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oddadmix
/
Nawah-Dialect-BERT-6M

Text Classification
Transformers
Safetensors
Arabic
bert
feature-extraction
arabic
dialect-identification
arabic-dialects
msa
encoder
tiny-model
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use oddadmix/Nawah-Dialect-BERT-6M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use oddadmix/Nawah-Dialect-BERT-6M with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="oddadmix/Nawah-Dialect-BERT-6M")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-Dialect-BERT-6M")
    model = AutoModel.from_pretrained("oddadmix/Nawah-Dialect-BERT-6M", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Nawah-Dialect-BERT-6M
50.9 MB
Ctrl+K
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  • 1 contributor
History: 13 commits
oddadmix's picture
oddadmix
Upload README.md with huggingface_hub
a603d94 verified about 2 months ago
  • .gitattributes
    1.52 kB
    initial commit about 2 months ago
  • README.md
    7.14 kB
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  • config.json
    1.12 kB
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  • dialect_model.pt
    24 MB
    xet
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  • dialect_model.py
    3.76 kB
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  • labels.json
    97 Bytes
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  • model.safetensors
    23.9 MB
    xet
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  • prepare_dialect.py
    5.9 kB
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  • tokenizer.json
    3.03 MB
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  • tokenizer_config.json
    269 Bytes
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  • train_dialect_cls_bilingual.py
    9.32 kB
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  • train_metrics.json
    34 kB
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