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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
714 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 12 commits
IJyad's picture
IJyad
Add root config.json so the Hub counts downloads
dd3f243 verified 6 days ago
  • encoder
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • tokenizer
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • .gitattributes
    1.52 kB
    initial commit 14 days ago
  • BENCHMARKS.md
    3.9 kB
    Upload BENCHMARKS.md with huggingface_hub 14 days ago
  • README.md
    8.96 kB
    Upload README.md with huggingface_hub 14 days ago
  • config.json
    600 Bytes
    Add root config.json so the Hub counts downloads 6 days ago
  • jeb_config.json
    406 Bytes
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • model.py
    3.94 kB
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago
  • model.safetensors
    710 MB
    xet
    Restructure: safetensors + encoder/tokenizer configs + self-contained loader 14 days ago