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sugarknight
/
erabi-practical-v1-experimental

Text Classification
Transformers
ONNX
Safetensors
Japanese
English
Chinese
GLiClass
gliclass
choice-classification
experimental
Model card Files Files and versions
xet
Community

Instructions to use sugarknight/erabi-practical-v1-experimental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sugarknight/erabi-practical-v1-experimental with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="sugarknight/erabi-practical-v1-experimental")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("sugarknight/erabi-practical-v1-experimental", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
erabi-practical-v1-experimental / onnx
2.64 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
sugarknight's picture
sugarknight
Update to World Choice V1 checkpoint with PyTorch and ONNX variants
72ef021 verified about 5 hours ago
  • fp16
    Update to World Choice V1 checkpoint with PyTorch and ONNX variants about 5 hours ago
  • fp32
    Update to World Choice V1 checkpoint with PyTorch and ONNX variants about 5 hours ago