diff --git a/README.md b/README.md
index f5fd8345..7ba2b748 100644
--- a/README.md
+++ b/README.md
@@ -7,6 +7,7 @@
 [![Downloads](https://static.pepy.tech/badge/llmtuner)](https://pypi.org/project/llmtuner/)
 [![GitHub pull request](https://img.shields.io/badge/PRs-welcome-blue)](https://github.com/hiyouga/LLaMA-Factory/pulls)
 [![Discord](https://dcbadge.vercel.app/api/server/c2EPEt5NU?compact=true&style=flat)](https://discord.gg/c2EPEt5NU)
+[![Spaces](https://img.shields.io/badge/🤗-Open%20In%20Spaces-blue)](https://huggingface.co/spaces/hiyouga/LLaMA-Board)
 
 👋 Join our [WeChat](assets/wechat.jpg).
 
@@ -14,7 +15,7 @@
 
 ## LLaMA Board: A One-stop Web UI for Getting Started with LLaMA Factory
 
-Preview LLaMA Board at **[Hugging Face Space](https://huggingface.co/spaces/hiyouga/LLaMA-Board)**.
+Preview LLaMA Board at **[🤗 Spaces](https://huggingface.co/spaces/hiyouga/LLaMA-Board)**.
 
 Launch LLaMA Board via `CUDA_VISIBLE_DEVICES=0 python src/train_web.py`. (multiple GPUs are not supported yet)
 
diff --git a/README_zh.md b/README_zh.md
index 42aa70fc..dbcee80a 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -7,6 +7,7 @@
 [![Downloads](https://static.pepy.tech/badge/llmtuner)](https://pypi.org/project/llmtuner/)
 [![GitHub pull request](https://img.shields.io/badge/PRs-welcome-blue)](https://github.com/hiyouga/LLaMA-Factory/pulls)
 [![Discord](https://dcbadge.vercel.app/api/server/c2EPEt5NU?compact=true&style=flat)](https://discord.gg/c2EPEt5NU)
+[![Spaces](https://img.shields.io/badge/🤗-Open%20In%20Spaces-blue)](https://huggingface.co/spaces/hiyouga/LLaMA-Board)
 
 👋 加入我们的[微信群](assets/wechat.jpg)。
 
@@ -14,9 +15,9 @@
 
 ## LLaMA Board: 通过一站式网页界面快速上手 LLaMA Factory
 
-通过 **[Hugging Face Space](https://huggingface.co/spaces/hiyouga/LLaMA-Board)** 预览 LLaMA Board。
+通过 **[🤗 Spaces](https://huggingface.co/spaces/hiyouga/LLaMA-Board)** 预览 LLaMA Board。
 
-使用 `CUDA_VISIBLE_DEVICES=0 python src/train_web.py` 启动 LLaMA Board。（该界面目前仅支持单卡训练）
+使用 `CUDA_VISIBLE_DEVICES=0 python src/train_web.py` 启动 LLaMA Board。（该模式目前仅支持单卡训练）
 
 下面是使用单张 GPU 在 10 分钟内更改对话式大型语言模型自我认知的示例。