A pre-trained model is a neural network that has been previously trained on a large dataset and is ready for use. Instead of training a model from scratch, developers can leverage pre-trained models for tasks like image recognition, natural language processing, or speech recognition.
These models have already learned important features from their training data and can be fine-tuned or used directly for specific applications, reducing the time and resources required for training. Common examples include models like ResNet, BERT, and GPT.
Pre-trained models are especially useful for tasks with limited labeled data, as they provide a starting point and can generalize well to different but related problems.