qwen35-ple Auditable N-Gram Memory Artifacts
This release contains the reproducible artifacts for the paper Auditable N-Gram Memory for Small Language Models.
Links
- Code repository: https://github.com/QingGo/qwen35-ple
- Paper source: https://github.com/QingGo/qwen35-ple/blob/main/paper/paper.typ
- Compiled PDF: https://github.com/QingGo/qwen35-ple/blob/main/paper.pdf
- Evaluation card: https://github.com/QingGo/qwen35-ple/blob/main/docs/evaluation-card-paper.md
- Reproducibility manifest: https://github.com/QingGo/qwen35-ple/blob/main/docs/reproducibility-manifest.md
Contents
projectors/: PLE Projector checkpoints (10k training, seeds 0-4).adapters/: Purified OPSD MoRA adapters (seeds 0-2).datasets/: PLE projector local-continuation datasets (1k and 10k).configs/: N-gram fusion router / token policy / projector configs.scripts/: Evaluation, training, fairness/sensitivity scripts.results/: HumanEval, TriviaQA, pass@k, LLM judge, sensitivity, CPU benchmark results.docs/: Evaluation card, reproducibility manifest, evidence notes.artifact-manifest.json/SHA256SUMS: checksums and provenance.
Use
# Reproduce PLE projector training (example)
python scripts/train_ple_projector.py --model <Qwen3.5-0.8B> --dataset datasets/ple-projector-dataset-10k.jsonl --max-train-samples 7000 --max-eval-samples 300 --steps 100 --device cuda --seed 0 --output projector-seed0.json
License
Artifacts are released under Apache-2.0 unless noted otherwise. Model weights remain subject to the upstream Qwen license.