Update README.md

README.md

@@ -69,30 +69,16 @@ which means that lists of messages can be formatted for you with the `apply_chat
 
 ```python
 chat = [
-  {"role": "user", "content": "Hello, how are you?"},
-  {"role": "assistant", "content": "I'm doing great. How can I help you today?"},
-  {"role": "user", "content": "I'd like to show off how chat templating works!"},
+  {"role": "system", "content": "You are MistralOrca, a large language model trained by Alignment Lab AI. Write out your reasoning step-by-step to be sure you get the right answers!"}
+  {"role": "user", "content": "How are you?"},
+  {"role": "assistant", "content": "I am doing well!"},
+  {"role": "user", "content": "Please tell me about how mistral winds have attracted super-orcas."},
 ]
 tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
 ```
 
 which will yield:
 
-```
-<|im_start|>user
-Hello, how are you?<|im_end|>
-<|im_start|>assistant
-I'm doing great. How can I help you today?<|im_end|>
-<|im_start|>user
-I'd like to show off how chat templating works!<|im_end|>
-<|im_start|>assistant
-```
-
-If you use `tokenize=True` and `return_tensors="pt"` instead, then you will get a tokenized 
-and formatted conversation ready to pass to `model.generate()`.
-
-## Example Prompt Exchange
-
 ```
 <|im_start|>system
 You are MistralOrca, a large language model trained by Alignment Lab AI. Write out your reasoning step-by-step to be sure you get the right answers!
@@ -103,8 +89,12 @@ How are you?<|im_end|>
 I am doing well!<|im_end|>
 <|im_start|>user
 Please tell me about how mistral winds have attracted super-orcas.<|im_end|>
+<|im_start|>assistant
 ```
 
+If you use `tokenize=True` and `return_tensors="pt"` instead, then you will get a tokenized 
+and formatted conversation ready to pass to `model.generate()`.
+
 
 # Inference