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
Download ner/moves from MSLars/de_pipeline: direct link, hf CLI and curl.
- Browser
- Download file 304 Bytes
-
https://huggingface.co/MSLars/de_pipeline/resolve/main/ner/moves
- Command line
-
hf download hf://MSLars/de_pipeline/ner/moves
-
curl -L -o moves https://huggingface.co/MSLars/de_pipeline/resolve/main/ner/moves
304 Bytes
| ��moves�{"0":{},"1":{"PER":32988,"ORG":18724,"GPE":12219,"OTH":6117,"LOC":4435},"2":{"PER":32988,"ORG":18724,"GPE":12219,"OTH":6117,"LOC":4435},"3":{"PER":32988,"ORG":18724,"GPE":12219,"OTH":6117,"LOC":4435},"4":{"PER":32988,"ORG":18724,"GPE":12219,"OTH":6117,"LOC":4435,"":1},"5":{"":1}}�cfg��neg_key� |