human
Summarize the following text.
Text: Random sampling, by itself, could potentially generate a very random word by chance. Temperature increases the probability of probable tokens while reducing the one that is not. Usually, the range is 0<temp ≤ 1. Note that when temp=1, there is no effect.

Lower temperatures are more appropriate when performing "correct" answer tasks like question-answering or summarization. The model repeating itself is a sign that the temperature is too low. Higher temperature means more randomness, which can help the model give more creative outputs. The model going off-topic or giving nonsensical outputs is a sign that the temperature is too high.

As sequences get longer, the model naturally becomes more confident in its predictions, so you can raise the temperature much higher for long prompts without going off-topic. In contrast, high temperatures on short prompts can lead to very unstable outputs.


Summary:
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
No

--- Answer ---
open