Update README For Batch Usage

README.md

@@ -53,4 +53,32 @@ logits = outputs.logits
 id = torch.argmax(logits, dim=-1).item()
 response = ID2LABEL[id]
 print(response)
+# "非正文"
+```
+
+# For Batch Usage
+```python
+import torch
+from transformers import AutoModelForSequenceClassification
+from transformers import AutoTokenizer
+
+ID2LABEL = {0: "正文", 1: "非正文"}
+
+model_name = 'ytzfhqs/Qwen2.5-med-book-main-classification'
+model = AutoModelForSequenceClassification.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left")
+
+text = ['下列为修订说明','阴离子间隙是一项受到广泛重视的酸碱指标。AG是一个计算值，指血浆中未测定的阴离子与未测定的阳离子的差值，正常机体血浆中的阳离子与阴离子总量相等，均为151mmol/L，从而维持电荷平衡。']
+encoding = tokenizer(text, return_tensors='pt',padding=True)
+encoding = {k: v.to(model.device) for k, v in encoding.items()}
+outputs = model(**encoding)
+logits = outputs.logits
+ids = torch.argmax(logits, dim=-1).tolist()
+response = [ID2LABEL[id] for id in ids]
+print(response)
+# ['非正文', '正文']
 ```