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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fd9390e70e041df8b23502d507bab723088b80455f3eae8f3fae9c158413499
- Size of remote file:
- 4.47 kB
- SHA256:
- 035df539022192682f8a73d26ff5b659b11e4600692967e91196e19e10c7ab96
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