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Maha
/
hin-trac2

Text Classification
Transformers
PyTorch
TensorBoard
bert
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Maha/hin-trac2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Maha/hin-trac2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Maha/hin-trac2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Maha/hin-trac2")
    model = AutoModelForSequenceClassification.from_pretrained("Maha/hin-trac2")
  • Notebooks
  • Google Colab
  • Kaggle
hin-trac2
714 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Maha's picture
Maha
add tokenizer
a21e7b8 about 4 years ago
  • runs
    add model about 4 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • .gitignore
    13 Bytes
    add model about 4 years ago
  • config.json
    943 Bytes
    add model about 4 years ago
  • pytorch_model.bin
    712 MB
    xet
    add model about 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer about 4 years ago
  • tokenizer.json
    1.96 MB
    add tokenizer about 4 years ago
  • tokenizer_config.json
    558 Bytes
    add tokenizer about 4 years ago
  • vocab.txt
    996 kB
    add tokenizer about 4 years ago