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:
- 57a9f5dfcbc1589dddd0cc9a5a25d4facc3bfaba6d479ba7fcf86036d2bbb446
- Size of remote file:
- 4.02 kB
- SHA256:
- ced450b6330acb85aa9078adb45bef1673074fa3ce249a15e859c4b3bd32d35a
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