Commit Graph

3 Commits

Author SHA1 Message Date
vh 9a916a759f Swap the MeroMero A4B onto the erp-seat seat as char-rp-fast, retire the Pfish-6 alias
Operator: "replace that a4b moe over pfish-6 -- remove the pfish-6 alias and
create an alias for char-rp-fast."

G4-MeroMero-26B-A4B-it-uncensored-heretic-NVFP4A16 is live on ana-ml2 :8021 under
its own served name, behind the new gateway alias char-rp-fast. Pfish-6 is gone
from the gateway and now returns an explicit 400 rather than a substitution; 0 of
17 LiteLLM keys scoped it, so nothing was orphaned. The compose project name stays
erp-seat because asset-engine derives seat liveness from it.

The first quant of that A4B served NaN and passed its healthcheck doing it. It was
built with the dense v2-31B recipe, whose ignore list has no router regex, so all
30 MoE routers were quantized to 4 bits -- and a 4-bit router changes which experts
run rather than degrading them. Quant rc=0, healthcheck green, correct KV pool,
correct served name, and every completion returned finish_reason=length with the
full token count and content: null. The model was emitting a full budget of tokens
that decoded to the empty string. Raw /v1/completions was empty too, ruling out the
chat template and the reasoning parser. The signal that named it was logprobs:
vLLM refused to serialize the response, "Out of range float values are not JSON
compliant: nan".

The lesson is about the control rather than the router. That tree had already been
structurally diffed and passed -- against a verified-good DENSE quant of the same
Gemma-4 family. A dense model has no routers, so the single thing that was wrong
was the single thing the control could not distinguish. Diffing instead against
Pfish-6, a known-good quant of the same 26B-A4B MoE, gave it in one line: 222
ignore entries against 252, the 30 missing being layers.N.router.proj. A positive
control is only worth what it can distinguish, and "same family" is not "same
architecture class".

Re-quantized with the MoE recipe, whose dry-run asserts 11,520 expert Linears and
refuses a router in the quantize set before any GPU time. The live seat then passed
prose with no channel-prefix leak, a solid-colour image read correctly, an auto
tool call parsed, finite logprobs, and KV 534,649 tokens / 2.04x carried over from
Pfish-6 unchanged. The broken tree is parked on ana-ml2 as
...-NVFP4A16.BROKEN-routers-quantized-20260910.

Section 4.4's temp port was not reachable: 15.9 GiB of weights plus KV plus
multimodal encoder-cache profiling does not fit in the ~19 GiB free beside GPU1's
six other tenants -- 0.20 utilization refused admission, 0.185 OOM'd in encoder
profiling. The substitute was reversibility and ordering: named .env backup, prove
the seat on its real port while no alias points at it, move the alias last. That is
why a NaN-serving seat never reached a consumer. The seat was down about 16 minutes
across two attempts; no consumer saw a broken alias.

Playbook gains the router-quant failure signature and the control-class rule in
3.15, and a logprobs check in 4.4. seat_verify.py carries that check as check 6.

Quality is NOT established: no RP eval, no long-context check, no A/B against
Pfish-6 or char-rp. Samplers are the author's card values, untuned here.
2026-09-10 11:34:05 -07:00
vh 6972e7ef7f feat(erp-seat): run 7 quantized to NVFP4A16 and serving as the trial seat on ana-ml2
- services/erp-seat-quant/run_quant_erp_v7.sh: v6 runner retargeted; dry-run gate
  passed identically (11,725 targets, 11,520 experts = 30x128x3, routers+vision BF16)
- 49 GiB bf16 relayed gx10 -> ana-ml2 (no key path either way; nh3-dev relays),
  checksums verified against source; quant 49 -> 16 GiB, all post-steps clean
- stacks/erp-seat: .env-driven swap to erp-tune-v7-nvfp4a16, served under its TRUE
  name; homepage labels + README updated, v6 rollback path recorded
- stacks/litellm: trial -> erp-tune-v7-nvfp4a16 (config-file alias; /model/update
  refuses a config model, so this is an edit + restart)
2026-09-09 15:30:15 -07:00
vh 911ff20356 feat(erp-seat): NVFP4A16 quant pipeline for the Gemma-4 26B-A4B MoE ERP tune + ana-ml2 GPU1 serve stack
- services/erp-seat-quant/quant_nvfp4a16_gemma4_moe.py: linearize_moe first (playbook §3.15),
  asserts the expert Linear count, routers/vision/audio/norms/lm_head ignored, W4A16 for RP
  long-session fidelity, post-steps restore processor configs + template and reset the
  tokenizer truncation cap (§3.14); --dry-run proves targets before GPU time
- services/erp-seat-quant/run_quant_erp_v6.sh: detached container on GPU1 (vllm-llmcompressor)
- stacks/erp-seat: serve recipe copied from gemma4-charrp, true served name only, port 8021
2026-09-08 21:55:28 -07:00