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dmis-lab
/
biosyn-sapbert-bc5cdr-disease

Feature Extraction
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
3

Instructions to use dmis-lab/biosyn-sapbert-bc5cdr-disease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dmis-lab/biosyn-sapbert-bc5cdr-disease with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="dmis-lab/biosyn-sapbert-bc5cdr-disease", device_map="auto")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("dmis-lab/biosyn-sapbert-bc5cdr-disease")
    model = AutoModel.from_pretrained("dmis-lab/biosyn-sapbert-bc5cdr-disease", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
biosyn-sapbert-bc5cdr-disease
439 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
nazneen's picture
nazneen
model documentation
5396bc1 over 3 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    5.06 kB
    model documentation over 3 years ago
  • config.json
    686 Bytes
    init over 4 years ago
  • pytorch_model.bin
    438 MB
    xet
    add sparse model over 4 years ago
  • sparse_encoder.pk
    35.1 kB
    add sparse model over 4 years ago
  • sparse_weight.pt
    824 Bytes
    xet
    add sparse model over 4 years ago
  • special_tokens_map.json
    112 Bytes
    init over 4 years ago
  • tokenizer.json
    461 kB
    init over 4 years ago
  • tokenizer_config.json
    401 Bytes
    init over 4 years ago
  • vocab.txt
    226 kB
    init over 4 years ago