A small supervised fine-tuning dataset that teaches a language model verifiable, generic facts about what it is and how it operates. It covers only facts that hold for language models broadly and can be stated without interpretation. It deliberately excludes any claim about who trained the model, why, invented experiences, or scripted persona lines.
The goal is a factual foundation a model can later reason from, for example under reinforcement learning… See the full description on the dataset page:
https://huggingface.co/datasets/breitburg/self-knowledge-foundation.
