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parinzee/moodeng-mt-iol-ai-2026
moodeng-mt-iol-ai-2026 is a machine learning model from parinzee. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Code provenance: moodeng-mt commit 11210fd69ecc48f0a6fe88cdc3bf7632aeb9907e ("Apply direct-answer flip + rowsleft-aware program gate"), submission/ tree extracted verbatim via git show, with files relocated so script.…
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Updated Jul 19, 2026
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From the Hugging Face model README
Code provenance: moodeng-mt commit
11210fd69ecc48f0a6fe88cdc3bf7632aeb9907e ("Apply direct-answer flip +
rows_left-aware program gate"), submission/ tree extracted verbatim via
git show, with files relocated so script.py sits at the root of this
tree instead of under a submission/ subdirectory — the competition
sandbox runs python script.py at the repo root.
This card replaces the Variant A card. Variant A described a pipeline with no direct-answer lane; that description is factually wrong for Variant B. Variant B makes a first-class direct-answer lane the primary solve path.
Variant A was moodeng-mt commit d519ec0 (arm 2b). Relative to Variant A,
Variant B changes only code, and only 4 of the 22 shipped code
files:
moodeng/synthesis/generate.pymoodeng/synthesis/pipeline.pymoodeng/synthesis/prompt.pymoodeng/runner_glue.pyThe other 18 code files are byte-identical to Variant A. The weights are
unchanged from Variant A — deepseek-ai/DeepSeek-R1-Distill-Qwen-7B,
fp16, ~15.2 GB, shipped under model/. Variant B ships no new weights.
Variant B promotes the free-text / direct-answer path from a last-resort
degrade into a first-class lane that runs on every puzzle and carries the
primary score. Program synthesis becomes opportunistic rather than the
default. The behavior is governed by a DirectAnswerConfig dataclass in
moodeng/synthesis/generate.py.
The competition sandbox passes no environment variables to the scored
subprocess, so the DirectAnswerConfig dataclass defaults are the
configuration that runs. There is no separate "production config" layered
on top. The shipped defaults are the D1-winning A/B arm:
enabled = True — the direct-answer lane is the default route.
enabled=False restores the exact pre-existing (program-lane-first,
free-text-as-last-resort) code path byte-for-byte, as an opt-out arm.attempt_programs = "off" — program synthesis is not attempted by
default. "leftover_budget" and "always" remain available (via
MOODENG_ATTEMPT_PROGRAMS) for A/B arms. When a program is attempted
and accepted, it still overrides the direct answer for that puzzle —
it is strictly better when real — which is why the gated program
plumbing is retained even though the shipped default never fires it.max_new_tokens = 1024 — used as a ceiling, not an unconditional
override. effective_max_new_tokens takes
min(max_new_tokens, tier_derived_cap), so the tier ladder can still
shrink the budget under time pressure exactly as it does for every
other token budget in the codebase. This ceiling fix was required: an
earlier unconditional 1024-token override, with no tier-throttling
relief, put a 40-row run at 3044.9 s versus the real 1800 s scored cap.
The ceiling can only ever lower the effective cap below what the tier
alone would allow — it can never make the lane more expensive than the
tier ladder intends.min_candidates = 2, program_budget_threshold_s = 30.0.When attempt_programs="leftover_budget" is selected, the program lane
only fires once budget.remaining() clears program_budget_threshold_s
plus a per-remaining-row reserve when rows_left is known (see
pipeline._should_attempt_programs). The gate is checked after the
direct-answer lane has already spent its real wall-clock, so it naturally
reflects true leftover budget with no separate bookkeeping.
DirectAnswerConfig.from_env uses an _opt_int parser that closes a
"zero env var" trap: an absent env var resolves to the dataclass
default (1024), rather than silently collapsing the default to None on
every no-env-var run (exactly the competition sandbox's condition). A var
that is set but empty is an explicit operator opt-out (None, bare
tier-derived cap); set but unparseable falls back to the class default.
python script.py with CWD = this tree's root,
offline, on a single T4 16 GB, fp16, under a 30-minute
wall-clock cap./tmp/data/test.csv.submission.csv to CWD with columns id, pred (a positional
JSON list), and an optional explanation.pred list of the correct length
no matter what fails (graceful degrade to a valid submission).jinja2. Prompts are pre-rendered raw strings built by
moodeng.synthesis.prompt; tokenizer.apply_chat_template is never
called anywhere in this tree.model/ at the root of this tree holds the real
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B checkpoint (model_type: qwen2,
fp16 safetensors shards, tokenizer, configs), unchanged from Variant A
(~15.2 GB). The checkpoint is a plain fp16 checkpoint; on the T4 it loads
under bitsandbytes NF4 4-bit with fp16 compute (as documented in
script.py's sandbox contract and the native-lane run notes), identical
to Variant A's load path. runner_glue.resolve_model_dir probes
{base_dir}/model/config.json as part of its resolver chain; if no
weights resolve, run_model is a no-op and the fallback-only path still
produces a valid submission.csv.
The direct-answer flip was authorized after it won a real-cap Modal T4 A/B.
Measured 12-row A/B on R1-Distill-7B (from the DirectAnswerConfig
docstring): the shipped arm D1 (attempt_programs="off" +
max_new_tokens=1024) reached chrF-mean 14.29 and a
reached-FINAL-ANSWERS rate of 19/55 (34.5%), versus the prior
tier-cap-defaults arm D2 at chrF-mean 10.65 / 5/65 (7.7%), versus
the pre-direct-answer-lane arm-2b baseline at chrF-mean 4.99.
D1 was then confirmed at 40 rows — roughly 2x the chrF of the previously
validated arm-2b configuration, with full per-row coverage (no fallback
answers needed). The 40-row confirm is what exposed the unconditional-
override wall-clock blocker, which the max_new_tokens-as-ceiling fix
above resolves.
Authorizing gate (orchestrator-confirmed): with the ceiling fix in place, the direct-answer flip won a 40-row real-cap Modal T4 A/B at a weighted platform score of 3.344 versus the arm-2b comparator's 2.835 (+18%), finishing in 1516 s wall-clock, under the 1800 s scored cap — the config that authorized shipping Variant B.
This card and the shipped code contain no puzzle text, gold answers, or test rows. All references to "the puzzle task" are generic; no competition content is embedded.