How to use lion-ai/arctic-l-medembed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lion-ai/arctic-l-medembed") sentences = [ "post-discharge oral hygiene follow-up plan", "The patient is advised to continue regular oral hygiene measures and follow-up with their primary care dentist.", "PLAN: Follow-up with the patient as clinically indicated.", "The patient's last available report revealed significant improvement in kidney function. No further information is currently available. The patient is advised to follow up with his primary care physician for routine care." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
