The `top_p` parameter in the ChatGPT API represents the “nucleus sampling” or the cumulative distribution function (CDF) of the model’s next word prediction probabilities. It’s a number between 0 and 1, where the model selects the smallest possible set of words whose cumulative probability exceeds the `top_p` value.
By changing the `top_p` value, you can affect the text’s randomness. Higher values lead to more randomness, while lower values make the output more deterministic. If you set `top_p` to 1, the model uses all possible next words, which maximizes randomness. If you set `top_p` to some low value like 0.1, the model uses only the most probable next words, making your answers more predictable.
To use the `top_p` parameter, simply include it in the options object when calling the `openai.ChatCompletion.create()` method. Here’s an example:
```
response = openai.ChatCompletion.create(
model=“gpt-3.5-turbo”,
messages=[
{“role”: “system”, “content”: “You are a helpful assistant.”},
{“role”: “user”, “content”: “Who won the world series in 2020?”},
],
options={“top_p”: 0.8}
)
```
This code sets the `top_p` parameter value to 0.8, which introduces an element of randomness in the output while still keeping it fairly consistent with what the model considers the most probable responses.
