Fix formatting issues in LLM AI section

Author: Amanda-dong

docs/hpc/08_ml_ai_hpc/01_intro.md

@@ -6,6 +6,6 @@ For ML we'll cover two prominent open-source deep learning frameworks, PyTorch a
 
 For AI we'll cover how to run a Hugging Face Large Language Model (LLM) and how to fine tune an LLM. Specifically, we provide guides on:
 
-* **LLM Inference**: Use the standard Hugging Face transformers library for basic tasks, and also introduce vLLM, a high-throughput serving engine that offers faster inference and an OpenAI-compatible API.
-* **vLLM CLI**: We provide examples of using the vllm command-line tool to quickly serve models and engage in interactive chat sessions.
-* **Fine-tuning LLMs**: We provide a practical example of fine-tuning the Gemma model to follow specific instructions. This section compares the original model with our improved version, showing how to achieve better response quality on Torch.
+  * **LLM Inference**: Use the standard Hugging Face transformers library for basic tasks, and also introduce vLLM, a high-throughput serving engine that offers faster inference and an OpenAI-compatible API.
+  * **vLLM CLI**: We provide examples of using the vllm command-line tool to quickly serve models and engage in interactive chat sessions.
+  * **Fine-tuning LLMs**: We provide a practical example of fine-tuning the Gemma model to follow specific instructions. This section compares the original model with our improved version, showing how to achieve better response quality on Torch.