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0x7o
/
rubert-base-massive-ner

Token Classification
Transformers
PyTorch
Safetensors
Russian
bert
Model card Files Files and versions
xet
Community
2

Instructions to use 0x7o/rubert-base-massive-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use 0x7o/rubert-base-massive-ner with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="0x7o/rubert-base-massive-ner")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("0x7o/rubert-base-massive-ner")
    model = AutoModelForTokenClassification.from_pretrained("0x7o/rubert-base-massive-ner", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
rubert-base-massive-ner
1.42 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 4 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
fa628df about 3 years ago
  • .gitattributes
    1.52 kB
    initial commit about 3 years ago
  • .gitignore
    13 Bytes
    End of training about 3 years ago
  • README.md
    1.34 kB
    update model card README.md about 3 years ago
  • config.json
    6.64 kB
    End of training about 3 years ago
  • model.safetensors
    709 MB
    xet
    Adding `safetensors` variant of this model about 3 years ago
  • pytorch_model.bin
    709 MB
    xet
    End of training about 3 years ago
  • special_tokens_map.json
    125 Bytes
    End of training about 3 years ago
  • tokenizer.json
    3.57 MB
    End of training about 3 years ago
  • tokenizer_config.json
    395 Bytes
    End of training about 3 years ago
  • training_args.bin
    3.96 kB
    xet
    End of training about 3 years ago
  • vocab.txt
    1.65 MB
    End of training about 3 years ago