encourage use of rapidsai/notebooks for some examples (#379)

rapidsai · Jun 4, 2024 · 8bd5b05 · 8bd5b05
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diff --git a/README.md b/README.md
@@ -128,10 +128,10 @@ The RAPIDS versions for things like container images and install instructions ar
 ```python
 versions = {
     "stable": {
-        "rapids_container": "nvcr.io/nvidia/rapidsai/rapidsai-core:23.02-cuda11.8-runtime-ubuntu22.04-py3.10",
+        "rapids_container": "nvcr.io/nvidia/rapidsai/base:24.04-cuda11.8-py3.10",
     },
     "nightly": {
-        "rapids_container": "rapidsai/rapidsai-core-nightly:23.04-cuda11.8-runtime-ubuntu22.04-py3.10",
+        "rapids_container": "rapidsai/base:24.06a-cuda11.8-py3.10",
     },
 }
 ```

diff --git a/source/_includes/install-rapids-with-docker.md b/source/_includes/install-rapids-with-docker.md
@@ -9,8 +9,8 @@ Then copy the commands shown:
 docker pull {{ rapids_container }}
 docker run --gpus all --rm -it \
     --shm-size=1g --ulimit memlock=-1 \
-    -p 8888:8888 -p 8787:8787 -p 8786:8786 \
-    {{ rapids_container }}
+    -p 8888:80 -p 8787:8787 -p 8786:8786 \
+    {{ rapids_notebooks_container }}
 ```
 
 ```{note}

diff --git a/source/_includes/test-rapids-docker-vm.md b/source/_includes/test-rapids-docker-vm.md
@@ -1,4 +1,6 @@
-In the terminal we can open `ipython` and check that we can import and use RAPIDS libraries like `cudf`.
+To access Jupyter, navigate to `<VM ip>:8888` in the browser.
+
+In a Python notebook, check that you can import and use RAPIDS libraries like `cudf`.
 
 ```ipython
 In [1]: import cudf
@@ -14,7 +16,6 @@ timestamp
 2000-01-01 00:00:04   998    Quinn  0.651381 -0.525398
 ```
 
-You can also access Jupyter via `<VM ip>:8888` in the browser.
-Visit `cudf/10-min.ipynb` and execute the cells to try things out.
+Open `cudf/10min.ipynb` and execute the cells to explore more of how `cudf` works.
 
 When running a Dask cluster you can also visit `<VM ip>:8787` to monitor the Dask cluster status.
diff --git a/source/examples/rapids-autoscaling-multi-tenant-kubernetes/notebook.ipynb b/source/examples/rapids-autoscaling-multi-tenant-kubernetes/notebook.ipynb
@@ -222,9 +222,9 @@
     "In order to steam the container image to the GKE nodes our image needs to be stored in [Google Cloud Artifact Registry](https://cloud.google.com/artifact-registry/) in the same region as our cluster.\n",
     "\n",
     "```console\n",
-    "$ docker pull rapidsai/rapidsai-core:23.02-cuda11.8-runtime-ubuntu22.04-py3.10\n",
+    "$ docker pull rapidsai/base:24.04-cuda11.8-py3.10\n",
     "\n",
-    "$ docker tag rapidsai/rapidsai-core:23.02-cuda11.8-runtime-ubuntu22.04-py3.10 REGION-docker.pkg.dev/PROJECT/REPO/IMAGE:TAG\n",
+    "$ docker tag rapidsai/base:24.04-cuda11.8-py3.10 REGION-docker.pkg.dev/PROJECT/REPO/IMAGE:TAG\n",
     "\n",
     "$ docker push REGION-docker.pkg.dev/PROJECT/REPO/IMAGE:TAG\n",
     "```\n",