To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their frequency in the generated text so far. Greater numbers encourage the model to use new tokens, while lower numbers encourage the model to repeat the tokens. Set to 0 to disable. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
Whether or not to return the user prompt in the response. This option only applies to non-stream results.
Whether to stream back partial progress. If set, tokens are sent as data-only server-sent events as they become available.
The maximum number of tokens to predict for each response. Includes input plus output tokens. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
The number of generated texts that will be returned. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on whether they've appeared in the generated text so far. Greater numbers encourage the model to use new tokens, while lower numbers encourage the model to repeat the tokens.
Similar to frequency penalty, a penalty is applied to previously present tokens, except that this penalty is applied equally to all tokens that have already appeared, regardless of how many times they've appeared. Set to 0 to disable. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
Represents the prompt to be completed. The trailing white spaces are trimmed before completion.
Specifies how and if the token likelihoods are returned with the response.
The generated text is cut at the end of the earliest occurrence of this stop sequence. The generated text will include this stop sequence.
A number that sets the randomness of the generated output. A lower temperature means a less random generations.
Use lower numbers for tasks with a correct answer such as question answering or summarizing. High temperatures can generate hallucinations or factually incorrect information. Start with temperatures lower than 1.0 and increase the temperature for more creative outputs, as you regenerate the prompts to refine the outputs. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
An integer that sets up the model to use only the top k most likely tokens in the generated output. A higher k introduces more randomness into the output making the output text sound more natural. Default value is 0 which disables this method and considers all tokens. To set a number for the likely tokens, choose an integer between 1 and 500.
If also using top p, then the model considers only the top tokens whose probabilities add up to p percent and ignores the rest of the k tokens. For example, if k is 20, but the probabilities of the top 10 add up to .75, then only the top 10 tokens are chosen. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
If set to a probability 0.0 < p < 1.0, it ensures that only the most likely tokens, with total probability mass of p, are considered for generation at each step.
To eliminate tokens with low likelihood, assign p a minimum percentage for the next token's likelihood. For example, when p is set to 0.75, the model eliminates the bottom 25 percent for the next token. Set to 1.0 to consider all tokens and set to 0 to disable. If both k and p are enabled, p acts after k. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
For an input that's longer than the maximum token length, specifies which part of the input text will be truncated.
Details for the text generation request for Cohere models.