Instructions to use nickprock/it_spacy_ner_trf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use nickprock/it_spacy_ner_trf with spaCy:
!pip install https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/it_spacy_ner_trf-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("it_spacy_ner_trf") # Importing as module. import it_spacy_ner_trf nlp = it_spacy_ner_trf.load() - Notebooks
- Google Colab
- Kaggle
Download token_classification_transformer/model from nickprock/it_spacy_ner_trf: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/token_classification_transformer/model
- Command line
-
hf download hf://nickprock/it_spacy_ner_trf/token_classification_transformer/model
-
curl -L -o model https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/token_classification_transformer/model
438 MB
- Xet hash:
- b7a860f496e9a2694518fe0f2f67f3ed1d1e8c86fd362477c143f217013dbde0
- Size of remote file:
- 438 MB
- SHA256:
- b60dcab0f65601e35a8ae041960b504d0f9789e55098a41406892d34cd520426
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.