Renaming notebook to conform to standard. Changing regular llama models inference script call

recipes/responsible_ai/llama_guard/README.md

@@ -16,7 +16,7 @@ In this case, the default categories are applied by the tokenizer, using the `ap
 
 Use this command for testing with a quantized Llama model, modifying the values accordingly:
 
-`python examples/inference.py --model_name <path_to_regular_llama_model> --prompt_file <path_to_prompt_file> --quantization --enable_llamaguard_content_safety`
+`python inference.py --model_name <path_to_regular_llama_model> --prompt_file <path_to_prompt_file> --enable_llamaguard_content_safety`
 
 ## Llama Guard 3 Finetuning & Customization
 The safety categories in Llama Guard 3 can be tuned for specific application needs. Existing categories can be removed and new categories can be added to the taxonomy. The [Llama Guard Customization](./llama_guard_customization_via_prompting_and_fine_tuning.ipynb) notebook walks through the process.