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PDAP
/
url-relevance

Text Classification
Transformers
google-tensorflow TensorFlow
TensorBoard
Safetensors
distilbert
generated_from_keras_callback
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use PDAP/url-relevance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use PDAP/url-relevance with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="PDAP/url-relevance")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("PDAP/url-relevance")
    model = AutoModelForSequenceClassification.from_pretrained("PDAP/url-relevance")
  • Notebooks
  • Google Colab
  • Kaggle
url-relevance
546 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 50 commits
EvilDrPurple's picture
EvilDrPurple
Delete runs/DistilBERT/Latest Model/events.out.tfevents.1713923967.kylie-aspiree5553g.917546.0
d1c8d99 verified about 2 years ago
  • runs
    Delete runs/DistilBERT/Latest Model/events.out.tfevents.1713923967.kylie-aspiree5553g.917546.0 about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    862 Bytes
    Upload TFDistilBertForSequenceClassification over 2 years ago
  • config.json
    955 Bytes
    Upload 3 files about 2 years ago
  • model.safetensors
    273 MB
    xet
    Upload 3 files about 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer about 2 years ago
  • tf_model.h5
    273 MB
    xet
    Upload 3 files about 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.2 kB
    Upload tokenizer about 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer about 2 years ago