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:
- ce9f214eacecb646a3688fb2f65be87a5105b09a74dfda82dd7dd1fb4c0779ab
- Size of remote file:
- 1.3 GB
- SHA256:
- dc0454bac094eb9bcfc5225a1906cb99c102336172ef9e7bafc8054a4c830871
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