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README.md

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+---
+license: bsd-3-clause
+language: ar
+inference: false
+tags:
+  - secryst
+  - transliteration
+  - diacritization
+  - onnx
+  - byt5
+---
+
+# ara-diac-2.0
+
+Part of the [Secryst](https://secryst.github.io) phonological-layer family — a dedicated model for **diacritization** (AR), distributed as a Secryst IMF artifact and loadable through any Secryst crystal:
+
+```python
+from secryst import Model
+Model.load("ara-diac-2.0")
+```
+
+- Artifact: `ara-diac-2.0-fp32.zip` (2.59 GiB)
+- Precision variants: `ara-diac-2.0-int8`
+
+## 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 | 2.2864 | rababa/docs/RESULTS.md#r7-verdict-table-sadeeddiac-25-2026-08-28 |
+| der_morph_greedy | 1.3343 | rababa/docs/RESULTS.md#r7-verdict-table-sadeeddiac-25-2026-08-28 |
+| wer_wikinews_multiref | 17.3794 | rababa/docs/RESULTS.md#r7-ood-verdict-table-wikinews-2024-multiref-2026-08-28 |
+| der_wikinews_multiref | 11.8273 | rababa/docs/RESULTS.md#r7-ood-verdict-table-wikinews-2024-multiref-2026-08-28 |
+
+## Benchmark
+
+SadeedDiac-25 — full 1,200-paragraph set, Misraj's evaluator, zero
+skipped examples, greedy decode (protocol-matched published numbers
+only):
+
+| system | Total DER | kind |
+|---|---|---|
+| Claude-3.7-Sonnet | 1.39% | frontier LLM |
+| **ara-diac-2.0 (this model)** | **2.29%** | dedicated, 580M |
+| GLM-5.2 | 2.69% | frontier LLM |
+| Gemini-Flash-2.0 | 3.19% | frontier LLM |
+| GPT-4 | 3.86% | frontier LLM |
+| Sadeed-1.5B | 7.29% | leaderboard baseline |
+
+Word-final iʿrāb endings (the hardest component): 1.33% DER.
+Out-of-domain generalization (WikiNews-2024 multi-reference):
+17.38 WER / 11.83 DER.
+
+## Architecture
+
+ByT5-large-class seq2seq transformer (580M parameters), byte-level
+input/output (no tokenizer — id = byte + 3). Trained on classical and
+modern Arabic running text with a news-domain adaptation stage over a
+morphology-auxiliary curriculum. The canonical distribution is the
+Secryst IMF artifact (sha256-verified, parity-gated against the
+PyTorch reference); this repository mirrors those exact bytes.
+
+
+## License
+
+BSD-3-CLAUSE
+
+## Provenance
+
+Trained in the [Secryst training monorepo](https://github.com/secryst/secryst-train) and published through the [interscript-ml](https://github.com/interscript/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.