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mofawzy
/
Bert-hard-balanced

Text Classification
Transformers
PyTorch
Arabic
bert
HARD
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use mofawzy/Bert-hard-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mofawzy/Bert-hard-balanced with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="mofawzy/Bert-hard-balanced")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("mofawzy/Bert-hard-balanced")
    model = AutoModelForSequenceClassification.from_pretrained("mofawzy/Bert-hard-balanced", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Bert-hard-balanced
4.04 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
mofawzy's picture
mofawzy
Update README.md
1cfc9dc over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • README.md
    1.32 kB
    Update README.md over 4 years ago
  • config.json
    779 Bytes
    add bert model fine tuned on hard dataset over 4 years ago
  • optimizer.pt
    2.69 GB
    xet
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • pytorch_model.bin
    1.35 GB
    xet
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • rng_state.pth
    14.5 kB
    xet
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • scheduler.pt
    623 Bytes
    xet
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • special_tokens_map.json
    112 Bytes
    add bert model fine tuned on hard dataset over 4 years ago
  • tokenizer.json
    837 kB
    add bert model fine tuned on hard dataset over 4 years ago
  • tokenizer_config.json
    381 Bytes
    add bert model fine tuned on hard dataset over 4 years ago
  • trainer_state.json
    1.88 kB
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • training_args.bin
    2.99 kB
    xet
    add more optimization for the model achieve accuracy 96.42 over 4 years ago
  • vocab.txt
    334 kB
    add bert model fine tuned on hard dataset over 4 years ago