Token Classification
Transformers
PyTorch
Scottish Gaelic
xlm-roberta
part-of-speech
Eval Results (legacy)
Instructions to use wietsedv/xlm-roberta-base-ft-udpos28-gd 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-gd 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-gd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-gd") model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-gd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c328f86c0951dd26317796db50563d45fe2f0c34ef548d536de69fb61de32ef
- Size of remote file:
- 1.11 GB
- SHA256:
- 9f147ca91ab7459b3226b6627fe9ac905ee9d444592c7f58b0c7ae244981f06f
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