roberta-classical-chinese-large-upos

Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging, derived from roberta-classical-chinese-large-char. Every word is tagged by UPOS (Universal Part-Of-Speech).

How to Use

import torch
from transformers import AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
s="子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎"
p=[model.config.id2label[q] for q in torch.argmax(model(tokenizer.encode(s,return_tensors="pt"))[0],dim=2)[0].tolist()[1:-1]]
print(list(zip(s,p)))

Reference

See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models

New

Select AutoNLP in the “Train” menu to fine-tune this model automatically.

Downloads last month
135
Hosted inference API
Token Classification
This model can be loaded on the Inference API on-demand.