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IJyad
/
jeb

Text Classification
Transformers
Safetensors
Arabic
jeb
system-one
calibrated-decisions
classification
routing
scoring
guardrails
moderation
arabic
reinforcement-learning
commercial-use
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use IJyad/jeb with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="IJyad/jeb")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("IJyad/jeb", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
jeb / tokenizer
3.79 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
IJyad's picture
IJyad
Restructure: safetensors + encoder/tokenizer configs + self-contained loader
ad5ba3c verified 14 days ago
  • special_tokens_map.json
    132 Bytes
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • tokenizer.json
    2.69 MB
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • tokenizer_config.json
    1.35 kB
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • vocab.txt
    1.1 MB
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago