Few-shot prompting with Llama
You're using a Llama model to identify the sentiment of customer reviews from Google and Yelp as Positive or Negative. To ensure these labels are consistent for each review, you'll design a few-shot prompt containing three examples.
Here are the examples you want to provide to the model:
- I ordered from this place last night, and I'm impressed! → Positive
- My order was delayed by over an hour without any updates. Disappointing! → Negative
- The food quality is top-notch. Highly recommend! → Positive
Deze oefening maakt deel uit van de cursus
Working with Llama 3
Oefeninstructies
- Complete the few-shot prompt by assigning
PositiveorNegativeto the reviews provided. - Send the prompt to the model with the
"Review"stop word so the model only responds to one review.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Complete the few-shot prompt
prompt="""Review 1: I ordered from this place last night, and I'm impressed!
Sentiment 1: ____,
Review 2: My order was delayed by over an hour without any updates. Disappointing!
Sentiment 2: ____,
Review 3: The food quality is top-notch. Highly recommend!
Sentiment 3: ____,
Review 4: Delicious food, and excellent customer service!
Sentiment 4:"""
# Send the prompt to the model with a stop word
output = llm(prompt, max_tokens=2, stop=["____"])
print(output['choices'][0]['text'])