Instructions to use raoulmago/codice_fiscale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raoulmago/codice_fiscale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="raoulmago/codice_fiscale")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("raoulmago/codice_fiscale") model = AutoModelForTokenClassification.from_pretrained("raoulmago/codice_fiscale", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98afeedaec31eab77e48c70f91c627e03ba8fe6f9cc9802e9750dca4ba6bdf0b
- Size of remote file:
- 4.98 kB
- SHA256:
- 63e37af1f705626b1894d4a14507e9c02628a4cb97627caae573e94a495c1d3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.