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abragin
/
bert_book_zipper

Text Classification
Transformers
PyTorch
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use abragin/bert_book_zipper with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="abragin/bert_book_zipper")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("abragin/bert_book_zipper")
    model = AutoModelForSequenceClassification.from_pretrained("abragin/bert_book_zipper")
  • Notebooks
  • Google Colab
  • Kaggle
bert_book_zipper
1.34 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
8149b2d almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    28 Bytes
    initial commit about 3 years ago
  • config.json
    1.09 kB
    Upload 7 files about 3 years ago
  • model.safetensors
    669 MB
    xet
    Adding `safetensors` variant of this model almost 3 years ago
  • pytorch_model.bin
    670 MB
    xet
    Upload 7 files about 3 years ago
  • special_tokens_map.json
    125 Bytes
    Upload 7 files about 3 years ago
  • tokenizer.json
    2.56 MB
    Upload 7 files about 3 years ago
  • tokenizer_config.json
    361 Bytes
    Upload 7 files about 3 years ago
  • training_args.bin
    3.45 kB
    xet
    Upload 7 files about 3 years ago
  • vocab.txt
    872 kB
    Upload 7 files about 3 years ago