metadata

license: apache-2.0
datasets:
  - CodeTed/CGEDit_dataset
language:
  - zh
metrics:
  - accuracy
library_name: transformers
tags:
  - CGED
  - CSC
pipeline_tag: text2text-generation

CGEDit - Chinese Grammatical Error Diagnosis by Task-Specific Instruction Tuning

Try the model from this space "Chinese Grammarly".

This model was obtained by fine-tuning the corresponding ClueAI/PromptCLUE-base-v1-5 model on the CoEdIT dataset.

Model Details

Model Description

Language(s) (NLP): Chinese
Finetuned from model: ClueAI/PromptCLUE-base-v1-5

Model Sources

Repository: https://github.com/TedYeh/Chinese_spelling_Correction

Usage

from transformers import AutoTokenizer, T5ForConditionalGeneration

tokenizer = AutoTokenizer.from_pretrained("CodeTed/Chinese_Grammarly")
model = T5ForConditionalGeneration.from_pretrained("CodeTed/Chinese_Grammarly")
input_text = '糾正句子裡的錯字: 看完那段文張，我是反對的！'
input_ids = tokenizer(input_text, return_tensors="pt").input_ids
outputs = model.generate(input_ids, max_length=256)
edited_text = tokenizer.decode(outputs[0], skip_special_tokens=True)