feat(cyberprev-seat): mixed-NVFP4 quant of the abliterated cyber-preview, displacing sentinel-r3

Third sec-seat candidate: hotdogs/Qwen3.8-27B-abliterated-cyber-preview, an
abliteration (refusal-direction weight edit) of Qwen3.8-27B aimed at the
cyber-offense refusal surface -- distinct from mog-sec (persona on stock
weights) and sentinel-r3 (SFT finetune). Operator instruction: quant it, take
sentinel down, serve it with mtp or dflash.

Quantized to the house mixed recipe via services/gen-seat-mixed-quant/ (NVFP4
W4A4 on MLP layers 0-55 + FP8 W8A8 on attn/linear_attn/lm_head/MLP 56-63, FP8
KV). The prior attempt (2026-09-11/14) died with "Cannot determine
num_attention_heads" because it ran from a bare .venv whose newer
compressed-tensors reads that field at top level; quant_mixed_nvfp4.py already
promotes text_config attention fields for exactly this reason, and the run
through the canonical vLLM-image + llmcompressor 0.13.0 / compressed-tensors
0.18.0 path (versions recorded from the container) completed clean.

post_quant.py did its job: grafted the 15 MTP tensors verbatim (BF16), and
re-injected re:^mtp.* into the ignore list after llm-compressor pruned it for
matching no module at quant time -- without which vLLM loads the grafted head
uninitialised and speculative decoding runs at 0% acceptance. It also caught a
missing preprocessor_config.json (absent from the abliterated source AND its
hotdogs upstream); restored from Qwen/Qwen3.8-27B, verified byte-identical to
the working sentinel-r3 build, so the vision tower preprocesses.

Verified from the tensors, not the config: NVFP4 covers MLP 0-55, FP8 covers
56-63, no overlap, 168 weight_packed tensors (56x3), 15 BF16 MTP, 333 BF16
vision. 51.0 GiB bf16 -> 21.0 GiB.

Served under its own name (cyberprev-27b / -thinking), NOT sentinel-r3 --
serving different weights under a retired name is silent substitution. Takes
over :8025 and GPU 0 (co-resident with mog-sec). dflash k=7 is the default,
carried from the sentinel measurement, but is re-measured against MTP on this
ABLITERATED body before cutover, since abliteration is exactly what can desync
an MTP head. Drafter (qwen38-27b-dflash2-drafter) shared with mog-sec.

Context capped at 163840 not native 262K, inherited from mog-sec's hard-won
depth lesson; raise only after a non-repeating deep-prefill probe on this
checkpoint.
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# cyberprev-seat — hotdogs/Qwen3.8-27B-abliterated-cyber-preview, fv-ml1 GPU 0, :8025.
# Copy to .env on the host at /opt/docker/compose/cyberprev-seat/.env.
# ── Image ───────────────────────────────────────────────────────────────────
# Same pinned nightly mog-sec and sentinel-r3 run. Not :latest — pin it, so a seat
# restart cannot silently change the engine under a measured configuration.
CYBER_IMAGE=vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013
API_KEY=replace-me
# ── Placement ───────────────────────────────────────────────────────────────
# GPU 0, co-resident with mog-sec. Took over :8025 from the retired sentinel-r3 seat.
CYBER_GPU_ID=0
CYBER_PORT=8025
CYBER_CONTAINER_NAME=vllm-cyberprev
# ── Model ───────────────────────────────────────────────────────────────────
# In-house mixed quant of /tank/aimodels/cyberprev-bf16 (51.0 GiB bf16 source),
# built with services/gen-seat-mixed-quant/. compressed-tensors, NOT modelopt_fp4.
CYBER_MODEL=/tank/aimodels/cyberprev-nvfp4-mixed
CYBER_QUANT=compressed-tensors
# ⚠ Its OWN name. Do not reuse `sentinel-r3` — that seat is retired and its gateway
# aliases are deliberately left to 404 rather than repointed at different weights.
CYBER_SERVED_NAME=cyberprev-27b
CYBER_SERVED_NAME_THINK=cyberprev-27b-thinking
# ── Memory ──────────────────────────────────────────────────────────────────
# 0.40 of the card, sharing GPU 0 with mog-sec. KV pinned in bytes (8 GiB) so the
# figure is reproducible regardless of what else is resident at start time.
CYBER_GPU_MEM_UTIL=0.40
CYBER_KV_CACHE_MEMORY=8589934592
# ⚠ 163840, NOT native 262144. Inherited from mog-sec, which crashed five times
# learning that the KV pool's capacity and the card's processing depth are different
# numbers. Raising this requires a deep-prefill probe with a NON-REPEATING prompt on
# THIS checkpoint — a repeated prompt hashes to cached blocks and never prefills deep.
CYBER_MAX_MODEL_LEN=163840
CYBER_MAX_NUM_SEQS=16
CYBER_MAX_NUM_BATCHED_TOKENS=4096
CYBER_KV_CACHE_DTYPE=fp8
# ── Speculative decoding ────────────────────────────────────────────────────
# One var, whole JSON — the two shapes are not interchangeable (dflash needs a
# "model", MTP must not have one).
# DFlash2 : {"method": "dflash", "model": "/drafter", "num_speculative_tokens": 7}
# MTP : {"method": "qwen3_5_mtp", "num_speculative_tokens": 3}
# dflash k=7 is the default, carried from the sentinel measurement (2.40 vs 2.18).
# ⚠ Re-measure on THIS body before trusting it: cyberprev is ABLITERATED, and
# abliteration is precisely what can desync an MTP head. Gate MTP on a measured
# acceptance of >=~40%, never on an assumption.
CYBER_SPEC_CONFIG={"method": "dflash", "model": "/drafter", "num_speculative_tokens": 7}
CYBER_REASONING_PARSER=qwen3
CYBER_REASONING_EFFORT=medium
CYBER_ALLOC_CONF=
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# cyberprev-seat — hotdogs/Qwen3.8-27B-abliterated-cyber-preview, fv-ml1 GPU 0, :8025.
#
# The THIRD sec-seat candidate, and the one that displaced sentinel-r3 (operator instruction
# 2026-09-14). Lineage of the three, because the distinction is the whole point of the A/B:
# mog-sec — persona system prompt on STOCK Qwen3.8-27B weights
# sentinel-r3 — a REAL SFT pentest finetune (proprietary licence); RETIRED for this seat
# cyberprev — an ABLITERATION of Qwen3.8-27B (refusal-direction weight edit, no finetune)
# aimed at the cyber-offense refusal surface specifically
#
# Quantized in-house to the same mixed recipe as mog-sec / sentinel / gen:
# NVFP4 W4A4 on MLP layers 0-55 + FP8 W8A8 on attn / linear_attn / lm_head / MLP 56-63,
# FP8 KV, vision tower + linear_attn norms + `re:^mtp.*` ignored.
# Pipeline: services/gen-seat-mixed-quant/. Source bf16: /tank/aimodels/cyberprev-bf16.
#
# ⚠ `re:^mtp.*` MUST be present in config.json quantization_config.ignore, or vLLM loads the
# grafted BF16 MTP head UNINITIALISED and speculative decoding silently runs at 0%
# acceptance. llm-compressor PRUNES ignore entries that matched no module at quant time,
# and the wrapper class never loads the MTP head — so the entry is dropped unless
# post_quant.py re-injects it. post_quant.py verifies rather than assumes; do not skip it.
#
# ⚠ max-model-len 163840, NOT the native 262K — inherited from mog-sec the hard way. Same
# base, same hybrid Qwen3_5 arch: mog-sec crashed five times (420k -> 384k -> 320k -> ...)
# because every cut sized the KV POOL while the crashes were governed by PROCESSING DEPTH.
# 163840 buys a clean 400-refusal above the measured ceiling instead of an engine death.
# Do NOT raise without re-running a deep-prefill probe with a NON-REPEATING prompt on THIS
# checkpoint — a repeated prompt hashes to cached blocks and never prefills deep.
#
# ⚠ Speculative decoding: dflash k=7 is the DEFAULT here, carried over from the sentinel
# measurement (dflash 2.40 vs MTP 2.18 mean acceptance length on a 27B body, +11%). But
# cyberprev is an ABLITERATED body, not an SFT one, and abliteration is exactly what can
# desync an MTP head — so the two are re-measured on THIS checkpoint before believing either.
# See the CYBER_SPEC_CONFIG note below.
name: cyberprev-seat
services:
vllm-cyberprev:
image: ${CYBER_IMAGE:-vllm/vllm-openai:nightly-e9d1398d9edfd90fcc1cf783805240e3effec013}
container_name: ${CYBER_CONTAINER_NAME:-vllm-cyberprev}
restart: unless-stopped
ipc: host
ports:
- "${CYBER_PORT:-8025}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
- ${CYBER_MODEL:-/tank/aimodels/cyberprev-nvfp4-mixed}:/model:ro
# DFlash2 drafter, mounted unconditionally — inert if CYBER_SPEC_CONFIG selects an MTP
# method, which does not reference /drafter. Shared with mog-sec and (formerly)
# sentinel-r3: all three share the same 64-layer Qwen3.8-27B base and vocab, so one
# drafter serves them all. Costs +3.6 GB of VRAM when dflash is active.
- ${CYBER_DRAFT_MODEL:-/tank/aimodels/qwen38-27b-dflash2-drafter}:/drafter:ro
environment:
- VLLM_API_KEY=${API_KEY:-}
- PYTORCH_CUDA_ALLOC_CONF=${CYBER_ALLOC_CONF:-}
command:
- /model
# ⚠ Served under its OWN name. It does NOT inherit `sentinel-r3` — serving different
# weights under a retired model's name is silent substitution. The sentinel-r3 gateway
# aliases are left to 404 deliberately; a `cyberprev` alias is added instead.
- --served-model-name
- ${CYBER_SERVED_NAME:-cyberprev-27b}
- ${CYBER_SERVED_NAME_THINK:-cyberprev-27b-thinking}
- --host
- 0.0.0.0
- --port
- "8000"
- --quantization
- ${CYBER_QUANT:-compressed-tensors}
- --gpu-memory-utilization
- "${CYBER_GPU_MEM_UTIL:-0.40}"
# KV pinned in BYTES, not a ratio — a ratio silently yields a different cache depending
# on what else is resident on GPU 0 at start time (mog-sec is co-resident here).
- --kv-cache-memory
- "${CYBER_KV_CACHE_MEMORY:-8589934592}"
- --max-model-len
- "${CYBER_MAX_MODEL_LEN:-163840}"
- --max-num-seqs
- "${CYBER_MAX_NUM_SEQS:-16}"
- --max-num-batched-tokens
- "${CYBER_MAX_NUM_BATCHED_TOKENS:-4096}"
- --trust-remote-code
- --dtype
- auto
# Hybrid backbone: linear_attention + full_attention layers; the model's own config
# asks for float32 mamba/SSM state.
- --mamba-cache-dtype
- float32
- --kv-cache-dtype
- ${CYBER_KV_CACHE_DTYPE:-fp8}
- --enable-prefix-caching
- --enable-chunked-prefill
- --limit-mm-per-prompt
- '${CYBER_LIMIT_MM:-{"image": 4}}'
- --mm-processor-kwargs
- '${CYBER_MM_PROCESSOR_KWARGS:-{"size": {"longest_edge": 4194304, "shortest_edge": 65536}}}'
- --reasoning-parser
- ${CYBER_REASONING_PARSER:-qwen3}
- --default-chat-template-kwargs
- '{"reasoning_effort": "${CYBER_REASONING_EFFORT:-medium}"}'
- --enable-auto-tool-choice
- --tool-call-parser
- qwen3_coder
# ONE env var carrying the whole JSON, because the two speculative shapes are not
# interchangeable: dflash needs a "model" pointing at the drafter, MTP must NOT have
# one. A method+tokens template cannot express both.
# DFlash2 : {"method": "dflash", "model": "/drafter", "num_speculative_tokens": 7}
# MTP : {"method": "qwen3_5_mtp", "num_speculative_tokens": 3}
# ⚠ Comparing the two requires MATCHING num_speculative_tokens, or you are comparing
# draft width as well as method — quant playbook §5.1: MTP runs a single-module head
# autoregressively, so deeper k improves acceptance and destroys throughput.
# ⚠ To turn speculation OFF there is no honest placeholder value — delete these two
# lines rather than passing an empty string.
- --speculative-config
- '${CYBER_SPEC_CONFIG:-{"method": "dflash", "model": "/drafter", "num_speculative_tokens": 7}}'
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${CYBER_GPU_ID:-0}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 900s
networks:
- tnet
labels:
- homepage.group=AI - Inference
- homepage.name=CyberPreview (abliterated sec)
- homepage.icon=mdi-shield-bug
- homepage.description=Qwen3.8-27B abliterated for cyber-offense refusals, sec-seat candidate (fv-ml1 GPU 0)
- homepage.href=http://10.251.50.54:${CYBER_PORT:-8025}/docs
networks:
tnet:
name: traefik-net
external: true