Instructions to use bsoviedo/es_COLNER_uncleaned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use bsoviedo/es_COLNER_uncleaned with spaCy:
!pip install https://huggingface.co/bsoviedo/es_COLNER_uncleaned/resolve/main/es_COLNER_uncleaned-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("es_COLNER_uncleaned") # Importing as module. import es_COLNER_uncleaned nlp = es_COLNER_uncleaned.load() - Notebooks
- Google Colab
- Kaggle
Download transformer/model from bsoviedo/es_COLNER_uncleaned: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/bsoviedo/es_COLNER_uncleaned/resolve/main/transformer/model
- Command line
-
hf download hf://bsoviedo/es_COLNER_uncleaned/transformer/model
-
curl -L -o model https://huggingface.co/bsoviedo/es_COLNER_uncleaned/resolve/main/transformer/model
440 MB
- Xet hash:
- 7ea50454f4a247c519bd41016a1bbb5021b78fa38695a49a021c5a46bf31443e
- Size of remote file:
- 440 MB
- SHA256:
- 4a9897eee453ccaf58d2c29fcc1c83b309558acaedd51cc8fd0e77cc858e0757
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