Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
cybersecurity
retrieval
mitre-attack
sigma
cve
text-embeddings-inference
Instructions to use alirezaaminzadeh/SecEmbed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alirezaaminzadeh/SecEmbed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alirezaaminzadeh/SecEmbed-base") 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:
- 3c9fb81c225305460601825b9587bcac1bf973384ea269ce202a0f38f1ecc95b
- Size of remote file:
- 5.59 kB
- SHA256:
- de209fdcf668e87403e8f717990572ca7f0b398bce2923caec7042eba721e90f
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