A guide to prompting Llama 2

Prompting large language models like Llama 2 involves using various techniques to guide and enhance their responses, such as formatting chat prompts with specific tags, employing system prompts to influence model behavior, and adjusting parameters like temperature for desired output randomness. Llama 2 offers different model sizes, each with varying capabilities and speeds, and it is important to choose the appropriate variant based on the task, whether it's summarizing, dialogue, or factual questioning. Techniques like Ghost Attention improve the model's ability to remember instructions over multiple dialogue turns, while experimentation with system prompts can dictate the model's persona and how it handles requests. The model's open-source nature allows users to control the code and data processing, providing advantages over proprietary systems like ChatGPT, especially in terms of privacy and customization. Despite some limitations in tasks like counting letters, Llama 2 shows potential in handling dialogue and factual questions effectively, with ongoing developments to enhance its capabilities further.