Instructions to use AMR-KELEG/ALDi-Token-DI-30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/ALDi-Token-DI-30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AMR-KELEG/ALDi-Token-DI-30")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/ALDi-Token-DI-30") model = AutoModelForTokenClassification.from_pretrained("AMR-KELEG/ALDi-Token-DI-30", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94185ff57ba8986e6cd2a5580d7f8352bdedf2a3f4b68e85d82d3b96c0121ad5
- Size of remote file:
- 3.52 kB
- SHA256:
- 5f4a455147ccbf0036de19db71d29ec98151af0398abdc00582c31cb72d154c5
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