Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:5483754
loss:MultipleNegativesRankingLoss
Instructions to use greyplan/loinc-multilingual-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use greyplan/loinc-multilingual-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("greyplan/loinc-multilingual-embeddings") sentences = [ "Flurazepam [Presence] in Serum or Plasma", "Cuantitativo", "Flurazepam: Suero o Plasma : Punto temporal: Presencia o umbral: Ordinal:", "连续数值型标尺 时刻" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K