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:
- 5492b7e08f122f365d9a368c36f08e9b1ec673db6af2b5d4b66f449c457f981f
- Size of remote file:
- 433 MB
- SHA256:
- dcd03609b51b90201ee97cdca06efcdb28c341e5470fd12b64849d0e55474f18
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