Instructions to use bmeisburger/datathon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bmeisburger/datathon with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bmeisburger/datathon")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("bmeisburger/datathon") model = AutoModelForTokenClassification.from_pretrained("bmeisburger/datathon") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cc12e8d40ee3b5aa54b6c03fb248a9ac898c05b924f071d4c9b702084699255
- Size of remote file:
- 501 MB
- SHA256:
- d960d46f78a2f756a0113b7a8f7089796b28ad26094b70869db743f101f6851e
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