Instructions to use ukr-models/uk-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ukr-models/uk-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ukr-models/uk-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ukr-models/uk-ner") model = AutoModelForTokenClassification.from_pretrained("ukr-models/uk-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0a0090e95e08e9ab5f1d0289bcbfde617ae9f991060d7c32cb3f15b28d7d4c1
- Size of remote file:
- 438 MB
- SHA256:
- 3976386932afde04f1a579211464073fd5f25ff8ea3f3c5c4fd5925e4a7724a0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.