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Gkumi
/
p_m

Token Classification
Transformers
Safetensors
bert
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use Gkumi/p_m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="Gkumi/p_m")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Gkumi/p_m")
    model = AutoModelForTokenClassification.from_pretrained("Gkumi/p_m")
  • Notebooks
  • Google Colab
  • Kaggle
p_m
437 MB
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  • 1 contributor
History: 5 commits
Gkumi's picture
Gkumi
Upload tokenizer
0777973 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    11 Bytes
    Upload BertForTokenClassification almost 2 years ago
  • config.json
    6 kB
    Upload BertForTokenClassification almost 2 years ago
  • model.safetensors
    436 MB
    xet
    Upload BertForTokenClassification almost 2 years ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer almost 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer almost 2 years ago
  • tokenizer_config.json
    1.3 kB
    Upload tokenizer almost 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer almost 2 years ago