/**
 * Inference code generated from the JSON schema spec in ./spec
 *
 * Using src/scripts/inference-codegen
 */
/**
 * Inputs for Token Classification inference
 */
export interface TokenClassificationInput {
    /**
     * The input text data
     */
    inputs: string;
    /**
     * Additional inference parameters
     */
    parameters?: TokenClassificationParameters;
    [property: string]: unknown;
}
/**
 * Additional inference parameters
 *
 * Additional inference parameters for Token Classification
 */
export interface TokenClassificationParameters {
    /**
     * The strategy used to fuse tokens based on model predictions
     */
    aggregation_strategy?: TokenClassificationAggregationStrategy;
    /**
     * A list of labels to ignore
     */
    ignore_labels?: string[];
    /**
     * The number of overlapping tokens between chunks when splitting the input text.
     */
    stride?: number;
    [property: string]: unknown;
}
/**
 * Do not aggregate tokens
 *
 * Group consecutive tokens with the same label in a single entity.
 *
 * Similar to "simple", also preserves word integrity (use the label predicted for the first
 * token in a word).
 *
 * Similar to "simple", also preserves word integrity (uses the label with the highest
 * score, averaged across the word's tokens).
 *
 * Similar to "simple", also preserves word integrity (uses the label with the highest score
 * across the word's tokens).
 */
export type TokenClassificationAggregationStrategy = "none" | "simple" | "first" | "average" | "max";
export type TokenClassificationOutput = TokenClassificationOutputElement[];
/**
 * Outputs of inference for the Token Classification task
 */
export interface TokenClassificationOutputElement {
    /**
     * The character position in the input where this group ends.
     */
    end: number;
    /**
     * The predicted label for a single token
     */
    entity?: string;
    /**
     * The predicted label for a group of one or more tokens
     */
    entity_group?: string;
    /**
     * The associated score / probability
     */
    score: number;
    /**
     * The character position in the input where this group begins.
     */
    start: number;
    /**
     * The corresponding text
     */
    word: string;
    [property: string]: unknown;
}
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