Update code snippets in README

README.md

@@ -24,30 +24,30 @@ Using this convenience API, requesting text completion from an already
 loaded LLM is as straightforward as:
 
 ```python
-import lmstudio as lm
+import lmstudio as lms
 
-llm = lm.llm()
-llm.complete("Once upon a time,")
+model = lms.llm()
+model.complete("Once upon a time,")
 ```
 
 Requesting a chat response instead only requires the extra step of
 setting up a `Chat` helper to manage the chat history and include
 it in response prediction requests:
 
 ```python
-import lmstudio as lm
+import lmstudio as lms
 
 EXAMPLE_MESSAGES = (
     "My hovercraft is full of eels!",
     "I will not buy this record, it is scratched."
 )
 
-llm = lm.llm()
-chat = lm.Chat("You are a helpful shopkeeper assisting a foreign traveller")
+model = lms.llm()
+chat = lms.Chat("You are a helpful shopkeeper assisting a foreign traveller")
 for message in EXAMPLE_MESSAGES:
     chat.add_user_message(message)
     print(f"Customer: {message}")
-    response = llm.respond(chat)
+    response = model.respond(chat)
     chat.add_assistant_response(response)
     print(f"Shopkeeper: {response}")
 ```