How can transfer learning improve the performance of a generative model for cross-domain data generation

Question

Can you tell me How can transfer learning improve the performance of a generative model for cross-domain data generation?

Answer 1

Use transfer learning by fine-tuning a pretrained generative model on target domain data to improve cross-domain generation quality. Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Leverages knowledge from large source-domain data.

• Requires less training data and time for the target domain.

• Enhances generation quality and domain relevance.

• Easily adaptable with modern libraries like Hugging Face.

Transfer learning boosts generative performance by reusing learned features from a source domain and adapting them to a new domain, hence enabling more accurate and efficient cross-domain data generation.