Update README.md

README.md

@@ -1,3 +1,153 @@
----
-license: apache-2.0
----
+---
+library_name: transformers
+base_model: Qwen/Qwen2.5-7B-Instruct
+license: apache-2.0
+datasets:
+- shibing624/chinese_text_correction
+language:
+- zh
+metrics:
+- f1
+tags:
+- text-generation-inference
+widget:
+- text: "文本纠错：\n少先队员因该为老人让坐。"
+---
+
+
+
+# Chinese Text Correction Model
+中文文本纠错模型chinese-text-correction-7b：用于拼写纠错、语法纠错
+
+`shibing624/chinese-text-correction-7b` evaluate test data：
+
+The overall performance of CSC **test**:
+
+|input_text|predict_text|
+|:--- |:--- |
+|文本纠错：\n少先队员因该为老人让坐。|少先队员应该为老人让座。|
+
+# Models
+
+| Name            |  Base Model   | Download                        |
+|-----------------|-------------------|-----------------------------------------------------------------------|
+| chinese-text-correction-1.5b  |  Qwen/Qwen2.5-1.5B-Instruct             | [🤗 Hugging Face](https://huggingface.co/shibing624/chinese-text-correction-1.5b)  |
+| chinese-text-correction-1.5b-lora  |  Qwen/Qwen2.5-1.5B-Instruct             | [🤗 Hugging Face](https://huggingface.co/shibing624/chinese-text-correction-1.5b-lora)  |
+| chinese-text-correction-7b   |  Qwen/Qwen2.5-7B-Instruct             | [🤗 Hugging Face](https://huggingface.co/shibing624/chinese-text-correction-7b)  |
+| chinese-text-correction-7b-lora  |  Qwen/Qwen2.5-7B-Instruct             | [🤗 Hugging Face](https://huggingface.co/shibing624/chinese-text-correction-7b-lora)  |
+
+
+
+## Usage (pycorrector)
+
+本项目开源在`pycorrector`项目：[pycorrector](https://github.com/shibing624/pycorrector)，可支持大模型微调后用于文本纠错，通过如下命令调用：
+
+Install package:
+```shell
+pip install -U pycorrector
+```
+
+```python
+from pycorrector.gpt.gpt_corrector import GptCorrector
+
+if __name__ == '__main__':
+    error_sentences = [
+        '真麻烦你了。希望你们好好的跳无',
+        '少先队员因该为老人让坐',
+        '机七学习是人工智能领遇最能体现智能的一个分知',
+        '一只小鱼船浮在平净的河面上',
+        '我的家乡是有明的渔米之乡',
+    ]
+    m = GptCorrector("shibing624/chinese-text-correction-7b")
+
+    batch_res = m.correct_batch(error_sentences)
+    for i in batch_res:
+        print(i)
+        print()
+```
+
+## Usage (HuggingFace Transformers)
+Without [pycorrector](https://github.com/shibing624/pycorrector), you can use the model like this: 
+
+First, you pass your input through the transformer model, then you get the generated sentence.
+
+Install package:
+```
+pip install transformers 
+```
+
+```python
+# pip install transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+checkpoint = "shibing624/chinese-text-correction-7b"
+
+device = "cuda" # for GPU usage or "cpu" for CPU usage
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
+
+input_content = "文本纠错：\n少先队员因该为老人让坐。"
+
+messages = [{"role": "user", "content": input_content}]
+input_text=tokenizer.apply_chat_template(messages, tokenize=False)
+
+print(input_text)
+
+inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
+outputs = model.generate(inputs, max_new_tokens=1024, temperature=0, do_sample=False, repetition_penalty=1.08)
+
+print(tokenizer.decode(outputs[0]))
+```
+
+output:
+```shell
+少先队员应该为老人让座。
+```
+
+
+模型文件组成：
+```
+shibing624/chinese-text-correction-7b
+|-- added_tokens.json
+|-- config.json
+|-- generation_config.json
+|-- merges.txt
+|-- model.safetensors
+|-- model.safetensors.index.json
+|-- README.md
+|-- special_tokens_map.json
+|-- tokenizer_config.json
+|-- tokenizer.json
+`-- vocab.json
+```
+
+#### 训练参数：
+
+- num_epochs: 8
+- batch_size: 2
+- steps: 36000
+- eval_loss: 0.12
+- base model: Qwen/Qwen2.5-7B-Instruct
+- train data: [shibing624/chinese_text_correction](https://huggingface.co/datasets/shibing624/chinese_text_correction)
+- train time: 10 days
+- eval_loss: ![](https://huggingface.co/shibing624/chinese-text-correction-7b-lora/resolve/main/eval_loss_7b.png)
+- train_loss: ![](https://huggingface.co/shibing624/chinese-text-correction-7b-lora/resolve/main/train_loss_7b.png)
+
+### 训练数据集
+#### 中文纠错数据集
+
+- 数据：[shibing624/chinese_text_correction](https://huggingface.co/datasets/shibing624/chinese_text_correction)
+
+
+如果需要训练Qwen的纠错模型，请参考[https://github.com/shibing624/pycorrector](https://github.com/shibing624/pycorrector) 或者 [https://github.com/shibing624/MedicalGPT](https://github.com/shibing624/MedicalGPT)
+
+## Citation
+
+```latex
+@software{pycorrector,
+  author = {Xu Ming},
+  title = {pycorrector: Implementation of language model finetune},
+  year = {2024},
+  url = {https://github.com/shibing624/pycorrector},
+}
+```
+