ChineseErrorCorrector3-4B

🇨🇳中文 | English

ChineseErrorCorrector3-4B is part of a comprehensive platform for Chinese text correction, integrating academic research, model training, evaluation, and inference. It covers two core directions: Spelling Correction (CSC) and Grammatical Error Correction (CGEC).

The methodology behind this line of models is presented in the paper CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards.

• Project Page: ChineseErrorCorrector GitHub
• Paper: arXiv:2606.00020

模型描述

一个面向中文文本纠错任务的综合平台，集学术研究、模型训练、模型评测和推理部署于一体，覆盖拼写纠错与语法纠错两个核心方向。

• twnlp/ChineseErrorCorrector3-4B: 使用200万纠错数据进行全量训练，适用于语法纠错和拼写纠错，效果最好，推荐使用。

模型评测（NaCGEC Data）

Sample Usage

You can use the model with the transformers library as follows:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "twnlp/ChineseErrorCorrector3-4B"

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)

prompt = "你是一个文本纠错专家，纠正输入句子中的语法错误，并输出正确的句子，输入句子为："
text_input = "对待每一项工作都要一丝不够。"
messages = [
    {"role": "user", "content": prompt + text_input}
]
text = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True,
        enable_thinking=False # Switches between thinking and non-thinking modes. Default is True.
    )
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)

generated_ids = model.generate(
    **model_inputs,
    max_new_tokens=512
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(response)
# Output: 对待每一项工作都要一丝不苟。

Citation

If you find this work helpful, please cite:

@misc{tian2026csrpchainofthoughtreasoningchinese,
      title={CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards}, 
      author={Wei Tian and Yuhao Zhou and Man Lan},
      year={2026},
      eprint={2606.00020},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2606.00020}, 
}

@misc{tian2025chineseerrorcorrector34bstateoftheartchinesespelling,
      title={ChineseErrorCorrector3-4B: State-of-the-Art Chinese Spelling and Grammar Corrector},
      author={Wei Tian and YuhaoZhou},
      year={2025},
      eprint={2511.17562},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2511.17562},
}