ara-diac-plane-1.0

Part of the Secryst phonological-layer family — a dedicated model for diacritization (AR), distributed as a Secryst IMF artifact and loadable through any Secryst crystal:

from secryst import Model
Model.load("ara-diac-plane-1.0")

• Artifact: ara-diac-plane-1.0.zip (0.20 GiB)

Measured quality

Full evaluation sets, zero skipped examples, the benchmark's own evaluator. Provenance for every number is the results record of the training project.

metric	value	provenance
der_total_greedy	3.5905	interscript/interscript-ml docs/RESULTS.md#run-018-plane-v2
der_morph_greedy	2.2149	interscript/interscript-ml docs/RESULTS.md#run-018-plane-v2

Benchmark

Full-set SadeedDiac-25 — 1,200 paragraphs, zero skipped, greedy decode (protocol-matched, Misraj's evaluator):

model	Total DER	notes
ara-diac-2.0 (teacher, 580M seq2seq)	2.29%	best dedicated
ara-diac-plane-1.0 (this model)	3.59%	219 MB int8
ara-diac-small-2.1 (seq2seq student)	4.57%	491 MB int8

On-device frontier on all three axes: -45% size and -67% CPU latency (~1,145 ms/window vs ~3,459 ms) against the shipped seq2seq int8 student, at 0.98pp better DER.

Architecture

Plane-factorized diacritization: a ByT5-small-class byte-level encoder (no decoder) with a diacritic-plane embedding; one classification head predicts a haraqat class per character position over 54 classes. Decoding is K=2 mask-predict passes — parallel forwards with the predicted plane fed back as input; no KV cache, no autoregressive loop. Skeleton round-trip is byte-exact (plane marks close into the preceding base letter; leading marks are preserved via a pre-marker).

The artifact is a single self-contained int8 ONNX graph in the plane zip contract (metadata.yaml with member sha256s + plane.onnx + classes.json), loadable by secryst-py PlaneModel.from_zip. The canonical distribution is the Secryst IMF artifact (sha256-verified); this repository mirrors those exact bytes.

Provenance: rababa run-018 — 551k unique units, 2 epochs, checkpoint sha256 26f49bd0ebbf3ca93cebf2f36bdd8b488f6bb17e99e3f61f9613e53d1852862.

License

BSD-3-CLAUSE

Provenance

Trained in the Secryst training monorepo and published through the interscript-ml distribution contract (models.yaml index, sha256-verified release assets, parity-gated artifacts). The canonical download channel is GitHub Releases; this repository is the Hugging Face mirror of the same bytes, pinned to the index revision.