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Blablablab
/
multilingual-style-representation

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
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xet
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1

Instructions to use Blablablab/multilingual-style-representation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Blablablab/multilingual-style-representation with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Blablablab/multilingual-style-representation")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
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License clarification for multilingual-style-representation model weights

#1 opened 5 days ago by
hellthroaster
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