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OTAR3088
/
CeLLaTe_Contracted_ent_1.0

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

Instructions to use OTAR3088/CeLLaTe_Contracted_ent_1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use OTAR3088/CeLLaTe_Contracted_ent_1.0 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="OTAR3088/CeLLaTe_Contracted_ent_1.0")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("OTAR3088/CeLLaTe_Contracted_ent_1.0")
    model = AutoModelForTokenClassification.from_pretrained("OTAR3088/CeLLaTe_Contracted_ent_1.0")
  • Notebooks
  • Google Colab
  • Kaggle
CeLLaTe_Contracted_ent_1.0
441 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Mardiyyah's picture
Mardiyyah
Add no_vague model trained with contracted ent dataset V3.1
9251582 verified 18 days ago
  • .gitattributes
    1.52 kB
    initial commit 18 days ago
  • README.md
    5.17 kB
    Add no_vague model trained with contracted ent dataset V3.1 18 days ago
  • config.json
    877 Bytes
    Add no_vague model trained with contracted ent dataset V3.1 18 days ago
  • model.safetensors
    440 MB
    xet
    Add no_vague model trained with contracted ent dataset V3.1 18 days ago
  • tokenizer.json
    1 MB
    Add no_vague model trained with contracted ent dataset V3.1 18 days ago
  • tokenizer_config.json
    590 Bytes
    Add no_vague model trained with contracted ent dataset V3.1 18 days ago