This project implements a least likely next token predictor using reinforcement learning. It leverages a pre-trained language model (GPT-2) to estimate token probabilities and trains a second model to predict tokens with the lowest probabilities, making it the "apex predator" of unlikely token predictors.
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This is cool. Sometimes me and my kids will play a game of trying to create a short sentence that we feel has never been said before in history (ie. Dinner will be pretzels served on a Frisbee with electric eel sauce)
This should be a way to model those sentences.