How to use Auto-opts/flax-TMNRLB_CVR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Auto-opts/flax-TMNRLB_CVR") sentences = [ "compression therapy benefits", "edema: what is, causes, symptoms, and treatment", "How VIN Data Enhances Market Value Assessments", "Daily Iron Intake from Leafy Greens and Fortified Cereals" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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