Interface FriendliParams

The FriendliParams interface defines the input parameters for the Friendli class.

interface FriendliParams {
    baseUrl?: string;
    frequencyPenalty?: number;
    friendliTeam?: string;
    friendliToken?: string;
    maxTokens?: number;
    model?: string;
    modelKwargs?: Record<string, unknown>;
    stop?: string[];
    temperature?: number;
    topP?: number;
}

Hierarchy (view full)

Properties

baseUrl? frequencyPenalty? friendliTeam? friendliToken? maxTokens? model? modelKwargs? stop? temperature? topP?

Properties

OptionalbaseUrl

baseUrl?: string

Base endpoint url.

OptionalfrequencyPenalty

frequencyPenalty?: number

Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled, taking into account their frequency in the preceding text. This penalization diminishes the model's tendency to reproduce identical lines verbatim.

OptionalfriendliTeam

friendliTeam?: string

Friendli team ID to run as.

OptionalfriendliToken

friendliToken?: string

Friendli personal access token to run as.

OptionalmaxTokens

maxTokens?: number

Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled at least once in the existing text. presence_penalty: Optional[float] = None The maximum number of tokens to generate. The length of your input tokens plus max_tokens should not exceed the model's maximum length (e.g., 2048 for OpenAI GPT-3)

Optionalmodel

model?: string

Model name to use.

OptionalmodelKwargs

modelKwargs?: Record<string, unknown>

Additional kwargs to pass to the model.

Optionalstop

stop?: string[]

When one of the stop phrases appears in the generation result, the API will stop generation. The phrase is included in the generated result. If you are using beam search, all of the active beams should contain the stop phrase to terminate generation. Before checking whether a stop phrase is included in the result, the phrase is converted into tokens.

Optionaltemperature

temperature?: number

Sampling temperature. Smaller temperature makes the generation result closer to greedy, argmax (i.e., top_k = 1) sampling. If it is None, then 1.0 is used.

OptionaltopP

topP?: number

Tokens comprising the top top_p probability mass are kept for sampling. Numbers between 0.0 (exclusive) and 1.0 (inclusive) are allowed. If it is None, then 1.0 is used by default.

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