Instructions to use AMR-KELEG/ALDi-Token-DI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/ALDi-Token-DI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AMR-KELEG/ALDi-Token-DI")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/ALDi-Token-DI") model = AutoModelForTokenClassification.from_pretrained("AMR-KELEG/ALDi-Token-DI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b13497919bbda36e37b173ee66b58bc7400edcd39bf387214acdd65faa49facd
- Size of remote file:
- 3.52 kB
- SHA256:
- 4bb3243e713170949466998e8a474a592be4c2bf750567ed9f5e8fd61388dc92
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