Prompt engineering

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How to Create Descriptive, Poetic Text

Choose a topic and narrow down the scope.
Select a point-of-view like third, second or first person.
Directly or indirectly convey a mood. A subject or scene could evoke a particular feeling or you could give the chatbot a mood directly.
Describe sensory details. Add details about the scene such as sounds, sights, smells, or textures. By pointing out an important detail, you can guide the output.
Don't tell, Show. Ask the chatbot not to tell the user how to think or feel.
Use figurative language. The chatbot should be encouraged to use metaphors, similes and descriptive phrases. Request a description that is evocative, lyrical, beautiful or poetic.
Iterate and iterate. Your first prompt might not yield the desired result. Rework the prompt until you find an appealing answer. After you have created a prompt that is appealing, the chatbot can create many descriptions and you can pick the one you like.
Edit and revise. Don't be afraid of revising and editing the generated text.
You can ask the chatbot for assistance. The chatbot will explain why it selected a specific detail or phrase in a reply. The chatbot can also help you create a better prompt. You can point out individual phrases and ask the chatbot for alternatives or suggestions.

Emergent Prompting

chain-of-thought prompting

Fill in the Blank

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Example

Tom Hanks is a _ by profession.

see more...^[1]

Parameters

Common Parameters

Temperature

Perplexity

Burstiness

User-created Parameters

Introduction

These are user-created parameters. They serve to convey the intent of the users in a more concise way. These are not part of the model API but patterns the LLM has picked up through its training. These parameters are just a compact way to deliver what is usually expressed in natural language.

Example in ChatGPT

Prompt: Write a paragraph about how adorable a puppy is.
Temperature: 1.0
Sarcasm: 0.9
Vividness: 0.4

We add "Prompt: " to the start of our prompt to make sure ChatGPT knows where our prompt is. We add the GPT parameter temperature, which goes from 0 to 1 to indicate the following parameters also range from 0 to 1. Then we list our parameters along with their values which go from 0 to 1 (0 is the smallest, and 1 is the largest). Note that having too many or contradictory parameters may lower the quality of the response.

List of Parameters

References

↑ How Can We Know What Language Models Know? https://arxiv.org/abs/1911.12543/

[”1”-1] How Can We Know What Language Models Know? https://arxiv.org/abs/1911.12543/

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