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

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)