source/README.md

NanoJev Core ML conversion

This toolkit targets the current unified-games NanoJev checkpoint at the immutable revision in assets.lock.json. It uses the trained best.safetensors, the bundled tokenizer and backbone configuration, and the original DecisionModel source. The current release differs from older NanoJev snapshots, so this package must not be presented as a reproduction of the tracker’s 26.19 result until the evaluated historical checkpoint is identified.

NanoJev encodes one path per candidate with Qwen3, then runs a trained scalar head. Choice requests additionally run an attention head over the whole candidate set. export_model.py preserves that set operation and the separate Boolean/Score behavior. The conversion writes one shared candidate-encoder package and one small head package, rather than replicating the 0.6B backbone for every question type.

uv sync --frozen
HF_HUB_DISABLE_XET=1 uv run python convert-coreml.py --length 128 --candidates 4 --parity-only
HF_HUB_DISABLE_XET=1 uv run python convert-coreml.py --length 128 --candidates 4
HF_HUB_DISABLE_XET=1 uv run python verify.py --length 128 --candidates 4

The L128/K4 bucket accepts one question per call. Native rendering rejects rather than truncates requests longer than 128 tokens. Larger lengths and candidate counts need separate exports and validation. assets.py allowlists files, disables remote model code, checks the full checkpoint hash, and loads all trained parameters strictly. All generated packages stay in ignored build/.

The upstream code includes an MIT license. The model card says this covers source code, but does not state a license for the trained checkpoint. Do not redistribute Core ML weights until the model owner grants or clarifies weight redistribution. The Qwen base retains its upstream license. Local conversion and parity checks are allowed; public model weights are held at this gate.