Instructions to use BenjaminKUL/plus_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminKUL/plus_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BenjaminKUL/plus_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminKUL/plus_model") model = AutoModelForTokenClassification.from_pretrained("BenjaminKUL/plus_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f2005980cfb88ebf522147084eed0e1e1e48d32aff0206283d30deab1623c1f
- Size of remote file:
- 521 MB
- SHA256:
- b58fa1e7fa5017fe2d3b649047e274ac32f4e286618ce01a71c2c8aa03b454fe
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