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
Commit ·
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Parent(s): 5cb2f5c
base_model
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README.md
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- "token-classification"
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- "pos"
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- "dependency-parsing"
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datasets:
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- "universal_dependencies"
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license: "mit"
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- "token-classification"
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- "pos"
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- "dependency-parsing"
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base_model: deepset/gbert-base
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datasets:
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- "universal_dependencies"
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license: "mit"
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