Instructions to use dchaplinsky/uk_ner_web_trf_13class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use dchaplinsky/uk_ner_web_trf_13class with spaCy:
!pip install https://huggingface.co/dchaplinsky/uk_ner_web_trf_13class/resolve/main/uk_ner_web_trf_13class-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("uk_ner_web_trf_13class") # Importing as module. import uk_ner_web_trf_13class nlp = uk_ner_web_trf_13class.load() - Notebooks
- Google Colab
- Kaggle
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@@ -50,5 +50,7 @@ The model was fine-tuned on the [NER-UK 2.0 dataset](https://github.com/lang-uk/
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Another transformer-based model **trained on 4 classes** for the SpaCy is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_best).
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Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [Mariana Romanyshyn](https://scholar.google.com/citations?user=yji2ZvIAAAAJ&hl=uk&oi=ao), [lang-uk project](https://lang.org.ua), 2024
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Another transformer-based model **trained on 4 classes** for the SpaCy is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_best).
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## Citation
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TBA
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Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [Mariana Romanyshyn](https://scholar.google.com/citations?user=yji2ZvIAAAAJ&hl=uk&oi=ao), [lang-uk project](https://lang.org.ua), 2024
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