Token Classification
Transformers
PyTorch
Japanese
roberta
japanese
wikipedia
cc100
pos
dependency-parsing
Instructions to use KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fe631b680da82e29035250cfc6a48322d8fcf3a490affd5f86282ec73576b5d
- Size of remote file:
- 810 kB
- SHA256:
- a7f87f538d8c73fb0a6a34efb7ba6e3488f920341119c02c208bce7965cf248e
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