs
+!!! Use this token at the beginning of the prompt: <b>itrobo2022</b><br><br>
+<b>itrobo2022.ckpt</b> - base trained model. It's a little hard to control the result, but good for generating a variety of robots, and for working with img2img.<br>
+<b>itrobo2022-40-with-v1-5-pruned-emaonly-60.ckpt</b> - 40% mixed with base SD1.5. Better manageability and control of results.
 
+<b>Example:<b><br>
+Prompt: <i>ITRobo2022 (a full body photo of pug)+, isolated, high resolution photo, cinematic lighting, trending on artstation, DOF, high resolution, 4 k, 8 k, solid background</i><br>
+Negative prompt: <i>(duplicate)+++, deformed, no leg, blurry, no head, headless, watermarks, writings, text, marks, ugly, a lot of fingers, mutation, too many legs</i><br>
 ![2022-12-16-22-03-57-1-289133679-ddim-itrobo2022-30-with-v.png](https://s3.amazonaws.com/moonup/production/uploads/1671430421748-630c71f215433862cfc241a9.png)
 
-itrobo2022.ckpt - trained model. Difficult to control, but good for generating a variety of robots, and for working with img2img.
-itrobo2022-40-with-v1-5-pruned-emaonly-60.ckpt - 40% mixed with base SD1.5. Better manageability and control of results.
-
 Best results on:
 DDIM
 steps:20