Model selection (GPT-4, GPT-3.5) in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the GPT-4 model for generating text.

Prompt Engineering / GenAI

model = "[1]"

Drag options to blanks, or click blank then click option'

Agpt-3.5-turbo

Bcurie

Cgpt-4

Ddavinci

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'gpt-3.5-turbo' instead of 'gpt-4'.

Using older model names like 'davinci' or 'curie'.

The GPT-4 model is selected by setting the model string to "gpt-4".

2fill in blank

medium

Complete the code to set the temperature parameter for more creative responses.

Prompt Engineering / GenAI

response = openai.ChatCompletion.create(model="gpt-4", temperature=[1], messages=messages)

Drag options to blanks, or click blank then click option'

A0.7

B0.0

C1.5

D-0.5

Attempts:

3 left

💡 Hint

Common Mistakes

Using a temperature like 1.5, which produces overly random output.

Setting temperature to 0.0, which makes output very deterministic.

A temperature of 0.7 encourages creativity without being too random.

3fill in blank

hard

Fix the error in the code to correctly select GPT-3.5 model.

Prompt Engineering / GenAI

model_name = "[1]"

Drag options to blanks, or click blank then click option'

Agpt-4

Btext-davinci-003

Cgpt-3

Dgpt-3.5-turbo

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'gpt-4' instead of GPT-3.5.

Using older names like 'text-davinci-003'.

The correct model name for GPT-3.5 is 'gpt-3.5-turbo'.

4fill in blank

hard

Fill both blanks to create a dictionary with model and max tokens for GPT-4.

Prompt Engineering / GenAI

config = {"model": "[1]", "max_tokens": [2]

Drag options to blanks, or click blank then click option'

Agpt-4

Bgpt-3.5-turbo

C8192

D4096

Attempts:

3 left

💡 Hint

Common Mistakes

Using GPT-3.5 model name with GPT-4 max tokens.

Setting max tokens too low for GPT-4.

GPT-4 supports max_tokens up to 8192, so model is 'gpt-4' and max_tokens is 8192.

5fill in blank

hard

Fill all three blanks to create a request with GPT-3.5, temperature 0.5, and max tokens 4096.

Prompt Engineering / GenAI

response = openai.ChatCompletion.create(model="[1]", temperature=[2], max_tokens=[3], messages=messages)

Drag options to blanks, or click blank then click option'

Agpt-4

B0.5

C4096

Dgpt-3.5-turbo

Attempts:

3 left

💡 Hint

Common Mistakes

Using GPT-4 model name instead of GPT-3.5.

Setting temperature too high or too low.

Using max tokens not supported by GPT-3.5.

The request uses GPT-3.5 model 'gpt-3.5-turbo', temperature 0.5 for moderate creativity, and max_tokens 4096.

Practice

1. Which model should you choose if you need detailed and complex text generation?

easy

A. GPT-3.5

B. Both are equally detailed

C. GPT-4

D. Neither, use a smaller model

Solution

1. Step 1: Understand model capabilities

   GPT-4 is designed for more complex and detailed tasks compared to GPT-3.5.

2. Step 2: Match task complexity to model

   For detailed and complex text generation, GPT-4 is the better choice.

3. Final Answer:

   GPT-4 -> Option C

4. Quick Check:

   Complex tasks = GPT-4 [OK]

Hint: Choose GPT-4 for complexity, GPT-3.5 for speed [OK]

Common Mistakes:

• Choosing GPT-3.5 for complex tasks
• Thinking both models have same detail level

2. Which of the following is the correct way to specify GPT-3.5 in an API call?

easy

A. "model": "gpt-3.5-turbo"

B. "model": "gpt-3"

C. "model": "gpt-4"

D. "model": "gpt-5"

Solution

1. Step 1: Recall model naming conventions

   The GPT-3.5 model is named "gpt-3.5-turbo" in API calls.

2. Step 2: Identify correct option

   "model": "gpt-3.5-turbo" matches the exact model name for GPT-3.5.

3. Final Answer:

   "model": "gpt-3.5-turbo" -> Option A

4. Quick Check:

   Correct model name = "model": "gpt-3.5-turbo" [OK]

Hint: Use exact model name string in API call [OK]

Common Mistakes:

• Using "gpt-3" instead of "gpt-3.5-turbo"
• Confusing GPT-4 name with GPT-3.5

3. Given this code snippet calling the OpenAI API, which model will produce faster responses but possibly less detailed output?

response = openai.ChatCompletion.create(
  model="gpt-3.5-turbo",
  messages=[{"role": "user", "content": "Explain photosynthesis."}]
)

medium

A. GPT-3.5, faster but less detailed

B. GPT-4, slower but more detailed

C. GPT-4, faster and more detailed

D. GPT-3.5, slower but more detailed

Solution

1. Step 1: Identify the model used in code

   The code uses "gpt-3.5-turbo" as the model parameter.

2. Step 2: Recall model speed and detail tradeoff

   GPT-3.5 is faster but less detailed compared to GPT-4.

3. Final Answer:

   GPT-3.5, faster but less detailed -> Option A

4. Quick Check:

   Model in code = GPT-3.5 [OK]

Hint: Check model name string to know speed/detail tradeoff [OK]

Common Mistakes:

• Assuming GPT-3.5 is slower
• Confusing model names in code snippet

4. You wrote this API call but get an error:

response = openai.ChatCompletion.create(
  model="gpt-3.5",
  messages=[{"role": "user", "content": "Tell me a joke."}]
)

What is the likely problem?

medium

A. Messages list is missing a system role

B. Model name is incomplete, should be "gpt-3.5-turbo"

C. API key is missing

D. The model "gpt-3.5" does not exist

Solution

1. Step 1: Check model name correctness

   The model name "gpt-3.5" is incomplete; the correct full name is "gpt-3.5-turbo".

2. Step 2: Understand error cause

   Using an incomplete model name causes the API to reject the call.

3. Final Answer:

   Model name is incomplete, should be "gpt-3.5-turbo" -> Option B

4. Quick Check:

   Model name must be exact [OK]

Hint: Use full model name string to avoid errors [OK]

Common Mistakes:

• Using partial model names
• Assuming system role is mandatory
• Ignoring API key errors

5. You want to build a chatbot that answers customer questions quickly and cheaply but can switch to detailed answers when needed. How should you select models in your code?

hard

A. Always use GPT-4 for all answers

B. Use GPT-4 only, it is always more accurate

C. Use GPT-3.5 only, it is always faster and cheaper

D. Use GPT-3.5 for quick replies, switch to GPT-4 for detailed ones

Solution

1. Step 1: Understand tradeoffs between GPT-3.5 and GPT-4

   GPT-3.5 is faster and cheaper but less detailed; GPT-4 is slower and costlier but more detailed.

2. Step 2: Match chatbot needs to model selection

   Use GPT-3.5 for quick, cheap answers and switch to GPT-4 when detailed responses are needed.

3. Final Answer:

   Use GPT-3.5 for quick replies, switch to GPT-4 for detailed ones -> Option D

4. Quick Check:

   Balance speed and detail with model switching [OK]

Hint: Switch models based on answer detail needed [OK]

Common Mistakes:

• Using only one model for all tasks
• Ignoring cost and speed tradeoffs