Update README.md

README.md

@@ -64,8 +64,6 @@ The base model, Nemotron-4-340B, was trained with a global batch-size of 2304, a
 1. We will spin up an inference server and then call the inference server in a python script. Let’s first define the python script ``call_server.py``
 
 ```python
-
-
 headers = {"Content-Type": "application/json"}
 
 def text_generation(data, ip='localhost', port=None):
@@ -102,7 +100,8 @@ prompt = PROMPT_TEMPLATE.format(prompt=question)
 print(prompt)
 
 response = get_generation(prompt, greedy=True, add_BOS=False, token_to_gen=1024, min_tokens=1, temp=1.0, top_p=1.0, top_k=0, repetition=1.0, batch=False)
-print(response)```
+print(response)
+```
 
 
 2. Given this python script, we will create a bash script, which spins up the inference server within the [NeMo container](https://github.com/NVIDIA/NeMo/blob/main/Dockerfile) and calls the python script ``call_server.py``. The bash script ``nemo_inference.sh`` is as follows,