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Stern5497
/
sbert-distiluse

Sentence Similarity
sentence-transformers
PyTorch
distilbert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Stern5497/sbert-distiluse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Stern5497/sbert-distiluse with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Stern5497/sbert-distiluse")
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle
sbert-distiluse
544 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Stern5497's picture
Stern5497
Upload 13 files
062c7eb almost 3 years ago
  • 1_Pooling
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  • 2_Dense
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  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • README.md
    2.59 kB
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  • config.json
    643 Bytes
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  • config_sentence_transformers.json
    122 Bytes
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  • modules.json
    341 Bytes
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  • pytorch_model.bin
    539 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    2.92 MB
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  • tokenizer_config.json
    610 Bytes
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  • vocab.txt
    996 kB
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