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
| { | |
| "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" | |
| } |