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workerplacemint/iol-ai-2026-solver
iol-ai-2026-solver is a machine learning model from workerplacemint. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is a minimal starter repo for the IOL-AI 2026 script competition.
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Updated Jul 9, 2026
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From the Hugging Face model README
This is a minimal starter repo for the IOL-AI 2026 script competition.
python -m venv .venv
source .venv/bin/activate # Windows PowerShell: .venv\Scripts\Activate.ps1
pip install -U pandas torch transformers accelerate huggingface_hub safetensors
The challenge eval sandbox cannot download the model at runtime. Download weights once before pushing to your public Hugging Face model repo:
python download_model.py Qwen/Qwen2.5-1.5B-Instruct ./model
Make sure the model license permits redistribution in a public repo.
python make_mock_data.py
IOL_DUMMY=1 python script.py
python - <<'PY'
import pandas as pd, json
s = pd.read_csv('submission.csv')
print(s)
print(json.loads(s.loc[0, 'pred']))
PY
For a real local model run after downloading weights:
python script.py
Create a practice CSV with id, context, query, task_type, eval_type, and gold.
The gold column must be a JSON list string, matching the pred submission format.
Score an existing submission:
python local_eval.py practice.csv --submission submission.csv --details eval_details.csv
Run script.py on the practice CSV first, then score submission.csv:
IOL_DUMMY=1 python local_eval.py practice.csv --run-script
The evaluator reports length match, approximate exact match, and chrF-style character similarity.
script.py and model/.