How to use ellisdoro/amphx-all-MiniLM-L6-v2_cross_attention_gat_h1024_o128_cross_entropy_e128_early-on2vec-koji-early with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ellisdoro/amphx-all-MiniLM-L6-v2_cross_attention_gat_h1024_o128_cross_entropy_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]
