Instructions to use nishantk613/en_Task1_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use nishantk613/en_Task1_pipeline with spaCy:
!pip install https://huggingface.co/nishantk613/en_Task1_pipeline/resolve/main/en_Task1_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_Task1_pipeline") # Importing as module. import en_Task1_pipeline nlp = en_Task1_pipeline.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65acd0542ff0be9d0b5891ff3ad85ef41a1a1ce95ab38f06235e2b845a67ce10
- Size of remote file:
- 34.4 MB
- SHA256:
- 0c0007eef563a538d07dcb4be23e2c04b2554ce4c81da846faaa2d0187c3e806
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