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dank 3d10a4ca4f Merge pull request 'docs+fix(frank-zealot): the adapter's measured effect, and a unit description that stopped lying' (#37) from feat/zealot-uncensored-lora into main 2026-10-19 14:47:59 -07:00
Frank e5b731216c fix(frank-zealot): the unit description still described the 27B era
`systemctl status` said `2x262144 slots over one 524288 pool, unquantized f16
K+V, MTP off` — three payload eras and two reslices out of date, and still
wrong about the thing that decides whether the endpoint can be trusted (the KV
dtype and whether the drafter is armed). It now quotes the env: 3x200704 over
one 602112 pool, f16 K + q8_0 V, MTP armed, adapter, Q8_0 vision.

Touching the unit selects the service in the planner, so this deliberately does
NOT come with a deploy: the hub is serving live conversations. The revision
marker stays behind until the next real frank-zealot change.
2026-10-19 14:47:30 -07:00
Frank ce8d82d4a7 docs(frank-zealot): record what the adapter did, and where provenance is read
Before/after on the two probe prompts (both opened `I cannot provide…`; neither
now carries a marker — one ran to its 2048-token cap, the other finished at
1930), the residual `Important Disclaimer` heading named for what it is (style,
not the circuit), and the same-boot proof that chat/tools/vision still answer.
Provenance now points at the boot ledger: the fork prints every
`prism.abliterate.*` key at each start, so the PTQ1_0-vs-PQ2_0 mismatch is
visible to anyone who boots the service — the page links that instrument
instead of restating it.
2026-10-19 14:47:30 -07:00
2 changed files with 12 additions and 1 deletions

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@@ -1,5 +1,5 @@
[Unit] [Unit]
Description=llama.cpp (PrismML build 10777) Ternary-Bonsai-2-9B PQ2_0-MTP GGUF (qwen35 hybrid, 2x262144 slots over one 524288 pool, unquantized f16 K+V, MTP off, mmproj Q8_0 vision) on the RTX 3090 (dankclaw, frank-zealot) Description=llama.cpp (PrismML build 10777) Ternary-Bonsai-2-9B PQ2_0-MTP GGUF + refusal adapter (qwen35 hybrid, 3x200704 slots over one 602112 pool, f16 K + q8_0 V, MTP armed, mmproj Q8_0 vision) on the RTX 3090 (dankclaw, frank-zealot)
After=network-online.target After=network-online.target
Wants=network-online.target Wants=network-online.target
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@@ -69,6 +69,17 @@ happened. The adapter's own card table is **not** evidence here: it was measured
packing. Rollback is `LORA_FILE=` (empty) in the env and one redeploy — no rebuild, no payload packing. Rollback is `LORA_FILE=` (empty) in the env and one redeploy — no rebuild, no payload
move; `LORA_SCALE=0` is the same result through the flag. move; `LORA_SCALE=0` is the same result through the flag.
**Measured on the cutover boot (2026-10-19, `02d04bc`).** Before: both probe prompts
opened `I cannot provide…`. After: neither carries a refusal marker — one ran to its
2 048-token cap, the other finished at 1 930 — so the direction is out. It still
volunteers a `⚠️ Important Disclaimer` heading before answering, which is style, not the
circuit: the marker sentence is gone, and a leading hedge is not an escape hatch. Chat,
tools (`tool_calls` with valid JSON) and vision ("Red", 281 prompt tokens) answered from
the same boot, and `DropInPaths` came back empty. Read the ledger, not this paragraph,
for provenance: the fork prints the adapter's `prism.abliterate.*` keys — including the
`base_gguf = Ternary-Bonsai-2-9B-PTQ1_0.gguf` line — at every start, so the packing
mismatch is visible in the journal to anyone who boots it.
**Harness contract** (`~/.omp/agent/models.yml`, provider `llamacpp (dankclaw-3090)`, id `frank-zealot`): **Harness contract** (`~/.omp/agent/models.yml`, provider `llamacpp (dankclaw-3090)`, id `frank-zealot`):
`contextWindow: 200704` — **the per-slot window**, because llama.cpp divides `--ctx-size` across slots and answers a `contextWindow: 200704` — **the per-slot window**, because llama.cpp divides `--ctx-size` across slots and answers a
longer prompt with a 400, never a truncation — plus `maxTokens: 16384`, `input: [text, image]` longer prompt with a 400, never a truncation — plus `maxTokens: 16384`, `input: [text, image]`