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vishnun
/
quantized_knowledge_graph_nlp_onnx

Token Classification
Transformers
ONNX
distilbert
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use vishnun/quantized_knowledge_graph_nlp_onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="vishnun/quantized_knowledge_graph_nlp_onnx")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("vishnun/quantized_knowledge_graph_nlp_onnx")
    model = AutoModelForTokenClassification.from_pretrained("vishnun/quantized_knowledge_graph_nlp_onnx")
  • Notebooks
  • Google Colab
  • Kaggle
quantized_knowledge_graph_nlp_onnx
171 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
vishnun's picture
vishnun
Upload with huggingface_hub
7c7b26c about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    720 Bytes
    Upload with huggingface_hub about 3 years ago
  • model_quantized.onnx
    170 MB
    xet
    Upload with huggingface_hub about 3 years ago
  • ort_config.json
    727 Bytes
    Upload with huggingface_hub about 3 years ago
  • special_tokens_map.json
    125 Bytes
    Upload with huggingface_hub about 3 years ago
  • tokenizer.json
    712 kB
    Upload with huggingface_hub about 3 years ago
  • tokenizer_config.json
    320 Bytes
    Upload with huggingface_hub about 3 years ago
  • vocab.txt
    232 kB
    Upload with huggingface_hub about 3 years ago