sentence-transformers How to use ellisdoro/dideo-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e1024_early-on2vec-koji-early with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("ellisdoro/dideo-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e1024_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] 
