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:
- 0d69855392ba82ef4b7a3f709b52bcc380c795df0d8c71ce5b5a6377c6440297
- Size of remote file:
- 6.14 MB
- SHA256:
- 6967e88ec7b0680d94a75500c46fe19a1b1e01ef5f608a58826077e45af5010d
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