Mastering LLM Interactions

Author(s): Dimitris Effrosynidis

Originally published on Towards AI.

Prompt engineering, quantized model optimization, and grammar-constrained sampling

This member-only story is on us. Upgrade to access all of Medium.

Generative AI transforms industries by enabling machines to produce human-like text, generate structured outputs, and solve complex problems creatively.

However, the magic happens when you combine cutting-edge models with advanced techniques like prompt engineering, quantized model optimization, and grammar-constrained sampling.

In this project, I explore the forefront of these techniques, demonstrating how to harness the capabilities of state-of-the-art language models to achieve specific and efficient results.

From crafting intricate prompts to controlling the randomness and structure of outputs, this work reflects the fusion of creativity, technical expertise, and a deep understanding of model behavior.

This article focuses on three pivotal aspects of generative AI:

Learn how to guide models using precise instructions, multi-component prompts, and in-context learning (zero-shot, one-shot, and few-shot prompting).Use advanced prompt strategies to create structured outputs like JSON-based descriptions.Explore how quantized models enable high-performance inference with reduced memory and computational requirements.Understand the trade-offs between file size, precision, and model accuracy using quantization levels such as Q2, Q4, and fp16.Enforce predefined formats like JSON during the token generation process using grammar-constrained sampling.Apply these techniques to achieve reliable and application-ready outputs in domains like structured data generation and sentiment classification.

As AI… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI