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Model: srikarkashyap/iol-ai-2026-baseline
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+  - iol-ai-2026
+---
+
+# IOL-AI 2026 submission (v3)
+
+Submission for the [IOL-AI 2026 challenge](https://iolai.org/):
+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).
+
+v2 changes over the plain baseline:
+
+- one generation per numbered item instead of one per problem
+- brief step-by-step reasoning, answer extracted from a `FINAL:` line
+- task-type-specific answer-format instructions
+- a one-shot worked example in the prompt
+- a global time budget that shrinks reasoning space near the 30-min limit
+
+- `script.py` reads `/tmp/data/test.csv` and writes `submission.csv`
+  (columns `id`, `pred`, where `pred` is a JSON list of per-item answers).
+- Model weights are shipped in this repo and loaded from `"."` because the
+  eval sandbox has no internet.
+
+Base model: [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct)
+(Apache 2.0).