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AHAAM
/
B2BERT

Text Classification
Transformers
Safetensors
bert
Arabic
Dialect Identification
Multi-Label
BERT
MLADI
NLP
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use AHAAM/B2BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AHAAM/B2BERT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="AHAAM/B2BERT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("AHAAM/B2BERT")
    model = AutoModelForSequenceClassification.from_pretrained("AHAAM/B2BERT")
  • Notebooks
  • Google Colab
  • Kaggle
B2BERT
437 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 9 commits
AHAAM's picture
AHAAM
Update README.md
18443bf verified 9 months ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    6.06 kB
    Update README.md 9 months ago
  • config.json
    1.51 kB
    Upload BertForSequenceClassification over 1 year ago
  • model.safetensors
    436 MB
    xet
    Upload BertForSequenceClassification over 1 year ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer over 1 year ago
  • tokenizer.json
    776 kB
    Upload tokenizer over 1 year ago
  • tokenizer_config.json
    1.49 kB
    Upload tokenizer over 1 year ago
  • vocab.txt
    305 kB
    Upload tokenizer over 1 year ago