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
Download transformer/model from dchaplinsky/uk_ner_web_trf_base: direct link, hf CLI and curl.
- Browser
- Download file 1.13 GB
-
https://huggingface.co/dchaplinsky/uk_ner_web_trf_base/resolve/main/transformer/model
- Command line
-
hf download hf://dchaplinsky/uk_ner_web_trf_base/transformer/model
-
curl -L -o model https://huggingface.co/dchaplinsky/uk_ner_web_trf_base/resolve/main/transformer/model
1.13 GB
- Xet hash:
- ebd8b4aa7eefe3451b4d2ba854057bbe0b81f50a072c6c4eee90912d521598e3
- Size of remote file:
- 1.13 GB
- SHA256:
- fffae05fdf673dbba508165c1e4da28c797426a5e1034c06b4b1afe5a6994b44
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