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:
- f4698779b032a2b487516b541f6fa2b2631a640f2a610e23e5dd5f264481ac3c
- Size of remote file:
- 4.47 kB
- SHA256:
- 04e5cd45727e7c49b2e29de4a3a9a3432b9f0002aa6e7a93a73478b08e40ced6
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