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: 253 Bytes
1936541 | 1 2 3 4 5 6 7 8 9 | {
"model": "all-MiniLM-L6-v2 + MultipleNegativesRankingLoss",
"positive_pairs": 222,
"recall@1": 0.2647058823529412,
"recall@3": 0.5588235294117647,
"recall@5": 0.7352941176470589,
"mrr": 0.46306534521712095,
"date": "2026-06-25"
} |