Posts tagged “llm”

Definition and explanation of tokens in large language models.

Five prompting techniques that improve LLM outputs: few-shot learning, chain-of-thought reasoning, XML structure, output constraints, and prompt chaining.

Your prompt's opening sets the context for the entire response.

LLMs generate text one token at a time. Understanding how they convert text to vectors, use attention to weigh context, and predict probabilities explains their behavior.

When models fail or behave unexpectedly, you need to understand why. Practical debugging techniques for tokenization, attention patterns, and context limits.