ayoubkirouane/Mpnet-base-ALL-NLI

base_model:

• microsoft/mpnet-base

Dataset :

• sentence-transformers/all-nli

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("ayoubkirouane/Mpnet-base-ALL-NLI")
# Run inference
sentences = [
    'a baby smiling',
    'The boy is smiling',
    'The girl is standing.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]