diff --git a/docs/my-website/docs/proxy/load_balancing.md b/docs/my-website/docs/proxy/load_balancing.md
index 0e1f58662cb..a73cfe33211 100644
--- a/docs/my-website/docs/proxy/load_balancing.md
+++ b/docs/my-website/docs/proxy/load_balancing.md
@@ -3,38 +3,39 @@
 Load balance multiple instances of the same model
 
 The proxy will handle routing requests (using LiteLLM's Router). **Set `rpm` in the config if you want maximize throughput**
+## Quick Start - Load Balancing
+### Step 1 - Set deployments on config
 
-#### Example config
-requests with `model=gpt-3.5-turbo` will be routed across multiple instances of `azure/gpt-3.5-turbo`
+**Example config below**. Here requests with `model=gpt-3.5-turbo` will be routed across multiple instances of `azure/gpt-3.5-turbo`
 ```yaml
 model_list:
   - model_name: gpt-3.5-turbo
     litellm_params:
-      model: azure/gpt-turbo-small-eu
-      api_base: https://my-endpoint-europe-berri-992.openai.azure.com/
-      api_key: 
+      model: azure/<your-deployment-name>
+      api_base: <your-azure-endpoint>
+      api_key: <your-azure-api-key>
       rpm: 6      # Rate limit for this deployment: in requests per minute (rpm)
   - model_name: gpt-3.5-turbo
     litellm_params:
       model: azure/gpt-turbo-small-ca
       api_base: https://my-endpoint-canada-berri992.openai.azure.com/
-      api_key: 
+      api_key: <your-azure-api-key>
       rpm: 6
   - model_name: gpt-3.5-turbo
     litellm_params:
       model: azure/gpt-turbo-large
       api_base: https://openai-france-1234.openai.azure.com/
-      api_key: 
+      api_key: <your-azure-api-key>
       rpm: 1440
 ```
 
-#### Step 2: Start Proxy with config
+### Step 2: Start Proxy with config
 
 ```shell
 $ litellm --config /path/to/config.yaml
 ```
 
-#### Step 3: Use proxy
+### Step 3: Use proxy - Call a model group [Load Balancing]
 Curl Command
 ```shell
 curl --location 'http://0.0.0.0:8000/chat/completions' \
@@ -51,7 +52,28 @@ curl --location 'http://0.0.0.0:8000/chat/completions' \
 '
 ```
 
-### Fallbacks + Cooldowns + Retries + Timeouts 
+### Usage - Call a specific model deployment
+If you want to call a specific model defined in the `config.yaml`, you can call the `litellm_params: model`
+
+In this example it will call `azure/gpt-turbo-small-ca`. Defined in the config on Step 1
+
+```bash
+curl --location 'http://0.0.0.0:8000/chat/completions' \
+--header 'Content-Type: application/json' \
+--data ' {
+      "model": "azure/gpt-turbo-small-ca",
+      "messages": [
+        {
+          "role": "user",
+          "content": "what llm are you"
+        }
+      ],
+    }
+'
+```
+
+
+## Fallbacks + Cooldowns + Retries + Timeouts 
 
 If a call fails after num_retries, fall back to another model group.
 
@@ -122,7 +144,7 @@ model_list:
       api_base: https://my-endpoint-europe-berri-992.openai.azure.com/
       api_key: <your-key>
       timeout: 0.1                      # timeout in (seconds)
-      stream_timeout: 0.01              # timeout stream requests (seconds)
+      stream_timeout: 0.01              # timeout for stream requests (seconds)
       max_retries: 5
   - model_name: gpt-3.5-turbo
     litellm_params:
@@ -130,7 +152,7 @@ model_list:
       api_base: https://my-endpoint-canada-berri992.openai.azure.com/
       api_key: 
       timeout: 0.1                      # timeout in (seconds)
-      stream_timeout: 0.01              # timeout stream requests (seconds)
+      stream_timeout: 0.01              # timeout for stream requests (seconds)
       max_retries: 5
 
 ```