Instructions to use BenjaminKUL/new_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminKUL/new_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BenjaminKUL/new_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminKUL/new_model") model = AutoModelForTokenClassification.from_pretrained("BenjaminKUL/new_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a56baf03128e6b8aa303481235845aaa9c877efeaa3cf6e0a1fcb0b52026ec1f
- Size of remote file:
- 521 MB
- SHA256:
- 4b5f0e13608b7b567ad4ddcdaa7c158e802134610776fdaa6812188f3d7904b1
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