update readme

README.md

@@ -22,4 +22,10 @@ Training set includes screenshots of groups of characters, and compared to prior
 
 The model does not turn everything into a final fantasy video game.  "photo of tom cruise" does not look like a video game, or like any character in the training set, but, if you generate "tom cruise on the rooftops of the midgar city slums" it will generate a video-game render like image.  Likewise, "photo of wall street, nyc" will not look like a video game unless also prompted as "photo of wall street, nyc, in the style of midgar city."  While there is visible "damage" to the original model, it has lost minimal subjective qualities, unlike other fine tuned models, for instance, those tuned very extensively to produce "anime style" images that lose the ability to generate content you would expect from the original source 1.4 checkpoint. 
 
-This is a step away from textual inversion and dreambooth and towards full fine tuning.  Further research will be undergone to replace regularization with images sourced from the original laion dataset.
+This is a step away from textual inversion and dreambooth and towards full fine tuning.  Further research will be undergone to replace regularization with images sourced from the original laion dataset.
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+Supplementary information here: https://gist.github.com/victorchall/67bc53472f86641aef1ebee1e154f5d1
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+My "group" regularization set here: https://github.com/victorchall/dreambooth-group-regularization
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+The group set is meant to mirror the sort of content in the group training set, and was generated with a few different captions.