Summary of Elements of a Prompt
When designing prompts for large language models, it is important to consider the elements of a prompt to get the best results.
Elements of a prompt typically include an instruction, context (which varies based on the use case), input data, and output indicator.
The input data should be passed to the model in a way that aligns with the task, such as using text as an indicator for text classification.
The output indicator specifies the expected output, such as sentiment in the case of sentiment analysis.
By utilizing different roles (system, user, assistant) in the prompt design, the task can be simplified and the model can provide more reliable outputs.
Experimenting with different inputs and outputs in the prompt design can help optimize the model's performance.
Context may not always be necessary in a prompt, but clear instructions, appropriate input data, and specific output indicators are crucial for effective prompt design.
Speakers/sources
- Not specified in the subtitles.
Notable Quotes
— 02:58 — « I can just space it like this and I I can submit this as is. »
— 04:51 — « the system role is where you will Define what type of behavior you are expecting from this model. »
— 06:51 — « it's important to think about different elements because this is what each one of the prompts that you will be designing and optimizing will carry a combination of these different components. »
Category
Educational