初始化项目，由ModelHub XC社区提供模型

Model: rpant/iolai26-solve
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-14B-Instruct-AWQ
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- iol-ai-2026
+- linguistic-reasoning
+---
+
+# IOL-AI 2026 Solver
+
+Solves IOL-style linguistics puzzles (Linguini CSV) with a single-shot LLM.
+Ships **Qwen/Qwen2.5-14B-Instruct-AWQ** (4-bit AWQ, Apache-2.0) at the repo
+root, loaded from `MODEL_ID = "."`; runs on a T4 within the 30-minute budget.
+
+## Architecture
+
+- **`script.py`** — entrypoint: reads `/tmp/data/test.csv`, writes
+  `submission.csv` (`id`, `pred` JSON list, `explanation`). Config flags at the
+  top; submission written before the model loads and after every step.
+- **`solver/pipeline.py`** — orchestration. The model answers every puzzle from
+  a minimal prompt (no scaffold, no chain-of-thought); output is parsed into one
+  answer per item and aligned by position. A light greedy-anchored
+  self-consistency vote refines answers while the clock allows. A deterministic
+  symbolic layer (`solver/`) is a last-resort fallback only.
+- **`solver/llm.py`** — batched transformers/AWQ generation, greedy,
+  `repetition_penalty=1.0`, per-token deadline.
+- **`solver/direct.py`** — prompt and answer parsing.
+
+## Run
+
+```bash
+python3 script.py [test.csv] [submission.csv]   # defaults: /tmp/data/test.csv, submission.csv
+```
+
+Weights are the unmodified
+[Qwen/Qwen2.5-14B-Instruct-AWQ](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-AWQ)
+release (Apache-2.0; `LICENSE` retained).