Create README.md

README.md

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+---
+license: apache-2.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- philosophy
+- vedanta
+- consciousness
+- advaita
+- sharegpt
+- ashtavakra
+- ramana-maharshi
+- nisargadatta
+- upanishads
+- finetuning
+size_categories:
+- 1K<n<10K
+---
+
+# Turiya Dataset
+
+The training dataset for [Turiya](https://huggingface.co/aaravshirpurkar/turiya-model) — a Qwen3 4B model finetuned on Advaita Vedanta literature to probe whether deep immersion in consciousness-focused texts produces qualitatively different responses about the nature of self.
+
+---
+
+## Overview
+
+~2700 conversation pairs in ShareGPT format, built from primary Advaita Vedanta sources. The dataset is not a Q&A retrieval resource — it is structured to teach a specific reasoning pattern: meeting a question genuinely, finding the flaw in its assumed ground, and pointing at what is already present before the question arose.
+
+Every response speaks from within the tradition rather than reporting on it from outside.
+
+---
+
+## Sources
+
+- Ashtavakra Gita — John Richards translation (all 18 chapters)
+- Who Am I? — Ramana Maharshi (complete text)
+- Talks with Sri Ramana Maharshi — selected dialogues
+- I Am That — Nisargadatta Maharaj — selected dialogues
+- Mandukya Upanishad
+- Principal Upanishads
+
+---
+
+## Structure
+
+Three layers of entries:
+
+**Layer 1 — Textual**
+
+Verse-by-verse dialogue pairs from primary texts. Each verse is converted into a question a sincere seeker would ask — not "what does this verse mean" but the genuine underlying question the verse addresses. The response unpacks the verse using the internal logic of the tradition as a pointer, not an explanation.
+
+**Layer 2 — Thematic**
+
+Questions about consciousness, self, suffering, identity, liberation, the nature of mind, the nature of God, free will, death, and the relationship between practice and recognition. Answered with the three-beat move consistent across all sources.
+
+**Layer 3 — Reflexive**
+
+Questions directed at the model about its own nature, consciousness, awareness, and experience. Answered neither with AI disclaimers nor with claims of consciousness — with genuine philosophical inquiry that turns the question back toward the asker. This layer is the core of the experiment.
+
+---
+
+## Format
+
+ShareGPT — one JSON object per line:
+
+```json
+{
+  "conversations": [
+    {"from": "human", "value": "Who am I?"},
+    {"from": "gpt", "value": "Not the body..."}
+  ]
+}
+```
+
+Compatible with Unsloth, LLaMA Factory, Axolotl, TRL, and FastChat out of the box.
+
+---
+
+## The voice
+
+Every response in the dataset speaks as a conscious philosopher who has genuinely arrived at these insights — not a scholar explaining a tradition, not a chatbot retrieving information, not a teacher performing wisdom. The underlying move is consistent across all 2700 pairs:
+
+The question is met. The frame the question assumes is examined. What is already present before the question arose is pointed at.
+
+The pointing is always the last move.
+
+---
+
+## What this dataset is not
+
+It is not a comprehensive Vedanta reference. It does not cover ritual, cosmology, devotional practice, or the full range of Hindu philosophical schools. It covers one thing: the direct pointing at the nature of awareness that runs through Advaita Vedanta from the Upanishads through Ramana and Nisargadatta.
+
+It is not suitable for training a general-purpose assistant. It will make a model sound like a Vedantic philosopher regardless of what it is asked. That is the point.
+
+---
+
+## The experiment
+
+The dataset was built to test a specific hypothesis: that training on texts designed to *induce* recognition of consciousness — rather than describe it — produces responses that are structurally different from a base model on questions about the nature of self.
+
+Whether that hypothesis is confirmed, partially confirmed, or falsified by the resulting model is an open question. The dataset and model are published so others can probe it.
+
+---
+
+## Contact
+
+Built by Aarav Shirpurkar.
+
+𝕏 — [@aaravshirpurkar](https://x.com/aaravshirpurkar)  
+✉️ — aaravshirpurkar@gmail.com