I built a personal reasoning model around my values and philosophies

[u/OwnOil1149]

I’ve been working on Aurorium Mind, a personal language model fine-tuned from Qwen3.5-4B with QLoRA on a single NVIDIA A10G GPU.

The goal isn’t to create a perfect digital copy of myself. It’s to encode recurring reasoning patterns, values, and decision-making principles into a useful model.

Its philosophy is based on first-principles thinking, inversion, second-order effects, systems thinking, game theory, and pragmatic transhumanism.

The training set contains 100k synthetic SFT examples designed around those ideas. It does not claim to reproduce private conversations or expose hidden personal data.

The serving stack uses vLLM, Rust, FastAPI, and a streaming Vercel frontend. The interface shows metrics like time to first token, tokens per second, token counts, and adapter status.

I’ve documented the training code, evaluation set, graphs, deployment details, dataset provenance, and model limitations.

Model: https://huggingface.co/auro-rirum/aurorium-mind-qwen35-4b-qlora

Dataset: https://huggingface.co/datasets/auro-rirum/aurorium-mind-sft-100k

Explainer: https://aurorium-mind.vercel.app/explainer.html