Update README.md

README.md

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----
-license: other
-license_name: research-only-lease-required
-license_link: LICENSE
----
+---
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - synthetic-data
+  - dpo
+  - gpqa
+  - reasoning
+  - alignment
+  - quantum
+  - neuroscience
+  - gloss-free
+  - data-efficient
+base_model: Qwen/Qwen2.5-7B-Instruct
+license: other
+language:
+  - en
+metrics:
+  - accuracy
+datasets:
+  - TrueRunAI/TrueRun-Groove-v2.1-DPO
+---
+
+# TrueRun-Groove-v2.1-7B
+
+Qwen2.5-7B-Instruct fine-tuned on ~1,200 high-rigor synthetic DPO pairs (Groove v2.1).
+
+Balanced quantum mechanics, neuroscience/BCI, alignment/game theory. Structural escalation for indefinite depth—no gloss decay.
+
+## Key Results (GPQA Diamond, 3 Seeds Mean)
+| Benchmark          | Questions | Baseline % | Groove Mean % | Delta     | Notes |
+|--------------------|-----------|------------|---------------|-----------|-------|
+| Full Diamond       | 198       | 33.33%     | 36.53%        | +3.20%    | Low variance (±0.58%) |
+| Quantum Subset     | 39        | 35.90%     | 51.92%        | +16.02%   | Leading public targeted lift for 7B |
+| Biology Subset     | 19        | 36.84%     | 52.63%        | +15.79%   | Strong transfer |
+| Physics Subset     | 86        | 51.16%     | 42.25%        | -8.91%    | Targeted regression—next iter fix |
+
+Leading data efficiency & domain-specific gains among public 7B fine-tunes.
+
+## License
+Other (non-exclusive commercial/research use—dataset for sale on OpenDataBay; model weights public for testing/reproduction).
+
+## Usage
+```python
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="TrueRunAI/TrueRun-Groove-v2.1-7B")
+pipe("Explain quantum entanglement simply but without losing rigor:", max_new_tokens=256)