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This article is divided into four parts; they are: • How Logits Become Probabilities • Temperature • Top- k Sampling • Top- p Sampling When you ask an LLM a question, it outputs a vector of logits.
Machine learning models possess a fundamental limitation that often frustrates newcomers to natural language processing (NLP): they cannot read.
Data leakage is an often accidental problem that may happen in machine learning modeling.
This article is divided into three parts; they are: • Understanding the Architecture of Llama or GPT Model • Creating a Llama or GPT Model for Pretraining • Variations in the Architecture The architecture of a Llama or GPT model is simply a stack of transformer blocks.
In 2025, “using AI” no longer just means chatting with a model, and you’ve probably already noticed that shift yourself.
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Strange as it may sound, large language models (LLMs) can be leveraged for data analysis tasks, including specific scenarios such as time series analysis.
Large language models generate text, not structured data.
Agentic AI is changing how we interact with machines.
Large language models (LLMs) are mainly trained to generate text responses to user queries or prompts, with complex reasoning under the hood that not only involves language generation by predicting each next token in the output sequence, but also entails a deep understanding of the linguistic patterns surrounding the user input text.