What are the differences between pre-trained models and custom models?

What are the differences between pre-trained models and custom models?

Pre-trained models are built on large datasets and can be used out-of-the-box, while custom models are tailored to specific tasks.

Can you give me examples of when to use each type?

Use pre-trained models for general tasks like image recognition, and custom models for specialized tasks like medical diagnosis.

What are the advantages of using a pre-trained model?

Pre-trained models save time and resources, as they require less data and training compared to custom models.

Are there any downsides to using pre-trained models?

Yes, they may not perform well on niche tasks and can introduce biases present in the training data.