Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
IR
reranking
securebert
docembedding
text-embeddings-inference
Instructions to use cisco-ai/SecureBERT2.0-cross_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cisco-ai/SecureBERT2.0-cross_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cisco-ai/SecureBERT2.0-cross_encoder") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58724297780dcfef1e51220b17e8e4865c383afc1fcedfd19441360363761867
- Size of remote file:
- 1.2 GB
- SHA256:
- 347a6fcb7d9239e1d15fce7b1771c2d954f5aec13547a51df8a45bb6336eff21
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