Instructions to use FriendlyUser/en_stonk_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use FriendlyUser/en_stonk_pipeline with spaCy:
!pip install https://huggingface.co/FriendlyUser/en_stonk_pipeline/resolve/main/en_stonk_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_stonk_pipeline") # Importing as module. import en_stonk_pipeline nlp = en_stonk_pipeline.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff40212c85cc7d4b5b8ea76fe396e52b6e3628a48bec2304aba8d5daa5d56bda
- Size of remote file:
- 6.28 MB
- SHA256:
- 9501662e93036b834cac45ad7014f9376ee2709606d82d79aa29e4243cdaca42
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