i post-trained a model to reliably roll a die

A model was post-trained to reliably generate random outputs, specifically simulating a die roll with each of the six numbers appearing approximately 1/6 of the time. This approach addresses the challenge of encouraging exploration in reinforcement learning (RL) rather than relying on known strategies, highlighting a potential avenue for improving model behavior in stochastic tasks. The findings and methodologies are documented in a blog post linked in the discussion.