Instructions to use KoichiYasuoka/bert-base-russian-upos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/bert-base-russian-upos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/bert-base-russian-upos")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-russian-upos") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-russian-upos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0d25f7768442a1384bca9aa47dedd2865619d33d78ceee2248243769ce0dff6
- Size of remote file:
- 729 MB
- SHA256:
- 7bceb86118a35a9c413943d309a018b5834dc035f7cf1e44b9c65e2d00bd1dce
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