Instructions to use rahulpointer/en_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use rahulpointer/en_pipeline with spaCy:
!pip install https://huggingface.co/rahulpointer/en_pipeline/resolve/main/en_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_pipeline") # Importing as module. import en_pipeline nlp = en_pipeline.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f603a8b6c70f09999d0266bf33cc34006f4ab6c6fc2cffdaad432e6d6b2a24a
- Size of remote file:
- 6.01 MB
- SHA256:
- 9e85250396006894deff9022b85b04f6d11033e21e8e5187aca60485a0eef1ca
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