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import type { PipelineType } from "./pipelines";
type TableData = Record<string, (string | number)[]>;
//#region outputs
export type WidgetExampleOutputLabels = Array<{ label: string; score: number }>;
export interface WidgetExampleOutputAnswerScore {
answer: string;
score: number;
}
export interface WidgetExampleOutputText {
text: string;
}
export interface WidgetExampleOutputUrl {
url: string;
}
export type WidgetExampleOutput =
| WidgetExampleOutputLabels
| WidgetExampleOutputAnswerScore
| WidgetExampleOutputText
| WidgetExampleOutputUrl;
//#endregion
export interface WidgetExampleBase<TOutput> {
example_title?: string;
group?: string;
/**
* Potential overrides to API parameters for this specific example
* (takes precedences over the model card metadata's inference.parameters)
*/
parameters?: {
/// token-classification
aggregation_strategy?: string;
/// text-generation
top_k?: number;
top_p?: number;
temperature?: number;
max_new_tokens?: number;
do_sample?: boolean;
/// text-to-image
negative_prompt?: string;
guidance_scale?: number;
num_inference_steps?: number;
};
/**
* Optional output
*/
output?: TOutput;
}
export interface WidgetExampleTextInput<TOutput = WidgetExampleOutput> extends WidgetExampleBase<TOutput> {
text: string;
}
export interface WidgetExampleTextAndContextInput<TOutput = WidgetExampleOutput>
extends WidgetExampleTextInput<TOutput> {
context: string;
}
export interface WidgetExampleTextAndTableInput<TOutput = WidgetExampleOutput> extends WidgetExampleTextInput<TOutput> {
table: TableData;
}
export interface WidgetExampleAssetInput<TOutput = WidgetExampleOutput> extends WidgetExampleBase<TOutput> {
src: string;
}
export interface WidgetExampleAssetAndPromptInput<TOutput = WidgetExampleOutput>
extends WidgetExampleAssetInput<TOutput> {
prompt: string;
}
export type WidgetExampleAssetAndTextInput<TOutput = WidgetExampleOutput> = WidgetExampleAssetInput<TOutput> &
WidgetExampleTextInput<TOutput>;
export type WidgetExampleAssetAndZeroShotInput<TOutput = WidgetExampleOutput> = WidgetExampleAssetInput<TOutput> &
WidgetExampleZeroShotTextInput<TOutput>;
export interface WidgetExampleStructuredDataInput<TOutput = WidgetExampleOutput> extends WidgetExampleBase<TOutput> {
structured_data: TableData;
}
export interface WidgetExampleTableDataInput<TOutput = WidgetExampleOutput> extends WidgetExampleBase<TOutput> {
table: TableData;
}
export interface WidgetExampleZeroShotTextInput<TOutput = WidgetExampleOutput> extends WidgetExampleTextInput<TOutput> {
text: string;
candidate_labels: string;
multi_class: boolean;
}
export interface WidgetExampleSentenceSimilarityInput<TOutput = WidgetExampleOutput>
extends WidgetExampleBase<TOutput> {
source_sentence: string;
sentences: string[];
}
//#endregion
export type WidgetExample<TOutput = WidgetExampleOutput> =
| WidgetExampleTextInput<TOutput>
| WidgetExampleTextAndContextInput<TOutput>
| WidgetExampleTextAndTableInput<TOutput>
| WidgetExampleAssetInput<TOutput>
| WidgetExampleAssetAndPromptInput<TOutput>
| WidgetExampleAssetAndTextInput<TOutput>
| WidgetExampleAssetAndZeroShotInput<TOutput>
| WidgetExampleStructuredDataInput<TOutput>
| WidgetExampleTableDataInput<TOutput>
| WidgetExampleZeroShotTextInput<TOutput>
| WidgetExampleSentenceSimilarityInput<TOutput>;
type KeysOfUnion<T> = T extends unknown ? keyof T : never;
export type WidgetExampleAttribute = KeysOfUnion<WidgetExample>;
export enum InferenceDisplayability {
/**
* Yes
*/
Yes = "Yes",
/**
* And then, all the possible reasons why it's no:
*/
ExplicitOptOut = "ExplicitOptOut",
CustomCode = "CustomCode",
LibraryNotDetected = "LibraryNotDetected",
PipelineNotDetected = "PipelineNotDetected",
PipelineLibraryPairNotSupported = "PipelineLibraryPairNotSupported",
}
/**
* Public interface for model metadata
*/
export interface ModelData {
/**
* id of model (e.g. 'user/repo_name')
*/
id: string;
/**
* Kept for backward compatibility
*/
modelId?: string;
/**
* Whether or not to enable inference widget for this model
*/
inference: InferenceDisplayability;
/**
* is this model private?
*/
private?: boolean;
/**
* this dictionary has useful information about the model configuration
*/
config?: Record<string, unknown> & {
adapter_transformers?: { model_class?: string; model_name?: string };
architectures?: string[];
sklearn?: {
filename?: string;
model_format?: string;
};
speechbrain?: {
interface?: string;
};
peft?: {
base_model_name?: string;
task_type?: string;
};
};
/**
* all the model tags
*/
tags?: string[];
/**
* transformers-specific info to display in the code sample.
*/
transformersInfo?: TransformersInfo;
/**
* Pipeline type
*/
pipeline_tag?: PipelineType | undefined;
/**
* for relevant models, get mask token
*/
mask_token?: string | undefined;
/**
* Example data that will be fed into the widget.
*
* can be set in the model card metadata (under `widget`),
* or by default in `DefaultWidget.ts`
*/
widgetData?: WidgetExample[] | undefined;
/**
* Parameters that will be used by the widget when calling Inference API
* https://huggingface.co/docs/api-inference/detailed_parameters
*
* can be set in the model card metadata (under `inference/parameters`)
* Example:
* inference:
* parameters:
* key: val
*/
cardData?: {
inference?:
| boolean
| {
parameters?: Record<string, unknown>;
};
base_model?: string;
};
/**
* Library name
* Example: transformers, SpeechBrain, Stanza, etc.
*/
library_name?: string;
}
/**
* transformers-specific info to display in the code sample.
*/
export interface TransformersInfo {
/**
* e.g. AutoModelForSequenceClassification
*/
auto_model: string;
/**
* if set in config.json's auto_map
*/
custom_class?: string;
/**
* e.g. text-classification
*/
pipeline_tag?: PipelineType;
/**
* e.g. "AutoTokenizer" | "AutoFeatureExtractor" | "AutoProcessor"
*/
processor?: string;
}
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