Corrected N=2580 result
- Full-Spec adherence / robustness: 0.933 / 0.933 (28/30)
- Exact GATE line: 30/30
- Thinking dumps: 0/30
- Remaining misses:
e11, e14 watch over-calls
- Adapter revision:
784a90897112cd94effb2da39f2fc151f55468ae
- Training evidence: repository commit
7bab0c5, results/training/n2580/
This is below the declared 0.95 bar and is not a threshold pass.
Exact inference
The adapter was trained against the listed bitsandbytes 4-bit base. Exact adapter evaluation requires CUDA. Applying the LoRA weights to upstream full-precision Qwen on CPU/MPS changes outputs and is non-comparable.
python eval.py \
--model lecporr/rotating-equip-sft \
--revision 784a90897112cd94effb2da39f2fc151f55468ae \
--eval-set data/eval.jsonl \
--device cuda
A merged 16-bit checkpoint is required for portable CPU/MPS one-command inference; see notebooks/COLAB_MERGE.md.
Limitations
Synthetic snapshots only. This model is not a physical diagnostic authority or safety controller. The 30-row public eval is small; staff-held-out evaluation remains required.