One of the demos I've delivered for my $MEGACORP$ is showing how to fine-tune large scale language models to generate text on our service. The demo I used was t

One of the demos I've delivered for my $MEGACORP$ is showing how to fine-tune large scale language models to generate text on our service. The demo I used was to create a "Plato" model by fine-tuning GPT-2 on his text "Timaeus", followed by a "Stirner" model trained on his work "The Unique and its Property". I finish the demo by training "Chimera" models, first a model trained by concatenating the texts together, and then another trained on weaving the lines of each book together, paragraph by paragraph. I find the results of a "Chimera" model far more fascinating. I can arbitrarily combine the texts of a set of philosophers, and get something hopefully which is totally different - something which is hopefully more than the sum of its parts...