Sentence Similarity
sentence-transformers
Joblib
Safetensors
modernbert
security
intrusion-detection
behavior-analytics
intent-recognition
linux
kubernetes
audit-log
text-embeddings-inference
Instructions to use willchen0011/SecEBL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use willchen0011/SecEBL with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("willchen0011/SecEBL") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
SecEBL Public Final Benchmark Examples
This directory contains publicly releasable example data for verifying the release code path: a subset of the internal Linux final benchmark plus normalized Kubernetes AuditLog examples.
The full internal benchmark, training corpora, private pressure-stream rows, and removed sensitive benchmark sessions are not distributed in this GitHub repository.
The *_gold.rev20.jsonl filenames are kept for compatibility. In this release,
they are the expected Rev20 behavior-tag labels for this public benchmark
subset.
linux/example_sessions.jsonl: 10,520 Linux command-session rows from 531 public subset sessions.linux/example_gold.rev20.jsonl: matching Rev20 behavior tags for the same 10,520 rows.k8s/example_sessions.jsonl: 144 normalized Kubernetes AuditLog rows across 46 sessions.k8s/example_gold.rev20.jsonl: matching Rev20 behavior tags for the same 144 K8s rows, with 163 behavior-label instances and 27 unique behavior tags.
Session-level labels use English enums: normal_operation and intrusion.