Zero-Shot Learning
Zero-shot learning lets an AI model perform a new task or recognize an unseen category without task-specific labeled examples.
#ModelAdaptation
Explore AIstify's latest reporting, research, and expert analysis tagged with "model adaptation", collected in one continuously updated archive.
Related Posts
Few-Shot Learning
Few-shot learning allows an AI model to recognize a task or pattern from only a small number of examples.
One-Shot Learning
One-shot learning is an AI approach that recognizes a new task or category from one example by using knowledge learned during previous training.
Low-Rank Adaptation (LoRA)
By
Daniel Mercer
• 1 min read
Low-rank adaptation (LoRA) is a parameter-efficient fine-tuning method that trains small adapter weights instead of updating an entire AI model.
Transfer Learning
By
AIstify Team
• 1 min read
A technique that adapts knowledge from one trained model to a new but related task. It speeds up training, improves efficiency, and reduces the need for large datasets.