Instructions to use KoichiYasuoka/bert-base-german-upos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/bert-base-german-upos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/bert-base-german-upos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-german-upos") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-german-upos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2e30fc2c13a2b26048e0d379f32230c1c26e3db897869f9af724802d286dbe3
- Size of remote file:
- 438 MB
- SHA256:
- 4b142e370aff8d696daa9032fe62347bc15e9a5536b7486ff390b7e949806b8e
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