Update Blog “deploying-a-hugging-face-llm-in-hpe-private-cloud-ai”

Author: ealagna

content/blog/deploying-a-hugging-face-llm-in-hpe-private-cloud-ai.md

@@ -61,7 +61,7 @@ First, install `openai` if you do not already have it and import.
 from openai import OpenAI
 ```
 
-Then using the endpoint and key generated by HPE MLIS enter them into your Jupyter Notebook. Be sure to append /v1 to the URL.
+Then, using the endpoint and key generated by HPE MLIS, enter them into your Jupyter Notebook. Be sure to append /v1 to the URL.
 
 ```python
 # Grab endpoint URL and API key from MLIS, remember to include "/v1" for latest version of the OpenAI-compatible API
@@ -70,7 +70,7 @@ openai_api_base = "https://smollm2-1-7b-vllm-predictor-dave-wright-hpe-1073f7cd.
 openai_api_key = "eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJpYXQiOjE3Mzk5MzgzMzAsImlzcyI6ImFpb2xpQGhwZS5jb20iLCJzdWIiOiI5MjNhM2JhOC1mMGU4LTQxOTQtODNkMS05ZWY4NzNjZGYxOWYiLCJ1c2VyIjoiZGF2ZS53cmlnaHQtaHBlLmNvbSJ9.YwH9gGPxTWxy4RSdjnQA9-U3_u7P0OIcarqw25DV8bOiftU1L4IvvyERHspj2lMGtZWbff1F3uh84wjAePHaHDcDTLoGtq6gJYwo_qRU03xV8Q2lwBetCCLUE4OHqS608gjJ-j1SLyqwxFxlXkqMOtnBY5_nswlAwCzHV28P8u8XxxfWuXFmoJpSA1egCWVVfEoTuK8CTz9kUJJ5opSp6m8qdqJmC2qxH0igcpKmL2H_MZ-62UHfEf240VRtc0DRNlOjeCoDM79aVPs3SjCtGeVkeEHimJwJbfGFIcu3LibX3QjbABUzWb5BPPZjzyEYUVM5ak12_sJ8j1mUW-r0sA"
 ```
 
-Now, we need an OpenAI client interface.
+You will now need to create an OpenAI client interface.
 
 ```python
 # create OpenAI client interface
@@ -80,7 +80,7 @@ client = OpenAI(
 )
 ```
 
-In order to interact with the model we need to create a chat function, but let's give it a history feature as well as basic chat.
+In order to interact with the model, you will need to create a chat function. For the purposes of our example, let's give it a history feature as well as basic chat.
 
 ```python
 # Interactive chat function with message history. 
@@ -124,12 +124,12 @@ def chat():
 
 ![Jupyter Notebook showing imported model endpoint and API key.](/img/jupyter.png)
 
-Then, interacting with the model is done through a simple chat.
+Once this is done, you can interact with the model through a simple chat.
 
 ![Interaction with the SmolLM2 Small Language Model in a Jupyter Notebook](/img/chat-interface.png)
 
-For a recorded demonstration that shows the process real time see this screen recording. <https://www.youtube.com/watch?v=oqjc-2c1Vtk>
+You can access [this link](https://www.youtube.com/watch?v=oqjc-2c1Vtk) to see a recorded demonstration that shows this process in real time. [](https://www.youtube.com/watch?v=oqjc-2c1Vtk)
 
 ### Summary
 
-With HPE Private Cloud AI loading new models into the system and providing endpoints is just a few simple clicks and easily integrates with popular tools like Jupyter Notebooks. To learn more about HPE Private Cloud AI please visit: <https://www.hpe.com/us/en/private-cloud-ai.html>
+With HPE Private Cloud AI, loading new models into the system and providing endpoints is just a few simple clicks and easily integrates with popular tools like Jupyter Notebooks. To learn more about HPE Private Cloud AI, please visit: <https://www.hpe.com/us/en/private-cloud-ai.html>