Generative AI Studio

Zero-shot prompting – This is a method where the LLM is given no additional data on the specific task that it is being asked to perform. Instead, it is only given a prompt that describes the task. For example, if you want the LLM to answer a question, you just prompt “what is prompt design?”.
One-shot prompting – This is a method where the LLM is given a single example of the task that it is being asked to perform. For example, if you want the LLM to write a poem, you might give it a single example poem.
Few-shot prompting – This is a method where the LLM is given a small number of examples of the task that it is being asked to perform. For example, if you want the LLM to write a news article, you might give it a few news articles to read.

What are the key features of Generative AI Studio Language?

Design a prompt
Create a conversation
Turn a model

In the world of Generative AI, a prompt is just a fancy name for the input text that you feed to your model. You can feed your desired input text like questions and instructions to the model. The model will then provide a response based on how you structured your prompt, therefore, the answers you get depend on the questions you ask.

The process of figuring out and designing the best input text to get the desired response back from the model is called Prompt Design, which often involves a lot of experimentation.

What are the mode parameters that you can tune in Generative AI Studio Language to improve the response that fits your requirement?

Model type
Temperate
Top K
Top P

FREE-FORM – This mode provides a free and easy approach to design your prompt. It is suitable for small and experimental prompts with no additional examples. You will be using this to explore zero-shot prompting.
STRUCTURED – This mode provides an easy-to-use template approach to prompt design. Context and multiple examples can be added to the prompt in this mode. This is especially useful for one-shot and few-shot prompting methods which you will be exploring later.

Temperature is a number used to tune the degree of randomness. Low temperature means choosing the most likely and predictable words. For example, flowers in the sentence the garden is full of beautiful__. High temperature means to choose the words that have low possibility and are more unusual. For example, bugs in the sentence the garden is full of beautiful__.

You need to specify the tuning parameters, the tuning dataset, and the tuning objective.

What are the best practices of prompt design?