Expired50% confidenceFactTime unknown
A model's vocabulary typically contains 30,000 to 100,000 tokens, and the degree of randomness in sampling is controlled via the Temperature parameter.
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Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026(expired)
Sources
Related Claims
Unverified温度参数控制采样的随机程度，核采样（top-p）从概率最高的token子集中随机选取73% similarUnverifiedThe Temperature parameter of large language models controls the randomness and creative divergence of the model; when Temperature is 0, the output is completely deterministic.71% similarVerifiedLarge language models are a stochastic sampling process when temperature is greater than 071% similarVerified温度（temperature）参数控制采样过程，温度越高输出越随机多样，温度越低越趋向最高概率的选择70% similarUnverifiedWhen testing citation behavior, temperature should be set to 0 or a low value with the top-p parameter fixed, and the same prompt should be run at least 20–50 times to use statistical distributions instead of single results.70% similar
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