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callmesan
/
indic-sentence-bert-nli-hinglish-binary

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use callmesan/indic-sentence-bert-nli-hinglish-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use callmesan/indic-sentence-bert-nli-hinglish-binary with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="callmesan/indic-sentence-bert-nli-hinglish-binary")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("callmesan/indic-sentence-bert-nli-hinglish-binary")
    model = AutoModelForSequenceClassification.from_pretrained("callmesan/indic-sentence-bert-nli-hinglish-binary")
  • Notebooks
  • Google Colab
  • Kaggle
indic-sentence-bert-nli-hinglish-binary
960 MB
Ctrl+K
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  • 1 contributor
History: 18 commits
callmesan's picture
callmesan
End of training
0836d12 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    2.54 kB
    End of training over 1 year ago
  • config.json
    736 Bytes
    Training in progress, epoch 0 over 1 year ago
  • model.safetensors
    950 MB
    xet
    Training in progress, epoch 9 over 1 year ago
  • special_tokens_map.json
    695 Bytes
    Training in progress, epoch 0 over 1 year ago
  • tokenizer.json
    6.41 MB
    Training in progress, epoch 0 over 1 year ago
  • tokenizer_config.json
    1.46 kB
    Training in progress, epoch 0 over 1 year ago
  • training_args.bin
    5.24 kB
    xet
    Training in progress, epoch 0 over 1 year ago
  • vocab.txt
    3.16 MB
    Training in progress, epoch 0 over 1 year ago