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:
- 7a91fa0b7882f5f32fd4d4037a052812cbb8e0cb7bbdccf1b6c18a181b51cf75
- Size of remote file:
- 33.2 MB
- SHA256:
- bbde3e53407df0e50122816df8f936ceb006580c17026e21037518ed542e4cbc
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