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sagteam
/
rubert-base-cased-mcn

Feature Extraction
Transformers
PyTorch
Russian
bert
Model card Files Files and versions
xet
Community
1

Instructions to use sagteam/rubert-base-cased-mcn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sagteam/rubert-base-cased-mcn with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="sagteam/rubert-base-cased-mcn")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("sagteam/rubert-base-cased-mcn")
    model = AutoModel.from_pretrained("sagteam/rubert-base-cased-mcn")
  • Notebooks
  • Google Colab
  • Kaggle
rubert-base-cased-mcn
791 MB
Ctrl+K
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  • 1 contributor
History: 8 commits
sunny3's picture
sunny3
Update README.md
fe5adfb over 3 years ago
  • ConceptVectorizer
    Add model mapping: index to MedDRA PT code over 3 years ago
  • .gitattributes
    1.38 kB
    initial commit over 3 years ago
  • README.md
    435 Bytes
    Update README.md over 3 years ago
  • config.json
    849 Bytes
    Push model files with MedDRA thesaurus embeddings over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch.FloatStorage"

    What is a pickle import?

    711 MB
    xet
    Push model files with MedDRA thesaurus embeddings over 3 years ago
  • special_tokens_map.json
    112 Bytes
    Push model files with MedDRA thesaurus embeddings over 3 years ago
  • tokenizer_config.json
    24 Bytes
    Push model files with MedDRA thesaurus embeddings over 3 years ago
  • vocab.txt
    1.65 MB
    Push model files with MedDRA thesaurus embeddings over 3 years ago