Instructions to use dchaplinsky/uk_ner_web_trf_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use dchaplinsky/uk_ner_web_trf_base with spaCy:
!pip install https://huggingface.co/dchaplinsky/uk_ner_web_trf_base/resolve/main/uk_ner_web_trf_base-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("uk_ner_web_trf_base") # Importing as module. import uk_ner_web_trf_base nlp = uk_ner_web_trf_base.load() - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -35,4 +35,4 @@ The model was fine-tuned on the [NER-UK dataset](https://github.com/lang-uk/ner-
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A bigger model, trained on xlm-roberta-large with the **State-of-the-Art** performance is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_large).
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Copyright: Dmytro Chaplynskyi, [lang-uk project](https://lang.org.ua), 2022
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A bigger model, trained on xlm-roberta-large with the **State-of-the-Art** performance is available [here](https://huggingface.co/dchaplinsky/uk_ner_web_trf_large).
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Copyright: [Dmytro Chaplynskyi](https://twitter.com/dchaplinsky), [lang-uk project](https://lang.org.ua), 2022
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