Instructions to use kleinay/nominalization-candidate-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kleinay/nominalization-candidate-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kleinay/nominalization-candidate-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kleinay/nominalization-candidate-classifier") model = AutoModelForTokenClassification.from_pretrained("kleinay/nominalization-candidate-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 614f927960b4a0e20c5bbfba3702abedee66f1376353a705941b7a9c5b04817e
- Size of remote file:
- 324 Bytes
- SHA256:
- 57c5ca704726dda24dcace4bf7f97bb251d245d605d9ef15fd3929648f381caf
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