Instructions to use lang-uk/uk_ner_wechsel_minixhofer_roberta_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use lang-uk/uk_ner_wechsel_minixhofer_roberta_large with spaCy:
!pip install https://huggingface.co/lang-uk/uk_ner_wechsel_minixhofer_roberta_large/resolve/main/uk_ner_wechsel_minixhofer_roberta_large-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("uk_ner_wechsel_minixhofer_roberta_large") # Importing as module. import uk_ner_wechsel_minixhofer_roberta_large nlp = uk_ner_wechsel_minixhofer_roberta_large.load() - Notebooks
- Google Colab
- Kaggle
uk_ner_wechsel-minixhofer-roberta-large
Model description
uk_ner_wechsel-minixhofer-roberta-large is a fine-tuned Roberta-Large model by @benjamin that is ready to use for Named Entity Recognition and achieves a SoA performance for the NER task for Ukrainian language. That's the best I have for NER so far
It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PERS) and Miscellaneous (MISC).
The model was fine-tuned on the NER-UK dataset, released by the lang-uk. Smaller transformer based model for the SpaCy is available here.
Copyright: Dmytro Chaplynskyi, lang-uk project, 2023
- Downloads last month
- -
Evaluation results
- NER Precisionself-reported0.928
- NER Recallself-reported0.913
- NER F Scoreself-reported0.920