Main Concept
Continued Pre-training consists in training a pre-trained model on new domain-specific data before fine-tuning it. It expands the model’s knowledge in a specific domain. It’s like if you give to a boy who already finished primary school a book about Birds of North America so he can expand his knowledge in that specific subject.
Context
Why is it important? How does it relate to other topics?
Key Aspects
- Difference from fine-tuning: Pre-training expands knowledge; fine-tuning specializes for tasks.
- Not currently supported by Amazon Bedrock (as of 2026). Research topic for deeper exploration later.
Applications
Where could it be applied?
Examples
Real-world examples, Evidence