diff --git a/docs/tutorials/8a_train_sqil_sac.ipynb b/docs/tutorials/8a_train_sqil_sac.ipynb
index 942f8a290..7eadebaa5 100644
--- a/docs/tutorials/8a_train_sqil_sac.ipynb
+++ b/docs/tutorials/8a_train_sqil_sac.ipynb
@@ -7,14 +7,14 @@
     "[download this notebook here](https://github.com/HumanCompatibleAI/imitation/blob/master/docs/tutorials/8a_train_sqil_sac.ipynb)\n",
     "# Train an Agent using Soft Q Imitation Learning with SAC\n",
     "\n",
-    "In the previous tutorial, we used Soft Q Imitation Learning ([SQIL](https://arxiv.org/abs/1905.11108)) on top of the DQN base algorithm. In fact, SQIL can be combined with any off-policy algorithm from `stable_baselines3`. Here, we train a HalfCheetah agent using SQIL + SAC."
+    "In the previous tutorial, we used Soft Q Imitation Learning ([SQIL](https://arxiv.org/abs/1905.11108)) on top of the DQN base algorithm. In fact, SQIL can be combined with any off-policy algorithm from `stable_baselines3`. Here, we train a Pendulum agent using SQIL + SAC."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "First, we need some expert trajectories in our environment (`seals/HalfCheetah-v0`).\n",
+    "First, we need some expert trajectories in our environment (`Pendulum-v1`).\n",
     "Note that you can use other environments, but the action space must be continuous."
    ]
   },
@@ -28,7 +28,7 @@
     "from imitation.data import huggingface_utils\n",
     "\n",
     "# Download some expert trajectories from the HuggingFace Datasets Hub.\n",
-    "dataset = datasets.load_dataset(\"HumanCompatibleAI/ppo-seals-HalfCheetah-v0\")\n",
+    "dataset = datasets.load_dataset(\"HumanCompatibleAI/ppo-Pendulum-v1\")\n",
     "\n",
     "# Convert the dataset to a format usable by the imitation library.\n",
     "expert_trajectories = huggingface_utils.TrajectoryDatasetSequence(dataset[\"train\"])"
@@ -75,12 +75,11 @@
     "from imitation.util.util import make_vec_env\n",
     "import numpy as np\n",
     "from stable_baselines3 import sac\n",
-    "import seals  # noqa: F401  # needed to load \"seals/\" environments\n",
     "\n",
     "SEED = 42\n",
     "\n",
     "venv = make_vec_env(\n",
-    "    \"seals/HalfCheetah-v1\",\n",
+    "    \"Pendulum-v1\",\n",
     "    rng=np.random.default_rng(seed=SEED),\n",
     ")\n",
     "\n",