Model is runned on dataset WikiText2 to showcase the learning methods as graph. In only few minutes model managed to: Lower perplexity for 10k, stay with enthropy tokens, minimise drastically halucinations without any RAG, use token similarity in Semantic Graph and guess multiple times what is coming before it sees the ground truth from dataset.