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Pre-trained Model

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. An AI model that has already been trained on a very large dataset for a general task.

Technical Definition

An AI model that has already been trained on a very large dataset for a general task.

How it works

Pre-trained Models (like BERT or GPT) have learned general language patterns and knowledge from vast amounts of text data. They serve as a powerful starting point for many NLP applications. Instead of building a model from scratch, developers can fine-tune these models for specific tasks like intent recognition or dialogue generation, saving significant computational resources and data.

Related Concepts

• Large Language Model (LLM) — A massive neural network trained on vast text corpora to understand and generate human language with remarkable fluency.
• Fine-Tuning — Adapting a pre-trained model to a specific task by continuing training on a smaller, task-specific dataset.
• Transfer Learning — Leveraging knowledge from a model trained on one task to improve performance on a different but related task.