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:
- d0cf77e1bde58ea865f77ff86eefdccb7ac9512e23ba33dd58263792c5a8108e
- Size of remote file:
- 649 MB
- SHA256:
- 7ff85dba579bca3aa2ae6faff5086f9422af9dfca51f08c249c6ddf177bc7771
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