Token Classification
Transformers
Safetensors
Faroese
xlm-roberta
faroese
pos-tagging
morphology
lrec-coling-2026
Instructions to use Setur/BRAGD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Setur/BRAGD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Setur/BRAGD")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Setur/BRAGD") model = AutoModelForTokenClassification.from_pretrained("Setur/BRAGD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a344c59824c80d70762050b3aed1dd9f6ae639e5c88c3935a0bb55b3897aa79
- Size of remote file:
- 496 MB
- SHA256:
- b6441fdc2b549c576180f269a9032ebbc0e062dfdf9a1ece5ca3c86839537ea1
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