addressing doc comments

docs/inference.md

@@ -41,35 +41,42 @@ model.resize_token_embeddings(model.config.vocab_size + 1)
 ```
 Padding would be required for batch inference. In this this [example](../inference/inference.py), batch size = 1 so essentially padding is not required. However,We added the code pointer as an example in case of batch inference.
 
+**Chat completion**
+The inference folder also includes a chat completion example, that adds built-in safety features in fine-tuned models to the prompt tokens. To run the example:
+
+```bash
+python inference/chat_completion.py --model_name "PATH/TO/MODEL/7B/" --prompt_file inference/chats.json  --quantization --use_auditnlg
+
+```
 **Code Llama**
 
 Code llama was recently released with three flavors, base-model that support multiple programming languages, Python fine-tuned model and an instruction fine-tuned and aligned variation of Code Llama, please read more [here](https://ai.meta.com/blog/code-llama-large-language-model-coding/).
 
 Find the scripts to run Code Llama [here](../inference/code-llama/), where there are two examples of running code completion and infilling.
 
-**Note** Please find the right model on HF side [here](https://huggingface.co/codellama).
+**Note** Please find the right model on HF side [here](https://huggingface.co/codellama). 
 
-To run the code completion example:
+Make sure to install Transfromers from source for now
 
 ```bash
 
-python code_completion_example.py --model_name MODEL_NAME  --prompt_file code_completion_prompt.txt --temperature 0.2 --top_p 0.9
+pip install git+https://github.com/huggingface/transformers
 
 ```
 
-To run the code infilling example:
+To run the code completion example:
 
 ```bash
 
-python code_infilling_example.py --model_name MODEL_NAME --prompt_file code_infilling_prompt.txt --temperature 0.2 --top_p 0.9
+python code_completion_example.py --model_name MODEL_NAME  --prompt_file code_completion_prompt.txt --temperature 0.2 --top_p 0.9
 
 ```
 
-**Chat completion**
-The inference folder also includes a chat completion example, that adds built-in safety features in fine-tuned models to the prompt tokens. To run the example:
+To run the code infilling example:
 
 ```bash
-python inference/chat_completion.py --model_name "PATH/TO/MODEL/7B/" --prompt_file inference/chats.json  --quantization --use_auditnlg
+
+python code_infilling_example.py --model_name MODEL_NAME --prompt_file code_infilling_prompt.txt --temperature 0.2 --top_p 0.9
 
 ```