Update README.md

README.md

@@ -8,11 +8,11 @@ Used 'fast-DreamBooth' on Google Colab and 768x768 images for all versions.
 
 I don't recommend using V1, but i've included it anyways.
 
-V1: Trained with around 1300 images (from danbooru), automatically cropped.__
-V2: Trained with 400 handpicked and handcropped images, and for the number of steps each model indicates in its name (for example, 'sketchstyle_v2-16000-2500txt_enc.ckpt' is trained for 16k steps, and 2500 steps for the text encoder).__
-V3: Trained with the same images as V2, but with 5000 steps and text encoder trained with 1000 steps, with 'style training' enabled. This version will continue to be trained on.__
+V1: Trained with around 1300 images (from danbooru), automatically cropped.<br />
+V2: Trained with 400 handpicked and handcropped images, and for the number of steps each model indicates in its name (for example, 'sketchstyle_v2-16000-2500txt_enc.ckpt' is trained for 16k steps, and 2500 steps for the text encoder).<br />
+V3: Trained with the same images as V2, but with 5000 steps and text encoder trained with 1000 steps, with 'style training' enabled. This version will continue to be trained on.<br />
 
-Lots of images include visible nipples so, in case you don't want nsfw images, include nsfw/nipples on the negative prompts.
+Lots of images include visible nipples so, in case you don't want nsfw images, include nsfw/nipples on the negative prompts.<br />
 Also, breasts tend to be large/huge so for anything smaller than that, use medium/small breasts on the prompts and large/huge breasts on the negative prompts, and skin tone tends to be 'tan' because of the same reason,
 so including tan/dark skin on the negative prompts and pale skin on the prompts will help to get whiter tones, though good anatomy gets affected.
 
@@ -20,7 +20,7 @@ Token: 'sketchstyle' (depending on the model downloaded, you might have to use i
 
 The closer you are to 768x768, the better, but you can get good results in any resolution.
 
-This model works specially good when changing the style of another image, so you could generate images with another model that you know works well with anatomy and such, and then use this model to change its style (examples below).
+This model works specially good when changing the style of another image, so you could generate images with another model that you know works well with anatomy and such, and then use this model to change its style (examples below).<br />
 I recommend, if using V2, to use the 10k steps version as it has the least anatomy errors, and use the 16k steps version when doing img2img.
 
 # Comparison between different versions and models