Token Classification
Transformers
PyTorch
Safetensors
Dutch
xlm-roberta
part-of-speech
Eval Results (legacy)
Instructions to use wietsedv/xlm-roberta-base-ft-udpos28-nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/xlm-roberta-base-ft-udpos28-nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wietsedv/xlm-roberta-base-ft-udpos28-nl")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-nl") model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-nl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2427925e69eda689f792678224e0c43e1d2493dc822c4a3bab30b98aeb4f30e6
- Size of remote file:
- 1.11 GB
- SHA256:
- f9e84e355d77dede2fd7750890020c3d12570be2f1734c1e415abcd20a423c37
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