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KoichiYasuoka
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roberta-classical-chinese-base-ud-goeswith

Token Classification
Transformers
PyTorch
Literary Chinese
roberta
classical chinese
literary chinese
ancient chinese
pos
dependency-parsing
Inference Endpoints
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roberta-classical-chinese-base-ud-goeswith / README.md
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metadata
language:
  - lzh
tags:
  - classical chinese
  - literary chinese
  - ancient chinese
  - token-classification
  - pos
  - dependency-parsing
base_model: KoichiYasuoka/roberta-classical-chinese-base-char
datasets:
  - universal_dependencies
license: apache-2.0
pipeline_tag: token-classification
widget:
  - text: 孟子見梁惠王

roberta-classical-chinese-base-ud-goeswith

Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing (using goeswith for subwords), derived from roberta-classical-chinese-base-char and UD_Classical_Chinese-Kyoto.

How to Use 

from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/roberta-classical-chinese-base-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("孟子見梁惠王"))

Reference

Koichi Yasuoka: Sequence-Labeling RoBERTa Model for Dependency-Parsing in Classical Chinese and Its Application to Vietnamese and Thai, ICBIR 2023: 8th International Conference on Business and Industrial Research (May 2023), pp.169-173.