Interface TogetherAICallOptions

interface TogetherAICallOptions {
    logprobs?: number;
    maxTokens?: number;
    model?: string;
    modelName?: string;
    repetitionPenalty?: number;
    safetyModel?: string;
    temperature?: number;
    topK?: number;
    topP?: number;
}

Hierarchy

  • BaseLLMCallOptions
  • Pick<TogetherAIInputs, "modelName" | "model" | "temperature" | "topP" | "topK" | "repetitionPenalty" | "logprobs" | "safetyModel" | "maxTokens" | "stop">
    • TogetherAICallOptions

Properties

logprobs? maxTokens? model? modelName? repetitionPenalty? safetyModel? temperature? topK? topP?

Properties

Optional logprobs

logprobs?: number

An integer that specifies how many top token log probabilities are included in the response for each token generation step.

Optional maxTokens

maxTokens?: number

Limit the number of tokens generated.

Optional model

model?: string

The name of the model to query.

Optional modelName

modelName?: string

The name of the model to query. Alias for model

Optional repetitionPenalty

repetitionPenalty?: number

A number that controls the diversity of generated text by reducing the likelihood of repeated sequences. Higher values decrease repetition.

Default

{1}

Optional safetyModel

safetyModel?: string

Run an LLM-based input-output safeguard model on top of any model.

Optional temperature

temperature?: number

A decimal number that determines the degree of randomness in the response. A value of 1 will always yield the same output. A temperature less than 1 favors more correctness and is appropriate for question answering or summarization. A value greater than 1 introduces more randomness in the output.

Default

{0.7}

Optional topK

topK?: number

The topK parameter is used to limit the number of choices for the next predicted word or token. It specifies the maximum number of tokens to consider at each step, based on their probability of occurrence. This technique helps to speed up the generation process and can improve the quality of the generated text by focusing on the most likely options.

Default

{50}

Optional topP

topP?: number

The topP (nucleus) parameter is used to dynamically adjust the number of choices for each predicted token based on the cumulative probabilities. It specifies a probability threshold, below which all less likely tokens are filtered out. This technique helps to maintain diversity and generate more fluent and natural-sounding text.

Default

{0.7}

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