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hamzab
/
roberta-fake-news-classification

Text Classification
Transformers
PyTorch
English
roberta
classification
text-embeddings-inference
Model card Files Files and versions
xet
Community
3

Instructions to use hamzab/roberta-fake-news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use hamzab/roberta-fake-news-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="hamzab/roberta-fake-news-classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("hamzab/roberta-fake-news-classification")
    model = AutoModelForSequenceClassification.from_pretrained("hamzab/roberta-fake-news-classification")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
roberta-fake-news-classification
502 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 18 commits
hamzab's picture
hamzab
Update README.md
648014e almost 3 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • README.md
    1.92 kB
    Update README.md almost 3 years ago
  • config.json
    789 Bytes
    Added labels about 4 years ago
  • merges.txt
    456 kB
    Added tokenizer about 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "torch.LongStorage"

    What is a pickle import?

    499 MB
    xet
    Re-fine tuned the model about 4 years ago
  • special_tokens_map.json
    239 Bytes
    Added tokenizer about 4 years ago
  • tokenizer.json
    2.11 MB
    Added tokenizer about 4 years ago
  • tokenizer_config.json
    349 Bytes
    Added tokenizer about 4 years ago
  • vocab.json
    798 kB
    Added tokenizer about 4 years ago