Understanding pre-trained models
Pre-trained models are like learning from the experience of others. These models have been trained on extensive datasets, learning patterns, and features that make them adept at their tasks. Think of it as if a model has been reading thousands of books on a subject, absorbing all that information. When we use a pre-trained model, we’re leveraging all that prior knowledge.
In general, pre-training steps are not necessarily “useful” to a human, but it is crucial to a model to simply learn about a domain and about a medium. Pre-training helps models learn how language works in general but not how to classify sentiments or detect an object.
Benefits of using pre-trained models
The benefits of using pre-trained models are numerous. For starters, they save us a lot of time. Training a model from scratch can be a time-consuming process, but using a pre-trained model gives us a head start. Furthermore, these models often lead to...
