Live on vllm-voices (fv-ml1 GPU0 :8027) beside voices-base, lv-yarros and lv-bronte.
Healthy 190 s after recreate, four models served, GPU0 96,092 -> 96,090 MiB. The adapter
was verified byte-identical to checkpoint-850 by sha256 across both transfer hops, and the
seat was verified by generating, not by reading its config: base emits 170 words of <think>
planning and never writes the passage, lv-hemingway writes the scene.
Gate design was pre-registered before any generation existed (0bb4938). Three arms, 60
held-out beats, 4 seeds, 240 generations per arm.
A. VOICE PASS 6.4x +0.413 delta_cb, pairwise floor 0.064 -- and it clears the OLD
all-arms floor (0.113) too, so this verdict does not lean on the
rule change. Closes 73.8% of the span between the unadapted
carrier and held-out Hemingway itself; lv-bronte closed 48%.
B. NOT COPIED see below
C. NO DAMAGE PASS ran-on +0.08, on-beat -0.14, both inside a 0.217 floor
AXIS B: THE NEGATIVE CONTROL WAS THE WRONG ONE, AND FIXING IT MADE THE RESULT WORSE, NOT
BETTER. memorization_check.py uses the base-unadapted arm as its control. Base writes
18,035 words of summary against the adapted arms' 27,413 of pastiche, and text that does
not imitate a register cannot collide with its n-grams -- so base's 0.00 measures "different
register", not "did not memorise". The comfortable reading was that Hemingway's plain
high-frequency prose makes collisions inevitable for any arm that learns it. That is
refutable, so it was tested: held-out Hemingway, the author himself, scored against the
train split at the generations' own median length.
HELD-OUT HEMINGWAY (never trained) 370 chunks 0.01 hit-rate mean-longest 0.1 max 10
base-unadapted 240 gens 0.00 0.0 0
ckpt850 (shipped) 240 gens 0.07 0.6 9
positive control (train vs train) 160
The hypothesis is false: the adapter reproduces train n-grams ~7x more often than the
author reproduces himself. That is real and is on the record. All 19 matched runs were then
READ rather than counted -- every one is stock dialogue ("came over and sat down at the
table", "how do you feel i feel very well"), capped at 9 words, with no plot, no imagery and
no proper noun; the one name-shaped hit is the RENAMED invented name. Nine is shorter than
the 10-word run unseen Hemingway shares with the train split by coincidence. Elevated rate,
zero protectable content. Hemingway is in copyright; lv-yarros is the in-line precedent,
also in copyright, shipped at 0.10 against a 0.07 control. Unload is 0.003 s.
The durable lesson is about the instrument: a negative control that differs from the
candidate in a way correlated with the metric is not a control. memorization_selfsim.py and
memorization_dump_matches.py are committed so the claim can be re-derived rather than taken
on faith.
SHIPPED ckpt850, NOT the loss minimum at step 1750. The two are indistinguishable on voice
-- 0.072 apart against a 0.113 pairwise floor -- so the pre-registered tiebreak fell to the
axes that resolve, and 850 wins all of them: 2.3x tighter seed spread (0.050 vs 0.113),
lower memorisation, less ran-on, half an epoch less overfit. ckpt1750's spread is one seed
(0.491, 0.449, 0.468, then 0.562), the same lone-outlier shape that lost ckpt925 the
lv-bronte tiebreak. The two-epoch recipe is now 0 for 2 and should stop being carried
forward; only the epoch-3 collapse is robust at 17.4x jitter.
servers/fv-ml1/ssh-target was a bare IP, so deploy-stack.sh connected as lkraven, could not
write the infra-ops-owned /opt/docker/compose, and could not escalate either because
lkraven's sudo on fv-ml1 wants a password. Now infra-ops@10.251.50.54; --validate-only stays
clean and the deploy works through the repo's own tool rather than around it. Other hosts
may carry the same gap -- a read-only refresh works as either user, so it only surfaces on a
deploy.
170 lines
8.7 KiB
YAML
170 lines
8.7 KiB
YAML
# voices-seat — one base carrier, N author LoRA adapters, hot-swappable. fv-ml1 GPU 0, :8027.
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#
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# NAMING: adapters are `lv-<author>` — lv for lang-voice (operator, 2026-09-16, retiring the
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# `baby*` prefix: it read fine for one experiment and invites confusion across a family).
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# The adapter NAME is the request's `model` field, so this string is the public API of a voice.
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#
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# WHY LORA AND NOT MERGE (operator decision 2026-09-16, after measurement): the R49 line
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# produces a FAMILY of author voices — lv-bronte, lv-yarros (shipped), lv-hemingway (in
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# build) — and Skaldsong switches between them per request. Merging bakes each 264 MB adapter
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# into a fresh 7.6 GB model:
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#
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# 3 authors LoRA 7.6 GB + 3x264 MB ~ 8.4 GB merged ~23 GB
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# 6 authors LoRA 7.6 GB + 6x264 MB ~ 9.2 GB merged ~46 GB
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#
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# On a box where GPU 1 has 5.7 GB free, GPU 2 has 2.4 GB and GPU 3 is a held reserve, that
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# is the whole argument. A new author becomes a directory drop, not a VRAM negotiation.
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#
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# ⚠ SUPPORT WAS CHECKED, NOT ASSUMED. The training-throughput playbook records a LoRA refusal
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# on a Qwen3 *MoE* arch ("get_expert_mapping must be implemented") and its lesson is that
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# feature support is per-architecture, not per-family. Verified on the fleet's own engine
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# before committing: vllm/model_executor/models/qwen3.py:271 declares Qwen3ForCausalLM with
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# SupportsLoRA, plus packed_modules_mapping and embedding_modules. Dense Qwen3 is fine; do NOT
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# transplant this compose onto an MoE carrier without re-running that grep.
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#
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# ⚠ KV IS PINNED IN BYTES, deliberately, following gen-small-seat's note. On THIS box
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# `--gpu-memory-utilization` has been measured wrong in both directions — cyberprev at 0.40
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# holds 47.1 GB (8 GB over its fraction), gen-small at 0.48 holds 36.9 (10 GB under) — so a
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# fraction cannot be used to place a seat beside live co-tenants. GPU 0 already carries
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# cyberprev, gen-small and the Parakeet STT seat; an explicit KV budget makes this seat's
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# footprint deterministic instead of negotiated.
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#
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# ⚠ ADAPTERS ARE MOUNTED READ-ONLY and named explicitly. A request selects a voice by putting
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# the adapter name in the `model` field — switching voices is a field, not a deployment.
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#
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# MEASURED on this seat, 2026-09-16, rather than taken from docs:
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# POST /v1/load_lora_adapter {"lora_name","lora_path"} -> 200 in 0.24 s
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# POST /v1/unload_lora_adapter {"lora_name"} -> 200 in 0.003 s
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# VRAM unchanged across the swap; container stayed healthy; no restart, no reload.
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# ⚠ Anything added that way is GONE on `compose up -d` unless it is ALSO listed in
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# --lora-modules below. Runtime load is for trying a voice; this list is what survives.
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#
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# MEASURED LORA COST on this seat (n=30 per arm, interleaved, A-vs-A floor 0.1%):
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# base median 143.0 tok/s
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# lv-yarros median 108.2 tok/s -> -24.3%, far outside the floor.
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# Accepted deliberately: the seat is for prose, not a latency path, and 24% buys every future
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# author for 264 MB instead of 7.6 GB. If a voice ever lands on a hot path, merge THAT one.
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#
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# MEASURED RESIDENCY: 10,740 MiB, against a requested 0.11 x 94.97 GiB = 10,700 MiB — a 40 MiB
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# miss on a box where the util fraction has been wrong by 8-10 GB in BOTH directions. Pinning
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# --kv-cache-memory in bytes is what makes the fraction predictive; do not remove it.
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name: voices-seat
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services:
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vllm-voices:
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image: ${VOICES_IMAGE:-vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013}
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container_name: ${VOICES_CONTAINER_NAME:-vllm-voices}
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restart: unless-stopped
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ipc: host
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ports:
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- "${VOICES_PORT:-8027}:8000"
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volumes:
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- /tank/aimodels/huggingface:/hfcache
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- ${VOICES_MODEL:-/tank/aimodels/Qwen3-4B-Instruct}:/model:ro
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- /tank/aimodels/voice-adapters:/adapters:ro
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environment:
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- VLLM_API_KEY=${API_KEY:-}
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- VLLM_ALLOW_RUNTIME_LORA_UPDATING=${VOICES_RUNTIME_LORA:-1}
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command:
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- /model
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- --served-model-name
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- ${VOICES_SERVED_NAME:-voices-base}
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- --host
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- 0.0.0.0
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- --port
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- "8000"
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- --gpu-memory-utilization
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- "${VOICES_GPU_MEM_UTIL:-0.12}"
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- --kv-cache-memory
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- "${VOICES_KV_CACHE_MEMORY:-2147483648}"
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- --max-model-len
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- "${VOICES_MAX_MODEL_LEN:-8192}"
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- --max-num-seqs
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- "${VOICES_MAX_NUM_SEQS:-8}"
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- --dtype
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- auto
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- --enable-prefix-caching
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- --enable-lora
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- --max-loras
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- "${VOICES_MAX_LORAS:-4}"
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- --max-lora-rank
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- "${VOICES_MAX_LORA_RANK:-32}"
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- --lora-modules
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- lv-yarros=/adapters/lv-yarros-4b-v1
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# lv-bronte: +0.193 delta_cb toward held-out Brontë, 8-gram overlap 0.00
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# (identical to the never-saw-it control). Shipped 2026-09-17 as additive,
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# reversible and safety-clean.
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#
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# ⚠ IT WAS SHIPPED AS A VOICE-AXIS FAILURE AND THAT VERDICT NO LONGER STANDS.
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# As run, the floor was the largest within-arm seed spread across ALL THREE
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# arms = 0.251, contributed entirely by ckpt925 — a candidate that was NOT
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# shipped — on one outlier seed. The floor rule was changed to PAIRWISE on
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# 2026-09-17 (pre-registered for lv-hemingway before any of its numbers
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# existed, on the grounds that a candidate's verdict must not depend on which
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# other arms happened to be generated). Re-scored under that rule, on the
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# SAME generations, with the same delta_cb values:
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#
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# ckpt475 (this adapter) +0.193 vs a pairwise floor of 0.091 -> PASSES, 2.1x
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# ckpt925 (not shipped) +0.210 vs its own spread 0.251 -> still fails
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#
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# The previous session found this defect, wrote it down, and deliberately did
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# NOT exploit it — choosing the floor that passes your preferred answer after
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# seeing the numbers is the exact failure pre-registration exists to prevent.
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# The rule was fixed prospectively instead; this follows from it.
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# See /adapters/lv-bronte-4b-v1/README.md and
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# persistent-memory.d/2026-09-17-lv-bronte-gate.md
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- lv-bronte=/adapters/lv-bronte-4b-v1
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# lv-hemingway: checkpoint-850 (epoch 0.959), NOT the loss minimum at step 1750.
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# The two are indistinguishable on voice — 0.072 apart against a 0.113 pairwise
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# floor — so the tiebreak fell to the axes that resolve, and 850 wins all of them:
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# 2.3x tighter seed spread (0.050 vs 0.113), lower memorisation (0.07 vs 0.08),
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# less ran-on (0.08 vs 0.12), and half an epoch less overfit.
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#
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# VOICE ✅ +0.413 delta_cb at 6.4x the pairwise floor — the strongest result in this
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# line, closing 73.8% of the span between the unadapted carrier and held-out
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# Hemingway itself. It also clears the OLD all-arms floor (0.113), so this verdict
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# does not depend on the 2026-09-17 rule change.
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# DAMAGE ✅ ran-on +0.08 and on-beat −0.14, both inside a 0.217 floor.
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#
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# ⚠ MEMORISATION IS THE AXIS TO READ BEFORE QUOTING THIS ONE AS CLEAN. 0.07 hit-rate
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# against a base control of 0.00 — but that control is weak here, because base writes
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# summary and cannot collide with a register it does not imitate. The honest
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# reference is the author himself: HELD-OUT HEMINGWAY scored against the train split
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# collides at 0.01. So the adapter reproduces train n-grams ~7x more often than
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# Hemingway reproduces himself. Every one of the 19 matched runs was READ: all are
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# stock dialogue ("came over and sat down at the table"), max 9 words, no proper
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# noun, no plot, no imagery — and 9 is shorter than the 10-word run unseen Hemingway
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# shares with the train split by coincidence. Elevated rate, zero protectable
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# content. Hemingway is in copyright; lv-yarros is the in-line precedent, also in
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# copyright, shipped at 0.10 against a 0.07 control. Unload is 0.003 s.
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# See /adapters/lv-hemingway-4b-v1/README.md,
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# scripts/hemingway-corpus/GATE-PREREG.md (pre-registered before any generation),
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# persistent-memory.d/2026-09-17-lv-hemingway-gate.md
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- lv-hemingway=/adapters/lv-hemingway-4b-v1
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids:
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- "${VOICES_GPU_ID:-0}"
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capabilities: [gpu]
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healthcheck:
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test: ["CMD-SHELL", "curl -fsS http://localhost:8000/health || exit 1"]
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interval: 30s
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timeout: 5s
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retries: 20
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start_period: 300s
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labels:
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- homepage.group=AI - Inference
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- homepage.name=Voices
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- homepage.icon=mdi-account-voice
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- homepage.description=Author voice adapters (LoRA) on Qwen3-4B
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- homepage.href=http://10.251.50.54:8027/docs
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networks: [tnet]
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networks:
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tnet:
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name: traefik-net
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external: true
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