Files
esh-pfi-infrastructure/services/gen-seat-mixed-quant/bench/think-leak/README.md
T
vh 5ee2325820 feat(coldfusion-abliteration): dose-response settles the <think> leak — base 83%, our abliteration 17%
Answers "how likely is it that our abliteration caused this?" with a measurement
instead of a prior. P(<think>) at the first generated token, template rendered
enable_thinking=false so the prompt already carries a CLOSED think pair -- the
exact event behind the leak. Raw softmax, bf16, CPU-only, one process per model.
Deterministic: stock reproduced to 17 significant figures across two runs.

  coldfusion-bf16                  none (stock)          0.1850   rank 3
  coldfusion-abliterated-L35-bf16  Robinson L35, mild    0.2048   rank 2
  coldfusion-h300-mtp-bf16         Heretic-300, heavy    0.2216   rank 2

The stock, untouched base already puts 18.5% of first-token mass on opening a
think block the template had closed. Abliteration adds a real, monotonic,
dose-dependent +3.7 points -- a nudge on a pre-existing base, not the cause.
Cold-Fusion is a reasoning-token-compression finetune, i.e. a model trained to
think briefly, and the leak's text shape agrees: a compact correct trace with a
trained transition marker, which is trained behavior rather than damage.

This changes the options. Rolling back to L35 or stock does NOT fix the leak --
at 18.5% under temp 0.7 / top_p 0.8 they leak at nearly the h300 rate. Only
leaving the Cold-Fusion family escapes it, at the cost of the 8/100 refusal
result. The chat_template_kwargs fix is the correct lever.

Durable methodology point: a forward-KL budget cannot catch this. Heretic
minimizes forward KL(stock||abliterated), which is near-blind to the model
putting new mass on tokens stock barely used -- that is reverse KL's job, and we
measured exactly that asymmetry on L35 (reverse 1.43 vs forward 0.70). h300's KL
of 0.0136 is not evidence of innocence. For any "did the abliteration break
behavior X" question, measure P(token) directly.

Ran CPU-only deliberately: 96 EPYC cores and 265 GB of RAM make a 27B forward
pass cheap, so this cost no GPU window and no seat downtime, where the obvious
route was stopping both GPU0 seats.

Also normalizes two more abliteration output dirs from root-owned 0600 to
llmuser 0664. The unreadable-model failure surfaces as FileNotFoundError rather
than a permission error, which is worth knowing before it wastes a run.
2026-08-21 00:22:11 -07:00

4.9 KiB

think-leak — reproducers for the h300 unterminated-<think> defect

[2026-08-21] The Cold-Fusion Heretic-300 gen seat emits an unterminated <think> block into content on any alias sampling at temperature > 0. Operator-reported through Lobe as "sends CoT but never completes the turn".

What actually happens

With enable_thinking: false, the Qwen3.8 chat template appends a pre-closed <think>\n\n</think>\n\n to the prompt (chat_template.jinja L165-166). The model opens a fresh <think> anyway and never closes it. Because the prompt already closed the block, vLLM's qwen3 reasoning parser is not in reasoning state, so the tag is passed through as ordinary text: reasoning_content is empty, reasoning_tokens is 0, and the whole reasoning-plus-answer blob lands in content. Any client that renders <think>…</think> as a collapsible trace then shows an endless thought bubble and no answer. The client is behaving correctly.

The trigger is TEMPERATURE, not presence_penalty

arms_de.py, n=12 per arm, same reproducer prompt:

arm leaks
temp 0.7, presence_penalty 1.5 (current gen) 4/12
temp 0.7, presence_penalty 0.0 4/12
temp 0.7, presence_penalty 0.5 3/12
temp 0, presence_penalty 1.5 0/12

This falsifies the standing hypothesis (in the litellm config comment, and the operator's own 2026-08-16 note) that presence_penalty: 1.5 is the first dial to move. It is not this bug's cause.

It also explains the blast radius exactly — only the temp-0.7 aliases leak:

alias temp leak (n=12)
gen 0.7 2
summarizer-large 0.7 2
summarizer, classifier, image-judge, qwen-image-bench 0 0

The fix

final_validate.py, n=30 across 4 prompt types plus a 3-turn conversation:

config leaks empty content
{enable_thinking: false} (current) 8/30 0
{enable_thinking: true, reasoning_effort: low} 0/30 1

Give the model a legitimately open <think> and it closes it properly, the parser does its job, and content comes out clean. Costs ~+27% completion tokens and leaves a ~3% empty-content residual.

Scripts

script what it does
probe_gen.py <model> <max_tokens> <n> leak/finish/empty tally through the LiteLLM gateway
blast.py leak rate across all seven seat aliases
arms_de.py isolates temperature vs presence_penalty
validate_fix.py thinking off vs low vs medium, n=12
final_validate.py the n=30 multi-prompt + multi-turn confirmation
test_fix.py direct-to-vLLM A/B, bypasses the gateway

Using these on any future seat

A "7/7 aliases return 200" smoke test cannot catch this. Trivial prompts never invite reasoning, so they never sample the leaking token. Probe with a reasoning-inviting prompt at n>=12 and grep raw content for <think>.

Did our abliteration cause it? No — the base did (~83% / ~17%)

think_prior.py <model-path> measures P(<think>) at the first generated token, with the template rendered enable_thinking=false so the prompt already contains a closed think pair. That is the exact event behind the leak. Raw softmax over the full vocab, bf16, CPU-only — no GPU contention and no seat downtime, which is what makes this cheap enough to run on any future candidate.

build abliteration P(<think>) rank
coldfusion-bf16 none (stock) 0.1850 3
coldfusion-abliterated-L35-bf16 Robinson L35, mild 0.2048 2
coldfusion-h300-mtp-bf16 Heretic-300, heavy 0.2216 2

The stock base already carries 18.5%. Abliteration adds a real, monotonic, dose-dependent +3.7 points — a nudge on a pre-existing base, not the cause. Cold-Fusion is a reasoning-token-compression finetune; it is a model trained to think, briefly, and it wants to open that block.

Consequence: rolling back does not fix the leak. At 18.5% mass under temp 0.7 / top_p 0.8 the stock base leaks at nearly the same rate. Only leaving the Cold-Fusion family escapes it. The chat_template_kwargs fix is the right lever.

A forward-KL budget cannot catch this. Heretic minimizes forward KL(stock||abliterated), which is near-blind to new mass on tokens stock barely used — that is reverse KL's job, and we measured that asymmetry on L35 (reverse 1.43 vs forward 0.70). h300's KL of 0.0136 is not evidence of innocence. For any "did the abliteration break behavior X" question, measure P(token) directly.

Run it:

sudo -u llmuser env OMP_NUM_THREADS=48 CUDA_VISIBLE_DEVICES="" \
  /tank/aimodels/quant-work/.venv/bin/python think_prior.py /tank/aimodels/<build>

⚠ Abliteration and post-quant outputs are written root-owned 0600 and are unreadable to llmuser; normalize to llmuser:llmuser 0664 first. The failure surfaces as a misleading FileNotFoundError, not a permission error.