Instructions to use csae8092/de_RTA_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use csae8092/de_RTA_NER with spaCy:
!pip install https://huggingface.co/csae8092/de_RTA_NER/resolve/main/de_RTA_NER-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("de_RTA_NER") # Importing as module. import de_RTA_NER nlp = de_RTA_NER.load() - Notebooks
- Google Colab
- Kaggle
Download tok2vec/model from csae8092/de_RTA_NER: direct link, hf CLI and curl.
- Browser
- Download file 4.44 MB
-
https://huggingface.co/csae8092/de_RTA_NER/resolve/main/tok2vec/model
- Command line
-
hf download hf://csae8092/de_RTA_NER/tok2vec/model
-
curl -L -o model https://huggingface.co/csae8092/de_RTA_NER/resolve/main/tok2vec/model
4.44 MB
- Xet hash:
- 086cf1d2c562f312ccbeed98342a5abf5420f479674f555954f0fe640bd633e6
- Size of remote file:
- 4.44 MB
- SHA256:
- 00df380708e6d990ae78d662b09ab139ccc2943b78c77e53a819be9301def001
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