qwen3-vl-8b-hebrew-rashi-merged · Model Card
qwen3-vl-8b-hebrew-rashi-merged: Model Card
Written by Isaac Godfried, published under apache-2.0, revision 1d86cbaf061e, read 2026-10-05. Shown as written; SAVRN's own facts about this model are on its page.
Qwen3-VL-8B Hebrew — v1.5 merged (Rashi focus, historical)
Cairo Genizah AI Transcription — formal analysis and write-up of the project The full account of the methods, training data, benchmarks and error analysis behind the Cairo Genizah AI transcription models. Search the transcribed corpus at Cairo Genizah AI.
This is a historical merged export, NOT the current flagship. The flagship isv1.9a — adapter + merge instructions at qwen3-vl-8b-hebrew-v19a-ckpt.
Full 16-bit merge of v1.5, the Rashi-script generation: pure Rashi glyph perception proven (CER 0.018 on unmemorizable synthetic text), crop-level Vilna gemara solved (CER 0.019), Talmud page-level gemara CER 0.059. Trained at a 3.2 MP resolution floor — use that policy at inference. Vision tower unadapted. Superseded by v1.6+ on print and v1.9a on manuscripts.
The series at a glance
One line per generation — which checkpoint to use and which are historical:
| version | repo | status | canonical revision | headline (benchmark) |
|---|---|---|---|---|
| v1.9a | v19a-ckpt | FLAGSHIP — use this | step 1300 43e21bd7 |
F1 0.816 / CER 0.216 (Genizah religious-140); F1 0.862 / CER 0.196 (frozen PGP-131) |
| v1.9b | v19b-ckpt | experimental control — not adopted | step 1300 f8618c28 |
merger-LoRA ablation study; loss ≡ v1.9a |
| v1.8b | v18b-ckpt | superseded; warm-start ancestor of all v1.9 | step 700 c80313f8 |
first arm with a live vision-tower LoRA |
| v1.8a | v18a-ckpt | superseded A/B control (vision frozen) | step 700 | control arm for the v1.8 vision experiment |
| v1.7 | v17-ckpt | superseded | step 800 | first Genizah-handwriting generation; best VLM on both corpora at its era's benchmarks (Aug 2026) |
| v1.6 | v16-ckpt | superseded; Talmud-print reference | step 1000 (official); step 1100 b9f47f32 (v1.7 warm start) |
Talmud page CER: gemara 0.090 / rashi 0.047 / tosafot 0.099 — Rashi-script 6.7× better than the best closed model we tested (0.315) |
| v1.5 | rashi-ckpt | superseded | final e050aca8 (step 2000) |
proved pure Rashi-glyph perception: CER 0.018 on unmemorizable synthetic text |
| v1 | hebrew-ckpt | superseded (language-only LoRA) | step 3800 e2f85dde |
first checkpoints to read Vilna gemara from pixels |
\* CER over substantive attempts only, alignment-based scorer. Benchmarks differ across generations (Talmud print vs Genizah manuscripts) — compare within a row's named benchmark, not across rows.