sentence-transformers How to use azizdh00/MNLP_M3_document_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("azizdh00/MNLP_M3_document_encoder")
sentences = [
"A hash function $h$ is collision-resistant if\\dots",
"6471::[9216:9728]",
"13251::[1536:2048]",
"5817::[2688:3200]"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
