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Navidium
/
NLP_HF_Workshop

Text Classification
Transformers
Safetensors
distilbert
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use Navidium/NLP_HF_Workshop with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="Navidium/NLP_HF_Workshop")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Navidium/NLP_HF_Workshop")
    model = AutoModelForSequenceClassification.from_pretrained("Navidium/NLP_HF_Workshop")
  • Notebooks
  • Google Colab
  • Kaggle
NLP_HF_Workshop
264 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
Navidium's picture
Navidium
Save model and tokenizer
7aecfab about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • config.json
    636 Bytes
    Save model and tokenizer about 2 years ago
  • model.safetensors
    263 MB
    xet
    Save model and tokenizer about 2 years ago
  • special_tokens_map.json
    125 Bytes
    Save model and tokenizer about 2 years ago
  • tokenizer.json
    669 kB
    Save model and tokenizer about 2 years ago
  • tokenizer_config.json
    1.2 kB
    Save model and tokenizer about 2 years ago
  • vocab.txt
    213 kB
    Save model and tokenizer about 2 years ago