diff --git a/.github/workflows/test-example-notebooks.yml b/.github/workflows/test-example-notebooks.yml
new file mode 100644
index 00000000..b3c8922d
--- /dev/null
+++ b/.github/workflows/test-example-notebooks.yml
@@ -0,0 +1,33 @@
+name: Test Example Notebooks
+
+on:
+  pull_request:
+    branches: ["master"]
+
+jobs:
+  api-docs:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - name: Setup Python
+        uses: actions/setup-python@v1
+        with:
+          python-version: "3.8"
+
+      - name: Upgrade Pip
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install setuptools wheel
+
+      - name: Setup Linux
+        run: |
+          sudo apt-get install -y cmake libsndfile1
+
+      - name: Install test dependencies
+        run: pip install pytest nbmake ipywidgets
+
+      - name: Test example notebooks
+        run: pytest --nbmake --nbmake-timeout=3000 docs/examples/**/*ipynb
diff --git a/docs/getting_started/installation.md b/docs/getting_started/installation.md
index 70809174..fcd0fafe 100644
--- a/docs/getting_started/installation.md
+++ b/docs/getting_started/installation.md
@@ -42,10 +42,10 @@ The requirements for additional functionality are separated out so that users ar
 If your machine has a GPU to accelerate the training process, make sure you install a GPU-enabled version of PyTorch before installing Ludwig:
 
 ``` sh
-pip install torch -f https://download.pytorch.org/whl/cu113/torch_stable.html
+pip install torch -f https://download.pytorch.org/whl/cu118/torch_stable.html
 ```
 
-The example above will install the latest version of PyTorch with CUDA 11.3. See the official [PyTorch docs](https://pytorch.org/get-started/locally/) for
+The example above will install the latest version of PyTorch with CUDA 11.8. See the official [PyTorch docs](https://pytorch.org/get-started/locally/) for
 more details on installing the right version of PyTorch for your environment.
 
 # Docker { #with-docker }