Model Neural network and Deep learning Layer: a data processing module the kernel and bias = weights model compilation epoch model’s evaluate method backpropagation gradient of loss Why do we need gradient? MSE (Mean Squared Error) Adding nonlinearity: Beyond weighted sums
Execution Engines GPT-3 comes with four execution engines of varying sizes and capabilities: Davinci, Ada, Babbage, and Curie. Davinci is the most powerful and the Playground’s default. Ada Babbage Curie Davinci Customizing GPT-3 Fine-tuning is about tweaking the whole model so that it performs every time in the way you wish it to perform. You can use an existing dataset of any shape and size, or incrementally add data based on user feedback. OpenAI also found that each doubling of…