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）
Table with columns: Model Name, Base Model, Avg, SIGHAN-2015, EC-LAW, MCSC, GPU, QPS| Model Name | Base Model | Avg | SIGHAN-2015 | EC-LAW | MCSC | GPU | QPS |
|---|
| ChatGLM3-6B-CSC | THUDM/chatglm3-6b | 0.4538 | 0.6572 | 0.4369 | 0.2672 | GPU | 3 |
| Qwen2.5-1.5B-CTC | Qwen/Qwen2.5-1.5B-Instruct | 0.6802 | 0.3032 | 0.7846 | 0.9529 | GPU | 6 |
| Qwen2.5-7B-CTC | Qwen/Qwen2.5-7B-Instruct | 0.8225 | 0.4917 | 0.9798 | 0.9959 | GPU | 3 |
| Qwen3-4B-CTC(Our) | Qwen/Qwen3-4B | 0.8521 | 0.6340 | 0.9360 | 0.9864 | GPU | 5 |
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
)
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)
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},
}
