FIMCompletionRequest

Echo back the prompt in addition to the completion

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

Include the log probabilities on the logprobs most likely output tokens, as well the chosen tokens. For example, if logprobs is 20, the API will return a list of the 20 most likely tokens. The API will always return the logprob of the sampled token, so there may be up to logprobs+1 elements in the response.

The maximum number of tokens that can be generated in the completion.

ID of the model to use.

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

The prompt to generate completions for.

Up to 16 sequences where the API will stop generating further tokens.

Whether to stream back partial progress. If set, tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: DONE message.

Options for streaming response. Only set this when you set stream: true.

The suffix that comes after a completion of inserted text.

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.