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MOdysseus
/
SPhilBERTa-LaBSE-Bridge-Ridge

Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
dense
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use MOdysseus/SPhilBERTa-LaBSE-Bridge-Ridge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use MOdysseus/SPhilBERTa-LaBSE-Bridge-Ridge with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("MOdysseus/SPhilBERTa-LaBSE-Bridge-Ridge")
    
    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
SPhilBERTa-LaBSE-Bridge-Ridge
549 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
MOdysseus's picture
MOdysseus
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  • 1_Pooling
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  • 3_Dense
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  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • LICENSE
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  • README.md
    5.37 kB
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  • config.json
    711 Bytes
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  • config_sentence_transformers.json
    284 Bytes
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  • model.safetensors
    541 MB
    xet
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  • modules.json
    705 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    5.36 MB
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  • tokenizer_config.json
    619 Bytes
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