Moved environment variable docs. (#203)

docs/_tutorials/getting-started.md

@@ -135,26 +135,6 @@ doc](/docs/config-json/).
 }
 ```
 
-## Multi-Node Environment Variables
-
-When training across multiple nodes we have found it useful to support
-propagating user-defined environment variables. By default DeepSpeed will
-propagate all NCCL and PYTHON related environment variables that are set. If
-you would like to propagate additional variables you can specify them in a
-dot-file named `.deepspeed_env` that contains a new-line separated list of
-`VAR=VAL` entries. The DeepSpeed launcher will look in the local path you are
-executing from and also in your home directory (`~/`).
-
-As a concrete example, some clusters require special NCCL variables to set
-prior to training. The user can simply add these variables to a
-`.deepspeed_env` file in their home directory that looks like this:
-```
-NCCL_IB_DISABLE=1
-NCCL_SOCKET_IFNAME=eth0
-```
-DeepSpeed will then make sure that these environment variables are set when
-launching each process on every node across their training job.
-
 # Launching DeepSpeed Training
 DeepSpeed installs the entry point `deepspeed` to launch distributed training.
 We illustrate an example usage of DeepSpeed with the following assumptions:
@@ -214,7 +194,28 @@ deepspeed --include="worker-2:0,1" \
 	<client_entry.py> <client args> \
 	--deepspeed --deepspeed_config ds_config.json
 ```
-This is a floating nav bar.
+
+## Multi-Node Environment Variables
+
+When training across multiple nodes we have found it useful to support
+propagating user-defined environment variables. By default DeepSpeed will
+propagate all NCCL and PYTHON related environment variables that are set. If
+you would like to propagate additional variables you can specify them in a
+dot-file named `.deepspeed_env` that contains a new-line separated list of
+`VAR=VAL` entries. The DeepSpeed launcher will look in the local path you are
+executing from and also in your home directory (`~/`).
+
+As a concrete example, some clusters require special NCCL variables to set
+prior to training. The user can simply add these variables to a
+`.deepspeed_env` file in their home directory that looks like this:
+```
+NCCL_IB_DISABLE=1
+NCCL_SOCKET_IFNAME=eth0
+```
+DeepSpeed will then make sure that these environment variables are set when
+launching each process on every node across their training job.
+
+
 ### MPI Compatibility
 As described above, DeepSpeed provides its own parallel launcher to help launch
 multi-node/multi-gpu training jobs. If you prefer to launch your training job