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
- Xet hash:
- aa6f1be71c0dd19eb10be9d212283d575319ee1071aa86c00253072b29b019c5
- Size of remote file:
- 1.43 GB
- SHA256:
- 961077410bffed0700cded9f0af42e7903e6abfc3ad5c8785809d033eb7c1c87
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.