For example, if tokens A, B, and C have a probability ofĠ.3, 0.2, and 0.1 and the top-P value is 0.5, then the model will Tokens are selectedįrom the most (see top-K) to least probable until the sum of their probabilitiesĮquals the top-P value. Top-P changes how the model selects tokens for output. Specify a lower value for less random responses and a higher value for more The final token selected using temperature sampling. Then tokens are further filtered based on top-P with Tokens in the model's vocabulary (also called greedy decoding), while a top-K ofģ means that the next token is selected from among the three mostįor each token selection step, the top-K tokens with the highest A top-K ofġ means the next selected token is the most probable among all Top-K changes how the model selects tokens for output. Specify a lower value for shorter responses and a higher value for potentially longer 100 tokens correspond to roughly 60-80 words. Maximum number of tokens that can be generated in the response. Temperature of 0 is deterministic: the highest probability response is While higher temperatures can lead to more diverse or creative results. Require a more deterministic and less open-ended or creative response, Lower temperatures are good for prompts that The temperature is used for sampling during the response generation, which The threshold for blocking responses that could belong to the specified The safety category to configure a threshold for.
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