Instructions to use reflex-project/de_trf_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use reflex-project/de_trf_base with spaCy:
!pip install https://huggingface.co/reflex-project/de_trf_base/resolve/main/de_trf_base-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("de_trf_base") # Importing as module. import de_trf_base nlp = de_trf_base.load() - Notebooks
- Google Colab
- Kaggle
Download trainable_lemmatizer/trees from reflex-project/de_trf_base: direct link, hf CLI and curl.
- Browser
- Download file 5.57 MB
-
https://huggingface.co/reflex-project/de_trf_base/resolve/main/trainable_lemmatizer/trees
- Command line
-
hf download hf://reflex-project/de_trf_base/trainable_lemmatizer/trees
-
curl -L -o trees https://huggingface.co/reflex-project/de_trf_base/resolve/main/trainable_lemmatizer/trees
5.57 MB
- Xet hash:
- 54295f757758c20313347d1da0a3194b290e0a97372fcc9f816f02fbae73228d
- Size of remote file:
- 5.57 MB
- SHA256:
- 942db8e716539dacdb9a8b4059b954fbcc94312637cf4feb44783962ef588dd1
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