Instructions to use MSLars/de_pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use MSLars/de_pipeline with spaCy:
!pip install https://huggingface.co/MSLars/de_pipeline/resolve/main/de_pipeline-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("de_pipeline") # Importing as module. import de_pipeline nlp = de_pipeline.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a46a08ccebc52da7bc3518d1dde1053c74ac3758b5ae41c30f1d3f77849409e
- Size of remote file:
- 502 MB
- SHA256:
- 5acdf0eb16389c4401ad28321ab8dd9afe5e45360b27d0d31aa396f612e73c31
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