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soyrsoyr
/
jev-playground-rlcd

Text Classification
Transformers
Safetensors
English
calibration
zero-shot-classification
system-one
Synthetic
rlcd
Model card Files Files and versions
xet
Community

Instructions to use soyrsoyr/jev-playground-rlcd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use soyrsoyr/jev-playground-rlcd with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="soyrsoyr/jev-playground-rlcd")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("soyrsoyr/jev-playground-rlcd", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
jev-playground-rlcd / deberta-large-7domain
1.75 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
soyrsoyr's picture
soyrsoyr
deberta-v3-large: 7-domain union run, 2 epochs, val ECE 0.0117, zero cross-domain generalization documented
bec0219 verified about 1 month ago
  • config.json
    1.06 kB
    deberta-v3-large: 7-domain union run, 2 epochs, val ECE 0.0117, zero cross-domain generalization documented about 1 month ago
  • model.safetensors
    1.74 GB
    xet
    deberta-v3-large: 7-domain union run, 2 epochs, val ECE 0.0117, zero cross-domain generalization documented about 1 month ago
  • tokenizer.json
    8.34 MB
    deberta-v3-large: 7-domain union run, 2 epochs, val ECE 0.0117, zero cross-domain generalization documented about 1 month ago
  • tokenizer_config.json
    504 Bytes
    deberta-v3-large: 7-domain union run, 2 epochs, val ECE 0.0117, zero cross-domain generalization documented about 1 month ago