Instructions to use nishantk613/en_Task2_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use nishantk613/en_Task2_pipeline with spaCy:
!pip install https://huggingface.co/nishantk613/en_Task2_pipeline/resolve/main/en_Task2_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_Task2_pipeline") # Importing as module. import en_Task2_pipeline nlp = en_Task2_pipeline.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7f44edf3c6847d364ffa056bb4ebe2fd78ed3ddd87287220da269f2af89b424
- Size of remote file:
- 34.4 MB
- SHA256:
- faa96b8208aadebfacce27e78e67e72f9280486b76640898897c5fec281c18fd
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