embedding.py

from sentence_transformers import SentenceTransformer

model = SentenceTransformer('symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli')

def getvec(text: str):
    sentences = [text,]
    embeddings = model.encode(sentences)
    return embeddings[0]