diff --git a/notebooks/unit6/unit6.ipynb b/notebooks/unit6/unit6.ipynb
index b797060..01b6802 100644
--- a/notebooks/unit6/unit6.ipynb
+++ b/notebooks/unit6/unit6.ipynb
@@ -5,7 +5,6 @@
     "colab": {
       "provenance": [],
       "private_outputs": true,
-      "authorship_tag": "ABX9TyPDFLK3trc6MCLJLqUUuAbl",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -36,7 +35,7 @@
         "\n",
         "<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit8/thumbnail.png\"  alt=\"Thumbnail\"/>\n",
         "\n",
-        "In this notebook, you'll learn to use A2C with PyBullet and Panda-Gym, two set of robotics environments. \n",
+        "In this notebook, you'll learn to use A2C with PyBullet and Panda-Gym, two set of robotics environments.\n",
         "\n",
         "With [PyBullet](https://github.com/bulletphysics/bullet3), you're going to **train a robot to move**:\n",
         "- `AntBulletEnv-v0` 🕸️ More precisely, a spider (they say Ant but come on... it's a spider 😆) 🕸️\n",
@@ -62,12 +61,12 @@
     {
       "cell_type": "markdown",
       "source": [
-        "### 🎮 Environments: \n",
+        "### 🎮 Environments:\n",
         "\n",
         "- [PyBullet](https://github.com/bulletphysics/bullet3)\n",
         "- [Panda-Gym](https://github.com/qgallouedec/panda-gym)\n",
         "\n",
-        "###📚 RL-Library: \n",
+        "###📚 RL-Library:\n",
         "\n",
         "- [Stable-Baselines3](https://stable-baselines3.readthedocs.io/)"
       ],
@@ -112,7 +111,7 @@
         "\n",
         "- 📖 Study Deep Reinforcement Learning in **theory and practice**.\n",
         "- 🧑‍💻 Learn to **use famous Deep RL libraries** such as Stable Baselines3, RL Baselines3 Zoo, CleanRL and Sample Factory 2.0.\n",
-        "- 🤖 Train **agents in unique environments** \n",
+        "- 🤖 Train **agents in unique environments**\n",
         "\n",
         "And more check 📚 the syllabus 👉 https://simoninithomas.github.io/deep-rl-course\n",
         "\n",
@@ -192,7 +191,7 @@
       "source": [
         "## Create a virtual display 🔽\n",
         "\n",
-        "During the notebook, we'll need to generate a replay video. To do so, with colab, **we need to have a virtual screen to be able to render the environment** (and thus record the frames). \n",
+        "During the notebook, we'll need to generate a replay video. To do so, with colab, **we need to have a virtual screen to be able to render the environment** (and thus record the frames).\n",
         "\n",
         "Hence the following cell will install the librairies and create and run a virtual screen 🖥"
       ],
@@ -266,7 +265,10 @@
       },
       "outputs": [],
       "source": [
-        "!pip install -r https://raw.githubusercontent.com/huggingface/deep-rl-class/main/notebooks/unit6/requirements-unit6.txt"
+        "!pip install stable-baselines3[extra]==1.8.0\n",
+        "!pip install huggingface_sb3\n",
+        "!pip install panda_gym==2.0.0\n",
+        "!pip install pyglet==1.5.1"
       ]
     },
     {
@@ -403,7 +405,7 @@
     {
       "cell_type": "markdown",
       "source": [
-        "A good practice in reinforcement learning is to [normalize input features](https://stable-baselines3.readthedocs.io/en/master/guide/rl_tips.html). \n",
+        "A good practice in reinforcement learning is to [normalize input features](https://stable-baselines3.readthedocs.io/en/master/guide/rl_tips.html).\n",
         "\n",
         "For that purpose, there is a wrapper that will compute a running average and standard deviation of input features.\n",
         "\n",
@@ -630,7 +632,7 @@
         "\n",
         "<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/create-token.jpg\" alt=\"Create HF Token\">\n",
         "\n",
-        "- Copy the token \n",
+        "- Copy the token\n",
         "- Run the cell below and paste the token"
       ]
     },
@@ -855,7 +857,7 @@
       "cell_type": "code",
       "source": [
         "# 6\n",
-        "model_name = \"a2c-PandaReachDense-v2\"; \n",
+        "model_name = \"a2c-PandaReachDense-v2\";\n",
         "model.save(model_name)\n",
         "env.save(\"vec_normalize.pkl\")\n",
         "\n",
@@ -927,4 +929,4 @@
       }
     }
   ]
-}
+}
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