Prompt engineering

Completion is the new text (output) generated by the model after you've inferenced it with (entered) a prompt.

Prompt Engineering for Coding

Genearte code using models like the OpenAI Codex.

Task

Give the model a high level task description. To improve the quality of the generated code, it's recommended to start the prompt with a broad description of the task at hand. For example, if you want to generate Python code to plot data from a standard dataset, you can provide a prompt like this: "# Load iris data from scikit-learn datasets and plot the training data." However, sometimes the generated code may not be optimal, in which case you can provide more specific instructions such as importing libraries before using them. By combining a high-level task description with detailed user instructions, you can create a more effective prompt for Codex to generate code.

Examples

Gives the model examples.

How to Create Descriptive, Poetic Text

Tips

• 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.

Template

Describe YOUR SCENE. Use sensory language and detail to describe the OBJECTS IN THE SCENE vividly. Describe SPECIFIC DETAILS and any other sensory details that come to mind. Vary the sentence structure and use figurative language as appropriate. Avoid telling the reader how to feel or think about the scene.

Emergent Prompting

Fill in the Blank

Example

Tom Hanks is a _ by profession.

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Parameters

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

• Professionalism -
• Randomness -
• Sentimentality -
• Sesquipedalianism -
• Sarcasm -
• Laconic -
• Asyndetic -
• Vividness -
• Ecclesiastical -