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| export declare const MODALITIES: readonly ["multimodal", "nlp", "cv", "audio", "tabular", "rl", "other"]; | |
| export type Modality = (typeof MODALITIES)[number]; | |
| export declare const MODALITY_LABELS: { | |
| multimodal: string; | |
| nlp: string; | |
| audio: string; | |
| cv: string; | |
| rl: string; | |
| tabular: string; | |
| other: string; | |
| }; | |
| /** | |
| * Public interface for a sub task. | |
| * | |
| * This can be used in a model card's `model-index` metadata. | |
| * and is more granular classification that can grow significantly | |
| * over time as new tasks are added. | |
| */ | |
| export interface SubTask { | |
| /** | |
| * type of the task (e.g. audio-source-separation) | |
| */ | |
| type: string; | |
| /** | |
| * displayed name of the task (e.g. Audio Source Separation) | |
| */ | |
| name: string; | |
| } | |
| /** | |
| * Public interface for a PipelineData. | |
| * | |
| * This information corresponds to a pipeline type (aka task) | |
| * in the Hub. | |
| */ | |
| export interface PipelineData { | |
| /** | |
| * displayed name of the task (e.g. Text Classification) | |
| */ | |
| name: string; | |
| subtasks?: SubTask[]; | |
| modality: Modality; | |
| /** | |
| * whether to hide in /models filters | |
| */ | |
| hideInModels?: boolean; | |
| /** | |
| * whether to hide in /datasets filters | |
| */ | |
| hideInDatasets?: boolean; | |
| } | |
| export declare const PIPELINE_DATA: { | |
| "text-classification": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "token-classification": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "table-question-answering": { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| "question-answering": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "zero-shot-classification": { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| translation: { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| summarization: { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "feature-extraction": { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| "text-generation": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "fill-mask": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| }; | |
| "sentence-similarity": { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| "text-to-speech": { | |
| name: string; | |
| modality: "audio"; | |
| }; | |
| "text-to-audio": { | |
| name: string; | |
| modality: "audio"; | |
| }; | |
| "automatic-speech-recognition": { | |
| name: string; | |
| modality: "audio"; | |
| }; | |
| "audio-to-audio": { | |
| name: string; | |
| modality: "audio"; | |
| }; | |
| "audio-classification": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "audio"; | |
| }; | |
| "audio-text-to-text": { | |
| name: string; | |
| modality: "multimodal"; | |
| hideInDatasets: true; | |
| }; | |
| "voice-activity-detection": { | |
| name: string; | |
| modality: "audio"; | |
| }; | |
| "depth-estimation": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "image-classification": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| }; | |
| "object-detection": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| }; | |
| "image-segmentation": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| }; | |
| "text-to-image": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "image-to-text": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| }; | |
| "image-to-image": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| }; | |
| "image-to-video": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "unconditional-image-generation": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "video-classification": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "reinforcement-learning": { | |
| name: string; | |
| modality: "rl"; | |
| }; | |
| robotics: { | |
| name: string; | |
| modality: "rl"; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| }; | |
| "tabular-classification": { | |
| name: string; | |
| modality: "tabular"; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| }; | |
| "tabular-regression": { | |
| name: string; | |
| modality: "tabular"; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| }; | |
| "tabular-to-text": { | |
| name: string; | |
| modality: "tabular"; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| hideInModels: true; | |
| }; | |
| "table-to-text": { | |
| name: string; | |
| modality: "nlp"; | |
| hideInModels: true; | |
| }; | |
| "multiple-choice": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| hideInModels: true; | |
| }; | |
| "text-ranking": { | |
| name: string; | |
| modality: "nlp"; | |
| }; | |
| "text-retrieval": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "nlp"; | |
| hideInModels: true; | |
| }; | |
| "time-series-forecasting": { | |
| name: string; | |
| modality: "tabular"; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| }; | |
| "text-to-video": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "image-text-to-text": { | |
| name: string; | |
| modality: "multimodal"; | |
| }; | |
| "image-text-to-image": { | |
| name: string; | |
| modality: "multimodal"; | |
| }; | |
| "image-text-to-video": { | |
| name: string; | |
| modality: "multimodal"; | |
| }; | |
| "visual-question-answering": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "multimodal"; | |
| }; | |
| "document-question-answering": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "multimodal"; | |
| hideInDatasets: true; | |
| }; | |
| "zero-shot-image-classification": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "graph-ml": { | |
| name: string; | |
| modality: "other"; | |
| }; | |
| "mask-generation": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "zero-shot-object-detection": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "text-to-3d": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "image-to-3d": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "image-feature-extraction": { | |
| name: string; | |
| modality: "cv"; | |
| }; | |
| "video-text-to-text": { | |
| name: string; | |
| modality: "multimodal"; | |
| hideInDatasets: false; | |
| }; | |
| "keypoint-detection": { | |
| name: string; | |
| subtasks: { | |
| type: string; | |
| name: string; | |
| }[]; | |
| modality: "cv"; | |
| hideInDatasets: true; | |
| }; | |
| "visual-document-retrieval": { | |
| name: string; | |
| modality: "multimodal"; | |
| }; | |
| "any-to-any": { | |
| name: string; | |
| modality: "multimodal"; | |
| }; | |
| "video-to-video": { | |
| name: string; | |
| modality: "cv"; | |
| hideInDatasets: true; | |
| }; | |
| other: { | |
| name: string; | |
| modality: "other"; | |
| hideInModels: true; | |
| hideInDatasets: true; | |
| }; | |
| }; | |
| export type PipelineType = keyof typeof PIPELINE_DATA; | |
| export type WidgetType = PipelineType | "conversational"; | |
| export declare const PIPELINE_TYPES: PipelineType[]; | |
| export declare const SUBTASK_TYPES: string[]; | |
| export declare const PIPELINE_TYPES_SET: Set<"other" | "text-classification" | "token-classification" | "table-question-answering" | "question-answering" | "zero-shot-classification" | "translation" | "summarization" | "feature-extraction" | "text-generation" | "fill-mask" | "sentence-similarity" | "text-to-speech" | "text-to-audio" | "automatic-speech-recognition" | "audio-to-audio" | "audio-classification" | "audio-text-to-text" | "voice-activity-detection" | "depth-estimation" | "image-classification" | "object-detection" | "image-segmentation" | "text-to-image" | "image-to-text" | "image-to-image" | "image-to-video" | "unconditional-image-generation" | "video-classification" | "reinforcement-learning" | "robotics" | "tabular-classification" | "tabular-regression" | "tabular-to-text" | "table-to-text" | "multiple-choice" | "text-ranking" | "text-retrieval" | "time-series-forecasting" | "text-to-video" | "image-text-to-text" | "image-text-to-image" | "image-text-to-video" | "visual-question-answering" | "document-question-answering" | "zero-shot-image-classification" | "graph-ml" | "mask-generation" | "zero-shot-object-detection" | "text-to-3d" | "image-to-3d" | "image-feature-extraction" | "video-text-to-text" | "keypoint-detection" | "visual-document-retrieval" | "any-to-any" | "video-to-video">; | |
| //# sourceMappingURL=pipelines.d.ts.map |