modify title level

Author: refraction-ray

docs/source/tutorials/sklearn_svc.ipynb

@@ -7,7 +7,6 @@
     "# Support Vector Classification with SKLearn\n",
     "\n",
     "Authored by [_Mark (Zixuan) Song_](https://marksong.tech)\n",
-    "- - -\n",
     "\n",
     "We use the `SKLearn` library to implement `SVC` in the following tutorial."
    ]
@@ -16,7 +15,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Overview\n",
+    "## Overview\n",
     "\n",
     "The aim of this tutorial is to implant a quantum machine learning (QML) transformer into SVC pipeline. And this is a general introduction to connect `tensorcircuit` with `scikit-learn`."
    ]

docs/source/tutorials/sklearn_svc_cn.ipynb

@@ -7,7 +7,6 @@
     "# 结合SKLearn实现的支持向量分类\n",
     "\n",
     "[_Mark (Zixuan) Song_](https://marksong.tech) 撰写\n",
-    "- - -\n",
     "\n",
     "本示例结合了`sklearn`库中的`SVC`类，实现了支持向量分类。"
    ]
@@ -16,7 +15,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 概述\n",
+    "## 概述\n",
     "\n",
     "本示例的目的是将量子机器学习（QML）转换器嵌入到SVC管道中并且介绍`tensorcircuit`与`scikit-learn`的一种连接方式。"
    ]