diff --git a/README.md b/README.md
index 039ed97..8bb016b 100644
--- a/README.md
+++ b/README.md
@@ -65,6 +65,9 @@
 [25/07/10] Data source added Telegram   
 [25/06/05] Support for image modal data fine-tuning    
 
+### Online Fine-Tuning
+- Big Model Lab (Lab4AI) (with 50 CNY voucher): https://www.lab4ai.cn/project/detail?utm_source=weclone1&id=ab83d14684fa45d197f67eddb3d8316c&type=project
+
 ### Hardware Requirements
 
 The project uses Qwen2.5-VL-7B-Instruct model by default with LoRA method for SFT stage fine-tuning. You can also use other models and methods supported by [LLaMA Factory](https://github.com/hiyouga/LLaMA-Factory/tree/main#supported-models).
diff --git a/README_zh.md b/README_zh.md
index f8ceb64..900d527 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -63,6 +63,9 @@
 [25/06/05]支持图片模态数据微调   
 [25/07/10]数据源增加Telegram
 
+### 在线微调
+- 大模型实验室 (Lab4AI) (送50元代金券): https://www.lab4ai.cn/project/detail?utm_source=weclone1&id=ab83d14684fa45d197f67eddb3d8316c&type=project
+
 ### 硬件要求
 
 项目默认使用Qwen2.5-7B-Instruct模型，LoRA方法对sft阶段微调，大约需要16GB显存。也可以使用[LLaMA Factory](https://github.com/hiyouga/LLaMA-Factory/blob/main/README_zh.md#%E6%A8%A1%E5%9E%8B)支持的其他模型和方法。