Token Classification
Transformers
PyTorch
Old Russian
xlm-roberta
part-of-speech
Eval Results (legacy)
Instructions to use wietsedv/xlm-roberta-base-ft-udpos28-orv 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-orv 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-orv")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-orv") model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-orv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 601665e1a697daea38e8a77c4ef3ad4770970b54c5244e6aabfdb8943fddc384
- Size of remote file:
- 1.11 GB
- SHA256:
- cffc3d3d2280059a76b390503bd2b97c36f8275c89889d6f6d4a6fec0eca6ac3
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