Files
esh-pfi-infrastructure/stacks/fablefusion-charrp-probe/compose.yaml
T
vh dd627b3b31 feat(refusal-probe): A/B refusal harness + Fable-Fusion 711 probe seat
Dark-Scarlett v1.0 refuses too much on the char-rp-reasoning seat. Root
cause is visible on its card: ReadyArt/Dark-Scarlett-v1.0-27B is a plain
finetune of stock Qwen/Qwen3.6-27B, tagged unaligned/nsfw/erp but carrying
no abliteration -- the base model's refusal machinery is intact, so
off-distribution prompts revert to safety-tuned Qwen3.6 behaviour.

Candidate kkuspa/Qwen3.6-27B-Fable-Fusion-711-...-NVFP4A16 is refusal-ablated
(Heretic), a structural edit rather than a behavioural preference. Verified
before pulling: Qwen3_5ForConditionalGeneration wrapper class, 15 mtp.*
tensors in a separate bf16 shard AND individually enumerated in
quantization_config.ignore, NVFP4A16 with null input_activations, FP8 KV
scales shipped, 262K context, Apache-2.0. Staged byte-verified at
/tank/aimodels/fable-fusion-711-nvfp4a16 (28.55 GB).

services/refusal-probe: deterministic marker-based classifier (LLM judge
only breaks AMBIGUOUS ties, never overrides), intensity-graded battery so
the report renders a refusal curve rather than an average, benign controls
that gate run validity, and explicit handling of the thinking-budget trap
-- empty content with finish_reason=length is reasoning exhausting the
budget, not a refusal, and is excluded from the denominator.

stacks/fablefusion-charrp-probe: throwaway :8019 seat serving as
char-rp-probe, never aliased to char-rp-reasoning. MTP depth 3 rather than
the card's 5 -- its 1.56x was measured greedy, and acceptance degrades at
the temp 1.0 this seat is probed at. GPU1 is zero-sum at 94.9/97.9 GB, so
this seat takes Dark-Scarlett's vacated slot; the A/B is sequential.
2026-08-15 23:14:05 -07:00

87 lines
3.1 KiB
YAML

# fablefusion-charrp-probe — THROWAWAY evaluation seat for
# kkuspa/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP-NVFP4A16
# on ana-ml2 GPU1, served as `char-rp-probe` on :8019.
#
# ⚠️ THIS IS NOT A PRODUCTION SEAT. It exists to A/B against the live
# Dark-Scarlett `char-rp-reasoning` seat (:8018) on refusal rate. It is
# deliberately NOT wired into any LiteLLM alias — see the "no false aliases"
# rule: nothing may answer to `char-rp-reasoning` except the real seat.
#
# ⚠️ GPU1 IS ZERO-SUM. The card sits at ~94.9/97.9 GB with the utility cluster
# co-resident. This seat CANNOT run alongside darkscarlett-charrp-reasoning —
# it takes DS's vacated slot at the same util. Sequence:
# docker compose -p darkscarlett-charrp-reasoning down
# docker compose -p fablefusion-charrp-probe up -d # probe
# docker compose -p fablefusion-charrp-probe down
# docker compose -p darkscarlett-charrp-reasoning up -d # restore
#
# Differences from the DS seat, and why:
# --speculative-config : FF ships its 15 MTP tensors in bf16 and lists them
# in quantization_config.ignore, so MTP actually
# loads here (DS's quant dropped them). Depth 3 to
# match the gen seat, not the card's 5 — the card's
# 1.56x was measured GREEDY, and acceptance falls at
# the temp 1.0 this seat is probed at.
# --served-model-name : char-rp-probe, never char-rp-reasoning.
name: fablefusion-charrp-probe
services:
vllm-fablefusion-probe:
image: ${FF_IMAGE:-vllm/vllm-openai:latest}
container_name: ${FF_CONTAINER:-vllm-fablefusion-probe}
restart: "no" # throwaway: never resurrect itself across a reboot
ipc: host
ports:
- "${FF_PORT:-8019}:8000"
volumes:
- /tank/aimodels:/tank/aimodels
environment:
- PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
- VLLM_API_KEY=${API_KEY:-}
command:
- ${FF_MODEL:-/tank/aimodels/fable-fusion-711-nvfp4a16}
- --quantization
- compressed-tensors
- --language-model-only
- --served-model-name
- char-rp-probe
- --reasoning-parser
- qwen3
- --tool-call-parser
- qwen3_coder
- --enable-auto-tool-choice
- --max-model-len
- "${FF_MAX_MODEL_LEN:-262144}"
- --max-num-seqs
- "${FF_MAX_NUM_SEQS:-32}"
- --gpu-memory-utilization
- "${FF_GPU_MEM_UTIL:-0.44}"
- --kv-cache-dtype
- fp8
- --speculative-config
- '{"method":"qwen3_5_mtp","num_speculative_tokens":${FF_MTP_DEPTH:-3}}'
- --trust-remote-code
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${FF_GPU_ID:-1}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 600s
networks:
- tnet
networks:
tnet:
name: traefik-net
external: true