Instructions to use waspa/en_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use waspa/en_pipeline with spaCy:
!pip install https://huggingface.co/waspa/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:
- a579141bfac4e03d623675c265e0592439c17a5a0abee122910bfed87534bdf6
- Size of remote file:
- 6.01 MB
- SHA256:
- dbe9b1a28ef8e6d173b0ba1010d1c5c70ae792ca993319f7574145f8352a70b5
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