Merge feat/danish-models: Danish fine-tune catalog entries (spec 001 workstream 6)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

# Conflicts:
#	docs/Decisions.md
#	docs/WorkBreakdown.md

docs/Decisions.md

@@ -1431,3 +1431,55 @@ tabs instead of a smaller Whisper model; a failed download is a retryable networ
 terminates the translate worker only.
 **Not done / follow-ups:** WebGPU for Opus-MT (unmeasurable here); more language pairs (the catalog
 is two entries, `TRANSLATION_MODELS`); a translation of live text *while* recording.
+
+## D-WS6a — Danish fine-tuned Whisper models: our own ONNX + CTranslate2 conversions, unpublished until the owner says go
+**Status:** Proposed (2026-10-29, spec 001 Goal 6)
+**Candidates checked (licence + architecture, from each repo's model card, config and notices):**
+- `thorhojhus/whisper-small-danish` — MIT; plain `WhisperForConditionalGeneration`, whisper-small
+  shapes and tokenizer unchanged (80 mel bins, 12/12 layers, vocab 51865). **Kept.**
+- `thorhojhus/whisper-large-v3-turbo-danish` — MIT; plain large-v3-turbo (128 mel, 32/4 layers,
+  vocab 51866). **Kept.**
+- `danish-foundation-models/edda-v0.2` — **Apache-2.0 confirmed** (licensor: the Alexandra
+  Institute; base model MIT); plain large-v3-turbo architecture, so Transformers.js loads it like the
+  stock turbo. Its `generation_config.json` pins `language: "da"`, `task: "transcribe"` and
+  `num_beams: 5`. **Kept.**
+**Catalog:** three entries with `verified: false` everywhere, ids built from one exported constant
+`DANISH_MODELS_HF_OWNER` (placeholder `"PENDING-OWNER"`): `<owner>/<name>-ONNX` for the browser
+engine and `<owner>/<name>-ct2-int8` as `fasterWhisperModel` (a Hub repo id — faster-whisper accepts
+those as well as its aliases). Publishing under the owner's account is a one-line change.
+**Conversions (outside the repo, in `/home/user/hf-publish/<repo>/`; nothing uploaded):** optimum 2.1
+`main_export` (fp32, KV-cached merged decoder) → onnxruntime fp16 / dynamic q8 / MatMulNBits q4 with
+the stock onnx-community settings; `ct2-transformers-converter --quantization int8`. File names, sizes
+and `transformers.js_config.use_external_data_format` match the stock `onnx-community/whisper-small`
+and `-large-v3-turbo` repos to within 0.2 MB per file, with one exception: our q8 turbo decoder
+(173 MB) quantizes the token embedding, while the stock one (440 MB) keeps it in fp32. Two export
+traps, now fixed in the tooling and described in each model card: optimum needs `accelerate`
+installed, or the tied `embed_tokens`/`proj_out` weight is stored twice (+159 MB on small); and
+onnxruntime's fp16 converter makes the merged decoder's If branches cyclic unless their outputs get
+branch-local names first. `generation_config.json` (`<|da|>` = 50285, `task_to_id`) and the tokenizer
+are copied unchanged and asserted equal to the source.
+**Measured** (WER on `da_festuge` with `language: "da"`; ONNX loaded from the local folder through
+Transformers.js 4.2.0 on onnxruntime-node, CT2 through faster-whisper 1.2.1 int8 beam 5; CPU only, one
+21.5 s clip, so the results are a conversion sanity check, not a benchmark):
+
+| model | q8 | q4 | fp16 enc + q4 dec | fp16 | CT2 int8 |
+|---|---|---|---|---|---|
+| whisper-small-danish | 0.109 | 0.094 | 0.094 | 0.094 | 0.078 |
+| stock whisper-small | 0.297 | 0.281 | — | — | 0.234 |
+| whisper-large-v3-turbo-danish | 0.141 | 0.141 | 0.094 | 0.094 | 0.094 |
+| edda-v0.2 | 0.109 | 0.063 | 0.094 | 0.094 | 0.078 |
+| stock whisper-large-v3-turbo | 0.125 | 0.141 | — | — | 0.094 |
+
+The small fine-tune cuts WER by about a factor of three. Neither turbo fine-tune separates from the
+stock turbo on this easy clip, so a longer, harder Danish test is needed to judge them. **D-022
+check:** the turbo fp16 encoders do not overflow on onnxruntime-node; whole-model fp16 gives the
+same transcript as fp16 + q4. WebGPU/WebNN behaviour still needs a real browser.
+**Dtype defaults:** WASM q4 for all three, including small (q4 matched or beat q8 and was 1.4–1.6×
+faster on CPU); WebGPU fp16 encoder + q4 decoder; WebNN fp16. All stay `verified: false`.
+**edda's `num_beams: 5`:** Transformers.js 4.2 has no beam search (its `BeamSearchSampler` returns
+`num_beams` candidates but generation keeps only the top-1), so browser decoding is greedy. It does
+not crash; the only cost is a full-vocabulary top-k per step. The server engine (faster-whisper) does
+use beam 5.
+**Pending the owner:** the Hugging Face account name, then upload the six prepared folders (model
+cards credit the original authors and carry MIT, or Apache-2.0 + NOTICE), then set
+`DANISH_MODELS_HF_OWNER`. The integrator sets `canTranslate: false` on these entries at merge.