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base_model: intfloat/multilingual-e5-large library_name: sentence-transformers
Usage
Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
pip install -U sentence-transformers
Then you can load this model and run inference.
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("HasinMDG/multilingual-e5-large")
# Run inference
sentences = [
"passage: Fit Bodies Aren't Perfect, Either \n",
'passage: Royals attend extravagant ceremony to celebrate the opening of new museum',
'passage: Native-American Kids Doused With Beer at SD Hockey Game \n',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
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