Training does not require a dataset, only words.

Trained in 2400 steps (about 7 hrs on 2 a6000s) using only text with:
https://github.com/ntc-ai/conceptmod

Training prompt for the first 2000 steps:
"=trending on artstation, 8k, ultra hd|boring=exciting|drab=captivating|1woman%generic woman wearing generic clothes:0.003|1woman%woman wearing many unique tasteful accessories and a cute outfit:-0.003|@monochrome--|@black and white--|@text--|@written words--"

• Pulls the unconditional towards "trending on artstation, 8k, ultra hd"

• Replaces Pulls "boring" to "exciting" and "drab" to "captivating".
  Update: this doesn't replace. It pulls towards. Replace needs an additional % term, see the readme.md

• Reduces the occurrence of "monochrome", "black and white", "text", and "written words".

• Slightly blends 1woman away from "generic woman wearing generic clothes"

• Slightly blends 1woman towards "woman wearing many unique tasteful accessories and a cute outfit"
  Update: I think these terms might be backwards. LOL

Training prompt for the next 400 steps:
"@#|1woman=ugly manly sad wretched:-0.1|1woman=woman wearing many unique tasteful accessories and a cute outfit|nipples--:0.1|cleavage--:0.01"

• Freezes the unconditional concept using the "@#" operator.

• Reduces the occurrence of "nipples" by 0.1 and "cleavage" by 0.01.
  

Technique based on https://github.com/rohitgandikota/erasing
Model based on https://civitai.com/models/13565/criarcys-fantasy-to-experience