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@@ -223,6 +223,16 @@ The following tables report detailed results on a shared CTI validation set. **D
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  - Monitor for drift if applying to new domains (e.g., non-English sources, informal channels).
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  - Respect licensing and confidentiality of any proprietary CTI sources used for inference.
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  ## Citation
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  If you find this model useful, please cite the repository and the base model:
 
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  - Monitor for drift if applying to new domains (e.g., non-English sources, informal channels).
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  - Respect licensing and confidentiality of any proprietary CTI sources used for inference.
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+ ## Support & Connect
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+ If this model helps your work, please consider **liking** the repository on Hugging Face ⭐ — it really helps visibility and motivates continued improvements.
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+ * **Donate / support:** Buy me a coffee — [https://buymeacoffee.com/juanmcristobal](https://buymeacoffee.com/juanmcristobal)
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+ * **Open to work:** I’m currently looking for opportunities in **Python / AI / Cybersecurity (CTI, NLP, applied ML)** — connect with me on LinkedIn: [https://www.linkedin.com/in/jmcristobal/](https://www.linkedin.com/in/jmcristobal/)
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+ If you use SecureModernBERT-NER in a project, feel free to share it in the Discussions/Issues — I love seeing real-world use cases.
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  ## Citation
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  If you find this model useful, please cite the repository and the base model: