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BluSerK
/
bert-base-uncased-news-classification

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

Instructions to use BluSerK/bert-base-uncased-news-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BluSerK/bert-base-uncased-news-classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="BluSerK/bert-base-uncased-news-classification")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("BluSerK/bert-base-uncased-news-classification")
    model = AutoModelForSequenceClassification.from_pretrained("BluSerK/bert-base-uncased-news-classification", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
bert-base-uncased-news-classification
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
BluSerK's picture
BluSerK
Update README.md
2be85c0 verified 12 days ago
  • .gitattributes
    1.52 kB
    initial commit 12 days ago
  • README.md
    2.85 kB
    Update README.md 12 days ago
  • config.json
    1.05 kB
    End of training 12 days ago
  • model.safetensors
    438 MB
    xet
    End of training 12 days ago
  • tokenizer.json
    711 kB
    End of training 12 days ago
  • tokenizer_config.json
    351 Bytes
    End of training 12 days ago
  • training_args.bin
    5.14 kB
    xet
    End of training 12 days ago