diff --git a/docs/get-started/xgboost-examples/csp/databricks/init-notebook-for-rapids-spark-xgboost-on-databricks-gpu-7.0-ml.ipynb b/docs/get-started/xgboost-examples/csp/databricks/init-notebook-for-rapids-spark-xgboost-on-databricks-gpu-7.0-ml.ipynb
index eda2739aa..1046eafb4 100644
--- a/docs/get-started/xgboost-examples/csp/databricks/init-notebook-for-rapids-spark-xgboost-on-databricks-gpu-7.0-ml.ipynb
+++ b/docs/get-started/xgboost-examples/csp/databricks/init-notebook-for-rapids-spark-xgboost-on-databricks-gpu-7.0-ml.ipynb
@@ -131,8 +131,7 @@
     "\n",
     "1. Edit your cluster, adding an initialization script from `dbfs:/databricks/init_scripts/init.sh` in the \"Advanced Options\" under \"Init Scripts\" tab\n",
     "2. Reboot the cluster\n",
-    "3. Go to \"Libraries\" tab under your cluster and install `dbfs:/FileStore/jars/xgboost4j-spark_3.0-1.4.2-0.1.0.jar` in your cluster by selecting the \"DBFS\" option for installing jars\n",
-    "4. Import the mortgage example notebook from `https://github.com/NVIDIA/spark-rapids-examples/blob/branch-21.08/examples/mortgage/notebooks/python/mortgage-gpu.ipynb`\n",
+
     "5. Inside the mortgage example notebook, update the data paths\n",
     "  `train_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-train.csv')`\n",
     "  `trans_data = reader.schema(schema).option('header', True).csv('/data/mortgage/csv/small-trans.csv')`"
diff --git a/docs/get-started/xgboost-examples/on-prem-cluster/kubernetes.md b/docs/get-started/xgboost-examples/on-prem-cluster/kubernetes.md
index 8eaaa7f73..8c90ce775 100644
--- a/docs/get-started/xgboost-examples/on-prem-cluster/kubernetes.md
+++ b/docs/get-started/xgboost-examples/on-prem-cluster/kubernetes.md
@@ -26,7 +26,7 @@ Build a GPU Docker image with Spark resources in it, this Docker image must be a
 
 1. Locate your Spark installations. If you don't have one, you can [download](https://spark.apache.org/downloads.html) from Apache and unzip it.
 2. `export SPARK_HOME=<path to spark>`
-3. [Download the Dockerfile](/dockerfile/Dockerfile) into `${SPARK_HOME}` (Here CUDA 11.0 is used as an example in the Dockerfile, you may need to update it for other CUDA versions.)
+
 4. __(OPTIONAL)__ install any additional library jars into the `${SPARK_HOME}/jars` directory
     * Most public cloud file systems are not natively supported -- pulling data and jar files from S3, GCS, etc. require installing additional libraries
 5. Build and push the docker image
@@ -37,7 +37,7 @@ export SPARK_DOCKER_IMAGE=<gpu spark docker image repo and name>
 export SPARK_DOCKER_TAG=<spark docker image tag>
 
 pushd ${SPARK_HOME}
-wget https://github.com/NVIDIA/spark-rapids-examples/raw/branch-21.08/dockerfile/Dockerfile
+
 
 # Optionally install additional jars into ${SPARK_HOME}/jars/