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A short class with Sarah and her students. The other ways are under More.
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Today, we are going to dissect a sample prompt to understand its components. What are the different parts that make up a prompt?
Is it just the instruction, or are there more parts?
Great question! A good prompt usually includes an instruction, context, input data, output format, and sometimes tone. Can anyone give me a brief definition of 'instruction'?
Isn't it what you want the model to do?
Exactly! Instructions tell the model the action it needs to perform. Now, how does context play a role?
Context provides background information to help the model understand the task better.
Exactly! The context helps guide the model’s response. Remember the acronym I like to use for these components: I-C-O-O-T? It stands for Instruction, Context, Output format, and Tone. Let’s keep this handy as we continue.
Let’s look at the sample prompt together. Can someone read it?
"You are a career coach. A student is applying to Google for a data science internship. Write a 4-line summary of their strengths using a confident tone. Use bullet points."
Perfect! Let's identify the key parts. What is the instruction here?
The instruction is to write a summary of strengths.
Yes! And what about the context?
The student is applying for an internship.
Precisely! Now, who remembers why specifying the tone is significant?
It helps ensure the response sounds appropriate for the situation, like being confident for a job application!
Exactly! And what's the output format?
It needs to be in bullet points and limited to four lines.
Wonderful teamwork, everyone! Remember, breaking down prompts into these components can dramatically influence the quality of the AI’s response.
Now that we understand the components, how can we apply this knowledge when creating our prompts?
We should start with a clear instruction, right?
Absolutely! Clarity is crucial. Can anyone suggest an example of a poorly written instruction?
How about "write something?" That's too vague!
Exactly! Instead, we could say, 'Write a 50-word persuasive paragraph on the benefits of regular exercise.' What makes this better?
It’s specific and gives a clear format!
Well done! Specificity helps guide the model to provide useful responses. Remember the tips: concise, clear, and context-rich. Now let’s practice making our prompts!
Includes instruction, context, input data, output format, and tone.
Clear prompts with specific details yield better model responses.
Setting a role in prompts can influence the context of the response.
In a prompt’s design, clarity’s key, / Context and tone help shape what we see.
Imagine a chef (the model) receiving a recipe (the prompt) that tells them the dish (instruction), ingredients (context), and style (tone), leading to a meal (output) everyone loves.
I-C-O-O-T: Instruction, Context, Output, Order (Format), Tone.
CLOSE - Clear, Logical, Organized, Specific, Engaging for each prompt.
Term
What is a prompt?
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What are the core components of a prompt?
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What is the role of context in a prompt?
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Why is tone important in a prompt?
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Term
Define Instruction.
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The input given to a language model to achieve a response.
Specific direction given to the model about what action to perform.
Background information or examples provided to guide the model’s response.
The required format of the model's response, such as bullet points or paragraph.
The desired voice or style of the response, which can be friendly, professional, etc.
This section dissects a sample prompt, detailing its core components and clarifying how each element contributes to the model's response.
The section provides a detailed examination of a specific prompt given to a language model. It breaks down the prompt into its core components, such as instruction, context, tone, and output format, and demonstrates how these elements interact to create an effective query. Understanding this sample prompt is essential for learning the nuances of prompt crafting.
The section examines a sample prompt to illustrate the fundamental elements that comprise an effective query to a language model. The prompt analyzed is:
"You are a career coach. A student is applying to Google for a data science internship. Write a 4-line summary of their strengths using a confident tone. Use bullet points."
Understanding how to effectively break down and utilize these components in prompts not only optimizes the model's performance but also enhances the prompt engineering skills essential for accurate and insightful AI interactions.