Sentence Similarity
sentence-transformers
Safetensors
English
bert
security
compliance
cre
opencre
bi-encoder
cybersecurity
framework-mapping
nist
owasp
mitre-atlas
text-embeddings-inference
Instructions to use rockCO78/tract-cre-assignment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rockCO78/tract-cre-assignment with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rockCO78/tract-cre-assignment") 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
Add deployment_artifacts.npz (required by tract assign)
Browse files- deployment_artifacts.npz +3 -0
deployment_artifacts.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:7e8b8f834db503118d75727675716471636f139ecb3b64fbd6bc96d6690122f7
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size 14808534
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