Remove Security and License sections from HF README
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README.md
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@@ -349,45 +349,6 @@ Once this basic version runs and already improves instruction following, the nex
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In short, the recommended order for a new model is: first make basic reinjection work, then try anchoring, and only then add rotation if you want the strongest alignment.
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## 🔐 Security
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Run a secret scan before any public push. `gitleaks` does not ship on PyPI, so install it from the official release or your system package manager instead of `pip install gitleaks`.
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For a full Git history scan:
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```bash
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gitleaks detect --source . -v
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```
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For a working-tree-only scan:
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```bash
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gitleaks detect --source . --no-git -v
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```
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This repository also includes a `.pre-commit-config.yaml` entry for `gitleaks`:
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```bash
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pip install pre-commit
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pre-commit install
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pre-commit run --all-files
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```
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In addition to automated secret scanning, avoid committing local absolute paths, internal hostnames, or private checkpoint locations.
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## ⚖️ License
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The code in this repository is released under the [MIT License](LICENSE).
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Prompt Reinjection is an inference-time code intervention that plugs into external model pipelines. This repository does not include, redistribute, or relicense any third-party model weights. Upstream weights and runtimes remain subject to their original licenses, including:
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- SD3 and SD3.5: Stability AI Community License
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- FLUX.1-dev: FLUX.1 `[dev]` Non-Commercial License
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- HunyuanImage-2.1: Tencent Hunyuan Community License Agreement
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- Qwen-Image: Apache License 2.0
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Users are responsible for ensuring that their checkpoint download, local use, fine-tuning, serving, and redistribution flows comply with the corresponding upstream terms. The MIT License in this repository applies only to this repository's code and included assets.
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## 📝 Citation
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If you find this project useful, please cite the ICML 2026 paper:
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In short, the recommended order for a new model is: first make basic reinjection work, then try anchoring, and only then add rotation if you want the strongest alignment.
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## 📝 Citation
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If you find this project useful, please cite the ICML 2026 paper:
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