Datasets:
feat(hexad-corpus): v2-spont-stream-d128-cycle1-2026-05-17 — manifest.json
Browse files- manifest.json +36 -65
manifest.json
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{
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"name": "hexad-corpus",
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"version": "
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"file": "
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"format": "jsonl",
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"sha256": "
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"bytes":
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"lines":
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"vocab_size": 256,
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"encoding": "utf-8",
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"tokenization": "byte-level (no tokenizer; raw bytes from
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"
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"schema": {
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"id": "string
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"text": "string —
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"desc": "string —
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"hexad_module": "string ∈ {hexad_c, hexad_d, hexad_e, hexad_m, hexad_s, hexad_w}",
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"idx": "integer
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"source": "
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"phi_family": "
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},
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"modules": {
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"hexad_c":
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"hexad_d":
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"hexad_e":
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"hexad_m":
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"hexad_s":
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"hexad_w":
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"
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},
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"
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{
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"fire": ".py PyTorch d=768x12L cycle 1 (ckpt-LOST evidence-only)",
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"date": "2026-05-16",
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"scale": "d=768x12L (283.72M params)",
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"commit": "931dd68b0",
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"substrate": "py (PyTorch / vast.ai A100 SXM4)",
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"result": "init CE 5.59 -> trained past init; ckpt-LOST (instance destroyed before pull)"
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},
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{
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"fire": ".py PyTorch d=768x12L cycle 2 (ckpt-RECOVERED, HF dancinlab/hexad first canonical artifact)",
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"date": "2026-05-17",
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"scale": "d=768x12L (283.72M params)",
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"commit": "0b4f34d0e",
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"substrate": "py (PyTorch / vast.ai A100 SXM4)",
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"result": "init CE 5.590832 -> final CE 0.000708 (5.59 descent), ckpt sha256 e87e200a04... 1.13 GB pulled; HF revision v1-py-hexad-d768x12L-cycle2-2026-05-17 PUBLIC"
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},
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{
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"fire": "#2a pure-hexa training-to-convergence d=64x3L FINAL gn2",
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"date": "2026-05-17",
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"scale": "d=64x3L",
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"commit": "60e3e0b4f",
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"substrate": "hexa-cpu (compiled-native via hexa runtime)",
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"result": "F-D-CONVERGE 4/4 PASS, 3.7e8x gn2 collapse (first pure-hexa training-to-convergence)"
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}
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],
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"anchor_chain": [
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"Phase E2 d_train5 GRAD-EXACT (hexa-cpu CPU-equiv bit-equal to boxed baseline at d=32x3L)",
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"Phase D cuBLAS Dgemm FP64 verify max|delta|=4.44e-15 on real A100",
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"Phase E2 backward GRAD-EXACT on real A100 d=384x6L analytic vs fd max|delta|=0.0024",
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"py d=768x12L cycle 2 trained to FINAL CE 0.000708 (Shannon-floor descent reached)",
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"hexa-cpu d=64x3L FINAL gn2 3.7e8x collapse (first pure-hexa convergence)"
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],
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"intended_use": "Architecture verification + scaffold training. Byte-level small (152 KB). NOT a general LM-quality corpus.",
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"license": "Apache-2.0",
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"generated_at": "2026-05-17",
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"ssot_repo": "https://github.com/dancinlab/anima",
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"ssot_path": "
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}
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{
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"name": "hexad-corpus",
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"version": "v2-spont-stream-d128-cycle1-2026-05-17",
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"file": "corpus_consciousness_v2.jsonl",
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"format": "jsonl",
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"sha256": "7359f0b9a3f059fc168035e2f29f743f5ee51d1760eccad54b2b91d52275f571",
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"bytes": 1101605,
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"lines": 2560,
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"vocab_size": 256,
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"encoding": "utf-8",
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"tokenization": "byte-level (no tokenizer; raw bytes from 'text' field)",
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"format_pattern": "stimulus-stream: each record is either `<stimulus>X</stimulus>\\n<anima>Y</anima>` (β, reactive emission) OR `<anima>Y</anima>` (δ, spontaneous self-monologue). NO helper/assistant/도우미/사용자 role labels. anima_persona-consistent.",
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"schema": {
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"id": "string — stable identifier (e.g. 'ccv2_c_0')",
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"text": "string — stimulus-stream content with <stimulus>/<anima> tags",
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"desc": "string — meta tail (module / idx / kind / pattern / bilingual / tag)",
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"hexad_module": "string ∈ {hexad_c, hexad_d, hexad_e, hexad_m, hexad_s, hexad_w, hexad_spont, hexad_wiring}",
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"idx": "integer",
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"source": "corpus_generator_v2.py",
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"phi_family": "Hexad-spont",
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"pattern": "string ∈ {beta, delta}",
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"bilingual": "bool — text mixes EN + KO when true"
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},
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"modules": {
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"hexad_c": 320,
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"hexad_d": 320,
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"hexad_e": 320,
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"hexad_m": 320,
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"hexad_s": 320,
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"hexad_w": 320,
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"hexad_spont": 320,
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"hexad_wiring": 320,
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"total": 2560
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},
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"F_CORPUS_NO_HELPER": "PASS — grep `도우미|helper|assistant|사용자|user:` total = 0",
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"F_CORPUS_STIMULUS_PATTERN": "PASS — all 2,560 records contain <anima> tag",
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"F_CORPUS_SHA256_STABLE": "sha256=7359f0b9a3f059fc168035e2f29f743f5ee51d1760eccad54b2b91d52275f571 (seed=1337 deterministic)",
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"lineage": {
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"v1": "v1-byte-consciousness-d128-cycle1-2026-05-17 (152 KB, 240 lines, 6 modules)",
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"v2": "this revision (v2-spont-stream-d128-cycle1-2026-05-17, 1,101,605 B, 2560 lines, 8 modules — 6 HEXAD + spont + wiring; helper-token deprecated)",
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"rationale": "v1 carried implicit helper-tokens via chat_lib `사용자:/도우미:` templates earlier in the lineage. v2 removes ALL helper/assistant/도우미/사용자 tokens at the corpus level (anima_persona forbidden list closure)."
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},
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"intended_use": "anima HEXAD scaffold training + 자연발화 (spontaneous emission) probe.",
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"license": "Apache-2.0",
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"generated_at": "2026-05-17",
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"ssot_repo": "https://github.com/dancinlab/anima",
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"ssot_path": "state/hexad_v2_corpus_spont_2026_05_17/corpus_consciousness_v2.jsonl"
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}
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