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
| language: | |
| - "ja" | |
| tags: | |
| - "japanese" | |
| - "wikipedia" | |
| - "cc100" | |
| - "pos" | |
| - "dependency-parsing" | |
| base_model: nlp-waseda/roberta-base-japanese | |
| datasets: | |
| - "universal_dependencies" | |
| license: "cc-by-sa-4.0" | |
| pipeline_tag: "token-classification" | |
| # roberta-base-japanese-juman-ud-goeswith | |
| ## Model Description | |
| This is a RoBERTa model pretrained on Japanese Wikipedia and CC-100 texts for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [roberta-base-japanese](https://huggingface.co/nlp-waseda/roberta-base-japanese). | |
| ## How to Use | |
| ``` | |
| from transformers import pipeline | |
| nlp=pipeline("universal-dependencies","KoichiYasuoka/roberta-base-japanese-juman-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple") | |
| print(nlp("全学年にわたって小学校の国語の教科書に挿し絵が用いられている")) | |
| ``` | |
| [fugashi](https://pypi.org/project/fugashi) is required. | |