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Merge pull request #64 from interscript/fix/remove-duplicate-tiny-spec
fix: remove duplicate ara-diac-tiny spec (last-key-wins hazard)
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src/gpu/modal_distill.py

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@@ -141,40 +141,6 @@ def _ensure_src_path() -> None:
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"mode": "sequence",
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"note": "r6 canonical (2.5793 DER); gate <= 3.07 windowed DER-CE",
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},
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"ara-diac-tiny": {
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# the browser/Worker tier: ~45M params -> ~45MB int8 zip. Same
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# teacher (r6), corpus, and frozen labels as run-002 — the ONLY
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# variable is student capacity. From-scratch risk is real (Thai
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# ablation: scratch byt5-small plateaued ~13% PER) but this is
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# dense CE on 30k paragraph units, not RL; gate: does not
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# collapse (finite output, DER bounded well below scratch) and
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# <= 5.0 windowed DER-CE would make it shippable.
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"teacher": "rababa_arabic_byt5/run-006-morph/best",
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"teacher_volume": "rababa",
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"student_config": {
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"vocab_size": 384,
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"d_model": 384,
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"d_ff": 1024,
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"d_kv": 64,
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"num_layers": 6,
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"num_decoder_layers": 2,
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"feed_forward_proj": "relu",
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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},
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"train": "r5-units/domain.txt",
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"train_extra": ["r5-units/replay.txt"],
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"unit_limits": [24000, 6000],
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"max_len": 1450,
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"label_beams": "1",
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"out": "rababa_arabic_distill_tiny/run-001",
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"labels_file": "teacher_labels_v2.jsonl",
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"labels_complete": "true",
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"mode": "sequence",
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"note": "tiny-tier probe: r6 teacher, run-002 corpus/labels, "
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"~45M student; collapse check + DER gate <= 5.0",
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},
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"ara-diac-small-pkm": {
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# TODO.qwen-next/02 — the LongCat/Qwen capacity axis: keep the
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# ByT5-small compute, add product-key lookup memory (+~25M

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