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
Download scheduler.pt from cisco-ai/SecureBERT2.0-cross_encoder: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/cisco-ai/SecureBERT2.0-cross_encoder/resolve/main/scheduler.pt
- Command line
-
hf download hf://cisco-ai/SecureBERT2.0-cross_encoder/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/cisco-ai/SecureBERT2.0-cross_encoder/resolve/main/scheduler.pt
1.47 kB
- Xet hash:
- 2dee48e7773823568408d347fb4d0ce70fc25e7cdd905ae741afc5fa41a49a9b
- Size of remote file:
- 1.47 kB
- SHA256:
- 5bc50cd91c9364b8f5f7be52e743b30cf1c0d97c97475282e10e4b9e2abe99a5
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