Model Card for cisco ai/SecureBERT2.0 cross encoder The SecureBERT 2.0 Cross Encoder is a cybersecurity domain specific model fine tuned from SecureBERT 2.0. It computes pairwise similarity scores between two texts, enabling use in text reranking, semantic search, and cybersecurity intelligence retrieval tasks. Model Details Model Description Developed by: Cisco AI Model type: Cross Encoder (Sentence Similarity) Architecture: ModernBERT (fine tuned via Sentence Transformers) Max Sequence Length: 1024 tokens Output Labels: 1 (similarity score) Language: English License: Apache 2.0 Finetuned from model: cisco ai/SecureBERT2.0 base Uses Direct Use Semantic text similarity in cybersecurity contexts Text and code reranking for information retrieval (IR) Threat intelligence question–answer relevance scoring Cybersecurity report and log correlation Downstream Use Can be integrated into: Cyber threat intelligence search engines SOC automation pipelines Cybersecurity knowledge graph enrichment Threat hunting and incident response systems Out of Scope Use Generic text similarity outside the cybersecurity domain Tasks requiring generative reasoning or open domain question answering Bias, Risk…
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