D1A-E2B

D1A is a small open decision model in the Jev style: one document and a set of typed questions in, a calibrated probability for every option out, in one forward pass, with no text generation. It speaks the same System One API as Jev, so the TypeSafe SDK works against it unchanged.

This checkpoint is a LoRA adapter plus a pointer head on google/gemma-4-E2B (revision d29ff6b4), trained for two epochs and calibrated with a temperature of 1.52.

	D1A-E2B (this checkpoint, 2 epochs)	v0.1 (1 epoch)	Jev (TypeSafe, hosted)
Accuracy, trained sources (dev)	0.824	0.794	0.845
Accuracy, new sources (dev)	0.602	0.569	0.857
Log loss (dev)	0.499	0.522
Calibration error, ECE (dev)	0.057	0.040
Where it runs	your machine (Apple GPU / NVIDIA), free, private		TypeSafe's cloud API

Measured on the same frozen evaluation sets (development partitions; the locked test was not read). Jev is more accurate today. The second epoch gained 3 points on both sets at a slightly higher calibration error. Tag v0.1-1epoch keeps the previous version; the Apple Silicon build JohnP1/d1a-e2b-mlx-q8 is still made from v0.1.

• Playground (nine live use cases): https://github.com/jonpol01/d1a-playground
• Code: https://github.com/jonpol01/d1a

Serve it

pip install "d1a[serve] @ git+https://github.com/jonpol01/d1a"
python -m d1a.serve --run JohnP1/d1a-e2b --port 8009

License

Apache-2.0. Base model: Gemma 4 by Google (Apache-2.0). Training and serving code: github.com/jonpol01/d1a, built on Kev by Jared Palmer (Apache-2.0).