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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 463b24b4a61ab50354a030e6066ee614299723107808dab804406cd61bd50ce5
- Size of remote file:
- 1.08 MB
- SHA256:
- 9fca70379c621cffc6910d3988182faedd75c5b01a8adcb552405a8f83ce7a41
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