sentence-transformers How to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("bobox/DeBERTaV3-small-GeneralSentenceTransformer-v2")
sentences = [
"What dual titles did Frederick William hold?",
"The impact was increased by chronic overfishing, and by eutrophication that gave the entire ecosystem a short-term boost, causing the Mnemiopsis population to increase even faster than normal – and above all by the absence of efficient predators on these introduced ctenophores.",
"The \"European Council\" (rather than the Council, made up of different government Ministers) is composed of the Prime Ministers or executive Presidents of the member states.",
"Nearly 50,000 Huguenots established themselves in Germany, 20,000 of whom were welcomed in Brandenburg-Prussia, where they were granted special privileges (Edict of Potsdam) and churches in which to worship (such as the Church of St. Peter and St. Paul, Angermünde) by Frederick William, Elector of Brandenburg and Duke of Prussia."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
