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]
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