Instructions to use KoichiYasuoka/roberta-base-korean-ud-goeswith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoichiYasuoka/roberta-base-korean-ud-goeswith with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KoichiYasuoka/roberta-base-korean-ud-goeswith")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-base-korean-ud-goeswith") model = AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-base-korean-ud-goeswith", device_map="auto") - Notebooks
- Google Colab
- Kaggle
roberta-base-korean-ud-goeswith
Model Description
This is a RoBERTa model pre-trained on Korean texts for POS-tagging and dependency-parsing (using goeswith for subwords), derived from roberta-base-korean-hanja.
How to Use
from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/roberta-base-korean-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("홍시 맛이 나서 홍시라 생각한다."))
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Model tree for KoichiYasuoka/roberta-base-korean-ud-goeswith
Base model
klue/roberta-base Finetuned
KoichiYasuoka/roberta-base-korean-hanja