Definition
A pre-trained model is a foundational AI model that has undergone extensive training on massive, diverse datasets, such as Wikipedia or ImageNet. This initial training allows the model to learn broad patterns, syntax, and semantic relationships. Instead of training from scratch, developers leverage these pre-trained weights as a starting point, significantly reducing computational costs and time required to achieve high performance on specialized downstream tasks through subsequent fine-tuning or transfer learning.
Summary
Pre-trained models are neural networks that have been trained on large datasets to learn general features before being adapted for specific tasks.
Key Concepts
- Transfer Learning
- Foundation Models
- Feature Extraction
- Weights Initialization
Use Cases
- Building chatbots using LLMs
- Image classification using ResNet
- Sentiment analysis with BERT