modified: README.md

new file: pipelines.ts
new file: widget-example.ts

README.md

@@ -9,8 +9,6 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 <details><summary>See axolotl config</summary>
@@ -152,4 +150,4 @@ The following hyperparameters were used during training:
 - Transformers 4.39.0.dev0
 - Pytorch 2.1.2+cu118
 - Datasets 2.18.0
-- Tokenizers 0.15.0
+- Tokenizers 0.15.0

pipelines.ts

@@ -0,0 +1,675 @@
+export const MODALITIES = ["cv", "nlp", "audio", "tabular", "multimodal", "rl", "other"] as const;
+
+export type Modality = (typeof MODALITIES)[number];
+
+export const MODALITY_LABELS = {
+	multimodal: "Multimodal",
+	nlp: "Natural Language Processing",
+	audio: "Audio",
+	cv: "Computer Vision",
+	rl: "Reinforcement Learning",
+	tabular: "Tabular",
+	other: "Other",
+} satisfies Record<Modality, 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;
+	/**
+	 * color for the tag icon.
+	 */
+	color: "blue" | "green" | "indigo" | "orange" | "red" | "yellow";
+	/**
+	 * whether to hide in /models filters
+	 */
+	hideInModels?: boolean;
+	/**
+	 * whether to hide in /datasets filters
+	 */
+	hideInDatasets?: boolean;
+}
+
+/// Coarse-grained taxonomy of tasks
+///
+/// This type is used in multiple places in the Hugging Face
+/// ecosystem:
+///  - To determine which widget to show.
+///  - To determine which endpoint of Inference Endpoints to use.
+///  - As filters at the left of models and datasets page.
+///
+/// Note that this is sensitive to order.
+/// For each domain, the order should be of decreasing specificity.
+/// This will impact the default pipeline tag of a model when not
+/// specified.
+export const PIPELINE_DATA = {
+	"text-classification": {
+		name: "Text Classification",
+		subtasks: [
+			{
+				type: "acceptability-classification",
+				name: "Acceptability Classification",
+			},
+			{
+				type: "entity-linking-classification",
+				name: "Entity Linking Classification",
+			},
+			{
+				type: "fact-checking",
+				name: "Fact Checking",
+			},
+			{
+				type: "intent-classification",
+				name: "Intent Classification",
+			},
+			{
+				type: "language-identification",
+				name: "Language Identification",
+			},
+			{
+				type: "multi-class-classification",
+				name: "Multi Class Classification",
+			},
+			{
+				type: "multi-label-classification",
+				name: "Multi Label Classification",
+			},
+			{
+				type: "multi-input-text-classification",
+				name: "Multi-input Text Classification",
+			},
+			{
+				type: "natural-language-inference",
+				name: "Natural Language Inference",
+			},
+			{
+				type: "semantic-similarity-classification",
+				name: "Semantic Similarity Classification",
+			},
+			{
+				type: "sentiment-classification",
+				name: "Sentiment Classification",
+			},
+			{
+				type: "topic-classification",
+				name: "Topic Classification",
+			},
+			{
+				type: "semantic-similarity-scoring",
+				name: "Semantic Similarity Scoring",
+			},
+			{
+				type: "sentiment-scoring",
+				name: "Sentiment Scoring",
+			},
+			{
+				type: "sentiment-analysis",
+				name: "Sentiment Analysis",
+			},
+			{
+				type: "hate-speech-detection",
+				name: "Hate Speech Detection",
+			},
+			{
+				type: "text-scoring",
+				name: "Text Scoring",
+			},
+		],
+		modality: "nlp",
+		color: "orange",
+	},
+	"token-classification": {
+		name: "Token Classification",
+		subtasks: [
+			{
+				type: "named-entity-recognition",
+				name: "Named Entity Recognition",
+			},
+			{
+				type: "part-of-speech",
+				name: "Part of Speech",
+			},
+			{
+				type: "parsing",
+				name: "Parsing",
+			},
+			{
+				type: "lemmatization",
+				name: "Lemmatization",
+			},
+			{
+				type: "word-sense-disambiguation",
+				name: "Word Sense Disambiguation",
+			},
+			{
+				type: "coreference-resolution",
+				name: "Coreference-resolution",
+			},
+		],
+		modality: "nlp",
+		color: "blue",
+	},
+	"table-question-answering": {
+		name: "Table Question Answering",
+		modality: "nlp",
+		color: "green",
+	},
+	"question-answering": {
+		name: "Question Answering",
+		subtasks: [
+			{
+				type: "extractive-qa",
+				name: "Extractive QA",
+			},
+			{
+				type: "open-domain-qa",
+				name: "Open Domain QA",
+			},
+			{
+				type: "closed-domain-qa",
+				name: "Closed Domain QA",
+			},
+		],
+		modality: "nlp",
+		color: "blue",
+	},
+	"zero-shot-classification": {
+		name: "Zero-Shot Classification",
+		modality: "nlp",
+		color: "yellow",
+	},
+	translation: {
+		name: "Translation",
+		modality: "nlp",
+		color: "green",
+	},
+	summarization: {
+		name: "Summarization",
+		subtasks: [
+			{
+				type: "news-articles-summarization",
+				name: "News Articles Summarization",
+			},
+			{
+				type: "news-articles-headline-generation",
+				name: "News Articles Headline Generation",
+			},
+		],
+		modality: "nlp",
+		color: "indigo",
+	},
+	"feature-extraction": {
+		name: "Feature Extraction",
+		modality: "nlp",
+		color: "red",
+	},
+	"text-generation": {
+		name: "Text Generation",
+		subtasks: [
+			{
+				type: "dialogue-modeling",
+				name: "Dialogue Modeling",
+			},
+			{
+				type: "dialogue-generation",
+				name: "Dialogue Generation",
+			},
+			{
+				type: "conversational",
+				name: "Conversational",
+			},
+			{
+				type: "language-modeling",
+				name: "Language Modeling",
+			},
+		],
+		modality: "nlp",
+		color: "indigo",
+	},
+	"text2text-generation": {
+		name: "Text2Text Generation",
+		subtasks: [
+			{
+				type: "text-simplification",
+				name: "Text simplification",
+			},
+			{
+				type: "explanation-generation",
+				name: "Explanation Generation",
+			},
+			{
+				type: "abstractive-qa",
+				name: "Abstractive QA",
+			},
+			{
+				type: "open-domain-abstractive-qa",
+				name: "Open Domain Abstractive QA",
+			},
+			{
+				type: "closed-domain-qa",
+				name: "Closed Domain QA",
+			},
+			{
+				type: "open-book-qa",
+				name: "Open Book QA",
+			},
+			{
+				type: "closed-book-qa",
+				name: "Closed Book QA",
+			},
+		],
+		modality: "nlp",
+		color: "indigo",
+	},
+	"fill-mask": {
+		name: "Fill-Mask",
+		subtasks: [
+			{
+				type: "slot-filling",
+				name: "Slot Filling",
+			},
+			{
+				type: "masked-language-modeling",
+				name: "Masked Language Modeling",
+			},
+		],
+		modality: "nlp",
+		color: "red",
+	},
+	"sentence-similarity": {
+		name: "Sentence Similarity",
+		modality: "nlp",
+		color: "yellow",
+	},
+	"text-to-speech": {
+		name: "Text-to-Speech",
+		modality: "audio",
+		color: "yellow",
+	},
+	"text-to-audio": {
+		name: "Text-to-Audio",
+		modality: "audio",
+		color: "yellow",
+	},
+	"automatic-speech-recognition": {
+		name: "Automatic Speech Recognition",
+		modality: "audio",
+		color: "yellow",
+	},
+	"audio-to-audio": {
+		name: "Audio-to-Audio",
+		modality: "audio",
+		color: "blue",
+	},
+	"audio-classification": {
+		name: "Audio Classification",
+		subtasks: [
+			{
+				type: "keyword-spotting",
+				name: "Keyword Spotting",
+			},
+			{
+				type: "speaker-identification",
+				name: "Speaker Identification",
+			},
+			{
+				type: "audio-intent-classification",
+				name: "Audio Intent Classification",
+			},
+			{
+				type: "audio-emotion-recognition",
+				name: "Audio Emotion Recognition",
+			},
+			{
+				type: "audio-language-identification",
+				name: "Audio Language Identification",
+			},
+		],
+		modality: "audio",
+		color: "green",
+	},
+	"voice-activity-detection": {
+		name: "Voice Activity Detection",
+		modality: "audio",
+		color: "red",
+	},
+	"depth-estimation": {
+		name: "Depth Estimation",
+		modality: "cv",
+		color: "yellow",
+	},
+	"image-classification": {
+		name: "Image Classification",
+		subtasks: [
+			{
+				type: "multi-label-image-classification",
+				name: "Multi Label Image Classification",
+			},
+			{
+				type: "multi-class-image-classification",
+				name: "Multi Class Image Classification",
+			},
+		],
+		modality: "cv",
+		color: "blue",
+	},
+	"object-detection": {
+		name: "Object Detection",
+		subtasks: [
+			{
+				type: "face-detection",
+				name: "Face Detection",
+			},
+			{
+				type: "vehicle-detection",
+				name: "Vehicle Detection",
+			},
+		],
+		modality: "cv",
+		color: "yellow",
+	},
+	"image-segmentation": {
+		name: "Image Segmentation",
+		subtasks: [
+			{
+				type: "instance-segmentation",
+				name: "Instance Segmentation",
+			},
+			{
+				type: "semantic-segmentation",
+				name: "Semantic Segmentation",
+			},
+			{
+				type: "panoptic-segmentation",
+				name: "Panoptic Segmentation",
+			},
+		],
+		modality: "cv",
+		color: "green",
+	},
+	"text-to-image": {
+		name: "Text-to-Image",
+		modality: "cv",
+		color: "yellow",
+	},
+	"image-to-text": {
+		name: "Image-to-Text",
+		subtasks: [
+			{
+				type: "image-captioning",
+				name: "Image Captioning",
+			},
+		],
+		modality: "cv",
+		color: "red",
+	},
+	"image-to-image": {
+		name: "Image-to-Image",
+		subtasks: [
+			{
+				type: "image-inpainting",
+				name: "Image Inpainting",
+			},
+			{
+				type: "image-colorization",
+				name: "Image Colorization",
+			},
+			{
+				type: "super-resolution",
+				name: "Super Resolution",
+			},
+		],
+		modality: "cv",
+		color: "indigo",
+	},
+	"image-to-video": {
+		name: "Image-to-Video",
+		modality: "cv",
+		color: "indigo",
+	},
+	"unconditional-image-generation": {
+		name: "Unconditional Image Generation",
+		modality: "cv",
+		color: "green",
+	},
+	"video-classification": {
+		name: "Video Classification",
+		modality: "cv",
+		color: "blue",
+	},
+	"reinforcement-learning": {
+		name: "Reinforcement Learning",
+		modality: "rl",
+		color: "red",
+	},
+	robotics: {
+		name: "Robotics",
+		modality: "rl",
+		subtasks: [
+			{
+				type: "grasping",
+				name: "Grasping",
+			},
+			{
+				type: "task-planning",
+				name: "Task Planning",
+			},
+		],
+		color: "blue",
+	},
+	"tabular-classification": {
+		name: "Tabular Classification",
+		modality: "tabular",
+		subtasks: [
+			{
+				type: "tabular-multi-class-classification",
+				name: "Tabular Multi Class Classification",
+			},
+			{
+				type: "tabular-multi-label-classification",
+				name: "Tabular Multi Label Classification",
+			},
+		],
+		color: "blue",
+	},
+	"tabular-regression": {
+		name: "Tabular Regression",
+		modality: "tabular",
+		subtasks: [
+			{
+				type: "tabular-single-column-regression",
+				name: "Tabular Single Column Regression",
+			},
+		],
+		color: "blue",
+	},
+	"tabular-to-text": {
+		name: "Tabular to Text",
+		modality: "tabular",
+		subtasks: [
+			{
+				type: "rdf-to-text",
+				name: "RDF to text",
+			},
+		],
+		color: "blue",
+		hideInModels: true,
+	},
+	"table-to-text": {
+		name: "Table to Text",
+		modality: "nlp",
+		color: "blue",
+		hideInModels: true,
+	},
+	"multiple-choice": {
+		name: "Multiple Choice",
+		subtasks: [
+			{
+				type: "multiple-choice-qa",
+				name: "Multiple Choice QA",
+			},
+			{
+				type: "multiple-choice-coreference-resolution",
+				name: "Multiple Choice Coreference Resolution",
+			},
+		],
+		modality: "nlp",
+		color: "blue",
+		hideInModels: true,
+	},
+	"text-retrieval": {
+		name: "Text Retrieval",
+		subtasks: [
+			{
+				type: "document-retrieval",
+				name: "Document Retrieval",
+			},
+			{
+				type: "utterance-retrieval",
+				name: "Utterance Retrieval",
+			},
+			{
+				type: "entity-linking-retrieval",
+				name: "Entity Linking Retrieval",
+			},
+			{
+				type: "fact-checking-retrieval",
+				name: "Fact Checking Retrieval",
+			},
+		],
+		modality: "nlp",
+		color: "indigo",
+		hideInModels: true,
+	},
+	"time-series-forecasting": {
+		name: "Time Series Forecasting",
+		modality: "tabular",
+		subtasks: [
+			{
+				type: "univariate-time-series-forecasting",
+				name: "Univariate Time Series Forecasting",
+			},
+			{
+				type: "multivariate-time-series-forecasting",
+				name: "Multivariate Time Series Forecasting",
+			},
+		],
+		color: "blue",
+		hideInModels: true,
+	},
+	"text-to-video": {
+		name: "Text-to-Video",
+		modality: "cv",
+		color: "green",
+	},
+	"image-text-to-text": {
+		name: "Image-Text-to-Text",
+		modality: "multimodal",
+		color: "red",
+		hideInDatasets: true,
+	},
+	"visual-question-answering": {
+		name: "Visual Question Answering",
+		subtasks: [
+			{
+				type: "visual-question-answering",
+				name: "Visual Question Answering",
+			},
+		],
+		modality: "multimodal",
+		color: "red",
+	},
+	"document-question-answering": {
+		name: "Document Question Answering",
+		subtasks: [
+			{
+				type: "document-question-answering",
+				name: "Document Question Answering",
+			},
+		],
+		modality: "multimodal",
+		color: "blue",
+		hideInDatasets: true,
+	},
+	"zero-shot-image-classification": {
+		name: "Zero-Shot Image Classification",
+		modality: "cv",
+		color: "yellow",
+	},
+	"graph-ml": {
+		name: "Graph Machine Learning",
+		modality: "other",
+		color: "green",
+	},
+	"mask-generation": {
+		name: "Mask Generation",
+		modality: "cv",
+		color: "indigo",
+	},
+	"zero-shot-object-detection": {
+		name: "Zero-Shot Object Detection",
+		modality: "cv",
+		color: "yellow",
+	},
+	"text-to-3d": {
+		name: "Text-to-3D",
+		modality: "cv",
+		color: "yellow",
+	},
+	"image-to-3d": {
+		name: "Image-to-3D",
+		modality: "cv",
+		color: "green",
+	},
+	"image-feature-extraction": {
+		name: "Image Feature Extraction",
+		modality: "cv",
+		color: "indigo",
+	},
+	other: {
+		name: "Other",
+		modality: "other",
+		color: "blue",
+		hideInModels: true,
+		hideInDatasets: true,
+	},
+} satisfies Record<string, PipelineData>;
+
+export type PipelineType = keyof typeof PIPELINE_DATA;
+
+export type WidgetType = PipelineType | "conversational";
+
+export const PIPELINE_TYPES = Object.keys(PIPELINE_DATA) as PipelineType[];
+
+export const SUBTASK_TYPES = Object.values(PIPELINE_DATA)
+	.flatMap((data) => ("subtasks" in data ? data.subtasks : []))
+	.map((s) => s.type);
+
+export const PIPELINE_TYPES_SET = new Set(PIPELINE_TYPES);

widget-example.ts

@@ -0,0 +1,125 @@
+
+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 ChatMessage {
+	role: "user" | "assistant" | "system";
+	content: string;
+}
+
+export interface WidgetExampleChatInput<TOutput = WidgetExampleOutput> extends WidgetExampleBase<TOutput> {
+	messages: ChatMessage[];
+}
+
+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> =
+	| WidgetExampleChatInput<TOutput>
+	| 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>;