Post-training
Additional steps taken after a model's initial training is complete to make it more useful.
Detailed Definition
Post-training refers to all of the additional steps taken after training is complete to make the model even more useful. This includes steps like "fine-tuning" and "RLHF." These processes refine the model's behavior, align it with human preferences, and specialize it for specific applications.
Learning MethodsMore in this Category
Few-Shot Learning
The ability of AI models to learn new tasks with only a small number of training examples.
Fine-tuning
A post-training technique to specialize a trained model on specific data for a particular task.
RLHF (reinforcement learning from human feedback)
A post-training technique to align AI models with human preferences using feedback.
Training/Pre-training
The process by which an AI model learns by analyzing massive amounts of data.
Supervised learning
A type of machine learning where a model is trained on labeled data with correct answers provided.
Unsupervised learning
A type of machine learning where a model is given unlabeled data to find patterns on its own.