How to use philmas/cese5020-contrastive-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("philmas/cese5020-contrastive-model", trust_remote_code=True) sentences = [ "Radionuclide therapy for targeted cancer treatment", "Reinforced fish plates with a zinc coating for tropical climates", "Tantalum alloy powders for hardened steel production.", "Kraft pulp used extensively in the production of kraft paper and bags." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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