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:
- f1911503ec359243dc6efa0aeaf392bad18be4b360103df72b9e0dedc50139f9
- Size of remote file:
- 6.15 kB
- SHA256:
- 6b170bb2ed7330d944f3ae4698ceb66399f7d6c8c6225cafc5eba84ce905ba04
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