Again, this (and my other text generation projects) are optimizing more for humor/chaos than accuracy, and there is a bolded important notice before the text em

Again, this (and my other text generation projects) are optimizing more for humor/chaos than accuracy, and there is a bolded important notice before the text emphasizing that the results may not be legal. Per the other comments on that Reddit thread, that appears to be the correct approach as the crazier-but-barely-legal cards are what resonate the best (the "bad" RoboRosewater cards were the most popular, not the good ones). Curating only cards which are grammatically good is in itself misleading. Part of the reason I work on text generation in the first place is to illustrate its limitations. I encourage you to run the notebook itself instead of arguing a No True Scotsman about something I never tried to assert. This notebook is not a thesis paper, just a side project about a ML model that took more time to train than to write the code for.