Instructions to use rame/en_pipeline_ner_model_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use rame/en_pipeline_ner_model_3 with spaCy:
!pip install https://huggingface.co/rame/en_pipeline_ner_model_3/resolve/main/en_pipeline_ner_model_3-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_pipeline_ner_model_3") # Importing as module. import en_pipeline_ner_model_3 nlp = en_pipeline_ner_model_3.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd8e8c070f76298a4814b1b4c64c34a4d2c28f61c546e8f49dd679a9deac0f2e
- Size of remote file:
- 266 MB
- SHA256:
- 2338e7a7cf090e5fa5a97cae7dfa5c82b72ad060e860b078d928fafa3aee06d9
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