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
- Xet hash:
- 4b5752dc78fad7901d02b20775c08374e534737434601d552acdbb123867cc6e
- Size of remote file:
- 171 kB
- SHA256:
- daf76830fdb47d83f3e6f161e9876b514138b12e8c3118aabf0b0cdd6f1947c6
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