From fed2df4c3e13dd167f78b32c45198886c118172b Mon Sep 17 00:00:00 2001
From: jnanliu <to.liujn@outlook.com>
Date: Tue, 25 Feb 2025 09:29:16 +0000
Subject: [PATCH] fix multi-line equation

---
 docs/en/user_guides/datasets.md    | 2 +-
 docs/zh_cn/user_guides/datasets.md | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/en/user_guides/datasets.md b/docs/en/user_guides/datasets.md
index 8f157cd7..571325ee 100644
--- a/docs/en/user_guides/datasets.md
+++ b/docs/en/user_guides/datasets.md
@@ -102,7 +102,7 @@ afqmc_datasets = [
 ```
 
 > [!TIP]
-> Additionally, for binary evaluation metrics (such as accuracy, pass-rate, etc.), you can also set the parameter `k` in conjunction with `n` for [G-Pass@$k$](http://arxiv.org/abs/2412.13147) evaluation. The formula for G-Pass@$k$ is: $$\text{G-Pass@}k_\tau=\mathbb{E}_{\text{Data}}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right],$$ where $n$ is the number of evaluations, and $c$ is the number of times that passed or were correct out of $n$ runs. An example configuration is as follows:
+> Additionally, for binary evaluation metrics (such as accuracy, pass-rate, etc.), you can also set the parameter `k` in conjunction with `n` for [G-Pass@ $k$ ](http://arxiv.org/abs/2412.13147) evaluation. The formula for G-Pass@$k$ is: $$ \text{G-Pass@}k_\tau=\mathbb{E}_{\text{Data}}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right], $$ where $n$ is the number of evaluations, and $c$ is the number of times that passed or were correct out of $n$ runs. An example configuration is as follows:
 
 ```python
 aime2024_datasets = [
diff --git a/docs/zh_cn/user_guides/datasets.md b/docs/zh_cn/user_guides/datasets.md
index b2a5587f..e0808a59 100644
--- a/docs/zh_cn/user_guides/datasets.md
+++ b/docs/zh_cn/user_guides/datasets.md
@@ -101,7 +101,7 @@ afqmc_datasets = [
 ```
 
 > [!TIP]
-> 另外，对于二值评测指标（例如accuracy，pass-rate等），还可以通过设置参数`k`配合`n`进行[G-Pass@$k$](http://arxiv.org/abs/2412.13147)评测。G-Pass@$k$计算公式为：$ \text{G-Pass@}k_\tau=\mathbb{E}_{\text{Data}}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right], $ 其中 $n$ 为评测次数, $c$ 为 $n$ 次运行中通过或正确的次数。配置例子如下：
+> 另外，对于二值评测指标（例如accuracy，pass-rate等），还可以通过设置参数`k`配合`n`进行[G-Pass@ $k$ ](http://arxiv.org/abs/2412.13147)评测。G-Pass@$k$计算公式为： $$\text{G-Pass@}k_\tau=\mathbb{E}_{\text{Data}}\left[ \sum_{j=\lceil \tau \cdot k \rceil}^c \frac{{c \choose j} \cdot {n - c \choose k - j}}{{n \choose k}} \right], $$ 其中 $n$ 为评测次数, $c$ 为 $n$ 次运行中通过或正确的次数。配置例子如下：
 
 ```python
 aime2024_datasets = [