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@huggingface/tasks

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import type { TaskDataCustom } from "../index.js"; const taskData: TaskDataCustom = { datasets: [ { description: "Wikipedia dataset containing cleaned articles of all languages. Can be used to train `feature-extraction` models.", id: "wikipedia", }, ], demo: { inputs: [ { label: "Input", content: "India, officially the Republic of India, is a country in South Asia.", type: "text", }, ], outputs: [ { table: [ ["Dimension 1", "Dimension 2", "Dimension 3"], ["2.583383083343506", "2.757075071334839", "0.9023529887199402"], ["8.29393482208252", "1.1071064472198486", "2.03399395942688"], ["-0.7754912972450256", "-1.647324562072754", "-0.6113331913948059"], ["0.07087723910808563", "1.5942802429199219", "1.4610432386398315"], ], type: "tabular", }, ], }, metrics: [], models: [ { description: "A powerful feature extraction model for natural language processing tasks.", id: "thenlper/gte-large", }, { description: "A strong feature extraction model for retrieval.", id: "Alibaba-NLP/gte-Qwen1.5-7B-instruct", }, ], spaces: [ { description: "A leaderboard to rank text feature extraction models based on a benchmark.", id: "mteb/leaderboard", }, { description: "A leaderboard to rank best feature extraction models based on human feedback.", id: "mteb/arena", }, ], summary: "Feature extraction is the task of extracting features learnt in a model.", widgetModels: ["facebook/bart-base"], }; export default taskData;