# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("ukr-models/uk-punctcase")
model = AutoModelForTokenClassification.from_pretrained("ukr-models/uk-punctcase")Quick Links
Model Description
Fine-tuning of XLM-RoBERTa-Uk model on Ukrainian texts to recover punctuation and case.
How to Use
Download script get_predictions.py from the repository.
from transformers import AutoTokenizer, AutoModelForTokenClassification
from get_predictions import recover_text
tokenizer = AutoTokenizer.from_pretrained('ukr-models/uk-punctcase')
model = AutoModelForTokenClassification.from_pretrained('ukr-models/uk-punctcase')
text = "..."
recover_text(text_processed, model, tokenizer)
- Downloads last month
- 10
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ukr-models/uk-punctcase")