Part 4/9:
- Automating the process by scripting prompts that combine various elements like genres, locations, time periods, and modifiers to create over 200 unique examples.
This process ensures a rich, varied dataset that encapsulates multiple formats and content styles, which is key for robust fine-tuning.
Implementing Synthetic Data with Prompt Engineering
To illustrate, Shapiro demonstrates creating prompts for generating plot outlines in different genres, locations, times, and themes. He stresses the importance of prompt engineering—modifying prompt phrasing to elicit the most useful output from the model. For example, changing the keyword from "premise" to "plot outline" can influence the detail and style of the generation.