Instructions to use benhartley/en_adept_ner_trf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use benhartley/en_adept_ner_trf with spaCy:
!pip install https://huggingface.co/benhartley/en_adept_ner_trf/resolve/main/en_adept_ner_trf-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_adept_ner_trf") # Importing as module. import en_adept_ner_trf nlp = en_adept_ner_trf.load() - Notebooks
- Google Colab
- Kaggle
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Evaluation results
- NER Precisionself-reported0.974
- NER Recallself-reported0.976
- NER F Scoreself-reported0.975
- TAG (XPOS) Accuracyself-reported0.000
- Lemma Accuracyself-reported0.000
- Unlabeled Attachment Score (UAS)self-reported0.000
- Labeled Attachment Score (LAS)self-reported0.000
- Sentences F-Scoreself-reported0.000