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EMBO
/
vicreg_our_contrast

Feature Extraction
sentence-transformers
Safetensors
modernbert
sentence-similarity
biomedical
embeddings
life-sciences
scientific-text
SODA-VEC
EMBO
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use EMBO/vicreg_our_contrast with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("EMBO/vicreg_our_contrast")
    
    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
vicreg_our_contrast
600 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 28 commits
drAbreu's picture
drAbreu
Update README.md
973da57 verified 11 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    6.22 kB
    Update README.md 11 months ago
  • config.json
    1.29 kB
    Training in progress, step 5000 about 1 year ago
  • model.safetensors
    596 MB
    xet
    Training in progress, step 102379 11 months ago
  • special_tokens_map.json
    694 Bytes
    Training in progress, step 5000 about 1 year ago
  • tokenizer.json
    3.58 MB
    Training in progress, step 5000 about 1 year ago
  • tokenizer_config.json
    20.8 kB
    Training in progress, step 5000 about 1 year ago
  • training_args.bin
    6.07 kB
    xet
    Training in progress, step 5000 11 months ago