metadata
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
ATT&CK BERT
ATT&CK BERT is a cybersecurity domain-specific language model based on sentence-transformers. ATT&CK BERT maps sentences representing attack actions to a semantically meaningful embedding vector. Sentences with similar meanings will have a high cosine similarity.
Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["Attacker takes a screenshot", "Attacker captures the screen"]
model = SentenceTransformer('basel/ATTACK-BERT')
embeddings = model.encode(sentences)
print(embeddings)