How to use ellisdoro/cteno-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e128_early-on2vec-koji-early with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ellisdoro/cteno-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e128_early-on2vec-koji-early") 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]
