Update README.md

README.md

@@ -1,3 +1,39 @@
----
-license: mit
----
+---
+license: mit
+---
+## Usage (HuggingFace Transformers)
+Without [ChineseErrorCorrector](https://github.com/TW-NLP/ChineseErrorCorrector/tree/0.1.0), 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 = "twnlp/ChineseErrorCorrector-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 = "你是一个拼写纠错专家，对原文进行错别字纠正，不要更改原文字数，原文为：\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。
+```