Instructions to use Shree17/en_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use Shree17/en_pipeline with spaCy:
!pip install https://huggingface.co/Shree17/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:
- 6fcc78d1181837dfc6fd36c4380f4f464d41df29cd992a55a57195641910ac84
- Size of remote file:
- 6.01 MB
- SHA256:
- acfc1018fd355c2045c66d4894eb3048bb6601fbf3e6a75071843316123ce18f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.