Instructions to use BenjaminKUL/plus2_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminKUL/plus2_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BenjaminKUL/plus2_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminKUL/plus2_model") model = AutoModelForTokenClassification.from_pretrained("BenjaminKUL/plus2_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69cce0fc58d56d4a36fc5dc4b4a12c687ef5e5bc2325133ced4579ea263d6e76
- Size of remote file:
- 521 MB
- SHA256:
- ac3545471af714f3134afe46d2b2bacee35e5213e6d741274adeaa21f10aa877
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