Update documentation from main repository

Author: future-xy

docs/stable/features/live_migration.md

@@ -19,7 +19,7 @@ To run this example, we will use Docker Compose to set up a ServerlessLLM cluste
 - **At least 20 GB of host memory** (this can be adjusted by using smaller models).
 - **ServerlessLLM version 0.6**: Ensure you have `sllm==0.6` and `sllm-store==0.6` installed.
 
-##
+## Usage
 
 Start a local Docker-based ray cluster using Docker Compose.
 

docs/stable/features/peft_lora_serving.md

@@ -3,23 +3,36 @@ sidebar_position: 2
 ---
 # PEFT LoRA Serving
 
+This example illustrates the process of deploying and serving a base large language model enhanced with LoRA (Low-Rank Adaptation) adapters in a ServerlessLLM cluster. It demonstrates how to start the cluster, deploy a base model with multiple LoRA adapters, perform inference using different adapters, and update or remove the adapters dynamically.
+
 ## Pre-requisites
 
 To run this example, we will use Docker Compose to set up a ServerlessLLM cluster. Before proceeding, please ensure you have read the [Quickstart Guide](../getting_started.md).
 
-We will use the following example base model & LoRA adapter
+We will use the following example base model & LoRA adapters
 - Base model: `facebook/opt-125m`
-- LoRA adapter: `peft-internal-testing/opt-125m-dummy-lora`
+- LoRA adapters:
+    - `peft-internal-testing/opt-125m-dummy-lora`
+    - `monsterapi/opt125M_alpaca`
+    - `edbeeching/opt-125m-lora`
+    - `Hagatiana/opt-125m-lora`
 
 ## Usage
 
 Start a local Docker-based ray cluster using Docker Compose.
 
-### Step 1: Clone the ServerlessLLM Repository
+### Step 1: Download the Docker Compose File
 
-If you haven't already, clone the ServerlessLLM repository:
+Download the `docker-compose.yml` file from the ServerlessLLM repository:
 ```bash
-git clone https://github.com/ServerlessLLM/ServerlessLLM.git
+# Create a directory for the ServerlessLLM Docker setup
+mkdir serverless-llm-docker && cd serverless-llm-docker
+
+# Download the docker-compose.yml file
+curl -O https://raw.githubusercontent.com/ServerlessLLM/ServerlessLLM/main/examples/docker/docker-compose.yml
+
+# Alternatively, you can use wget:
+# wget https://raw.githubusercontent.com/ServerlessLLM/ServerlessLLM/main/examples/docker/docker-compose.yml
 ```
 
 ### Step 2: Configuration
@@ -87,10 +100,8 @@ curl $LLM_SERVER_URL/v1/chat/completions \
 ```
 ### Step 5: Update LoRA Adapters
 If you wish to switch to a different set of LoRA adapters, you can still use `sllm-cli deploy` command with updated adapter configurations. ServerlessLLM will automatically reload the new adapters without restarting the backend.
-
-For example, to update the adapter (located at `ft_facebook/opt-125m_adapter1`) used by facebook/opt-125m:
 ```bash
-sllm-cli deploy --model facebook/opt-125m --backend transformers --enable-lora --lora-adapters demo_lora=ft_facebook/opt-125m_adapter1
+sllm-cli deploy --model facebook/opt-125m --backend transformers --enable-lora --lora-adapters demo-lora1=edbeeching/opt-125m-lora demo-lora2=Hagatiana/opt-125m-lora
 ```
 
 ### Step 6: Clean Up