node-llama-cpp/dist/evaluator/TokenBias.d.ts

Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level

import { Token, Tokenizer } from "../types.js";
import { LlamaText } from "../utils/LlamaText.js";
import type { LlamaModel } from "./LlamaModel/LlamaModel.js";
/**
 * @see [Using Token Bias](https://node-llama-cpp.withcat.ai/guide/token-bias) tutorial
 */
export declare class TokenBias {
    constructor(tokenizer: Tokenizer);
    /**
     * Adjust the bias of the given token(s).
     *
     * If a text is provided, the bias will be applied to each individual token in the text.
     *
     * Setting a bias to `"never"` will prevent the token from being generated, unless it is required to comply with a grammar.
     *
     * Setting the bias of the EOS or EOT tokens to `"never"` has no effect and will be ignored.
     * @param input - The token(s) to apply the bias to
     * @param bias - The probability bias to apply to the token(s).
     *
     * Setting to a positive number increases the probability of the token(s) being generated.
     *
     * Setting to a negative number decreases the probability of the token(s) being generated.
     *
     * Setting to `0` has no effect.
     *
     * For example, setting to `0.5` will increase the probability of the token(s) being generated by 50%.
     * Setting to `-0.5` will decrease the probability of the token(s) being generated by 50%.
     *
     * Setting to `"never"` will prevent the token from being generated, unless it is required to comply with a grammar.
     *
     * Try to play around with values between `0.9` and `-0.9` to see what works for your use case.
     */
    set(input: Token | Token[] | string | LlamaText, bias: "never" | number | {
        logit: number;
    }): this;
    static for(modelOrTokenizer: LlamaModel | Tokenizer): TokenBias;
}