sentence-transformers How to use Matjac5/MNLP_M2_document_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Matjac5/MNLP_M2_document_encoder")
sentences = [
"His anger reached a boiling point, the therapist said they should take a break and what?",
"chicken coop",
"cool off",
"bark"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
