Token Classification
Transformers
PyTorch
Ukrainian
xlm-roberta
named-entity-recognition
sequence-tagger-model
Instructions to use EvanD/xlm-roberta-base-ukrainian-ner-ukrner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EvanD/xlm-roberta-base-ukrainian-ner-ukrner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EvanD/xlm-roberta-base-ukrainian-ner-ukrner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EvanD/xlm-roberta-base-ukrainian-ner-ukrner") model = AutoModelForTokenClassification.from_pretrained("EvanD/xlm-roberta-base-ukrainian-ner-ukrner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot