Submission for the
IOL-AI 2026 challenge:
Qwen2.5-7B-Instruct quantized to 4-bit (bitsandbytes NF4) at load time,
greedy decoding, with per-item prompting.
v3: 7B in 4-bit instead of 1.5B (fp16 fallback if bitsandbytes is missing).
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one generation per numbered item instead of one per problem
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brief step-by-step reasoning, answer extracted from a FINAL: line
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task-type-specific answer-format instructions
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a one-shot worked example in the prompt
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a global time budget that shrinks reasoning space near the 30-min limit
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script.py reads /tmp/data/test.csv and writes submission.csv
(columns id, pred, where pred is a JSON list of per-item answers).
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Model weights are shipped in this repo and loaded from "." because the
eval sandbox has no internet.
