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  • 1

    Understanding LLMs and Llama

    Free

    The field of large language models has exploded, and Llama is a standout. With Llama 3, possibilities have soared. Explore its capabilities, learn to use it with llama-cpp-python, and understand how to control the model's behavior by adjusting parameters and assigning specific roles to guide the conversation.

  • 2

    Using Llama Locally

    Language models can do more than just generate text - they can be guided to produce structured and context-aware responses. In this chapter, you'll explore how to leverage llama-cpp-python to generate outputs in specific formats, including JSON-compatible responses for data integration. You'll also refine Llama's output using prompting techniques to align responses with different tasks. Finally, you'll build conversations that maintain context across multiple exchanges, ensuring more natural interactions.

Initializing

Exercise

Guiding customer support responses

You work for an e-commerce company and are integrating Llama into a customer support assistant. The assistant answers frequently asked questions, but you've noticed that responses are too repetitive.

You need to modify decoding parameters to encourage more varied wording while keeping responses informative.

The model is already instantiated with a model using llama_cpp and is stored in llm.

Instructions

100 XP
  • Set the temperature parameter so that responses are less repetitive and more dynamic.