Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
compliance
nist-800-53
hipaa
cybersecurity
text-embeddings-inference
Instructions to use stetteh/regmap-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use stetteh/regmap-embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("stetteh/regmap-embedder") 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
File size: 576 Bytes
1936541 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | """Quick start: map a few NIST SP 800-53 controls to HIPAA provisions with RegMap."""
from regmap_map import map_control
CONTROLS = [
"The organization enforces multi-factor authentication for remote access.",
"Employ integrity verification tools to detect unauthorized changes to software and firmware.",
"Retain audit records for a defined period to support after-the-fact investigations.",
]
for control in CONTROLS:
print("\nNIST control:", control)
for r in map_control(control, top_k=3):
print(f" {r['score']:.3f} {r['hipaa_citation']}")
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