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SecEmbed-small
alirezaaminzadeh/SecEmbed-small
SecEmbed-small is a sentence similarity model from alirezaaminzadeh. Use it when you need a score for how close two texts are. It is set up for sentence-transformers. The card lists the license as mit.
Cybersecurity dense embedding model continued from BAAI/bge-small-en-v1.5 on secembed-pairs using MultipleNegativesRankingLoss with hard negatives.
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At a glance
- Task
- Sentence Similarity
- Library
- sentence-transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026
- SHA
- b205b546
Base models
Model card
From the Hugging Face model README
SecEmbed-small
Cybersecurity dense embedding model continued from BAAI/bge-small-en-v1.5 on secembed-pairs using MultipleNegativesRankingLoss with hard negatives.
Usage
python from sentence_transformers import SentenceTransformer model = SentenceTransformer("alirezaaminzadeh/SecEmbed-small") emb = model.encode(["detect powershell encoded command", "T1059.001 PowerShell..."])
Cascade
Use with SecReranker: retrieve top-50 with SecEmbed, rerank to top-5.
Training
- Loss: MultipleNegativesRankingLoss
- Data: ATT&CK, Sigma, CVE, CWE, SOC playbook triplets
- Hardware: Hugging Face ZeroGPU
- Task
- Sentence Similarity
- Library
- sentence-transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026