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ligolab
/
DxRoberta

Feature Extraction
sentence-transformers
PyTorch
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use ligolab/DxRoberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ligolab/DxRoberta with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ligolab/DxRoberta")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Notebooks
  • Google Colab
  • Kaggle
DxRoberta
410 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 21 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
5d4b8b8 verified over 1 year ago
  • .gitattributes
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    Adding `safetensors` variant of this model over 1 year ago
  • README.md
    217 Bytes
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  • config.json
    682 Bytes
    add model about 5 years ago
  • merges.txt
    91.6 kB
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  • model.safetensors
    205 MB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • pytorch_model.bin
    205 MB
    xet
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  • special_tokens_map.json
    239 Bytes
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  • tokenizer.json
    264 kB
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  • tokenizer_config.json
    376 Bytes
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  • vocab.json
    151 kB
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