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File size: 1,425 Bytes
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import type { TaskDataCustom } from "../Types";
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: [
{
description: "",
id: "",
},
],
models: [
{
description: "A powerful feature extraction model for natural language processing tasks.",
id: "facebook/bart-base",
},
{
description: "A strong feature extraction model for coding tasks.",
id: "microsoft/codebert-base",
},
],
spaces: [],
summary:
"Feature extraction refers to the process of transforming raw data into numerical features that can be processed while preserving the information in the original dataset.",
widgetModels: ["facebook/bart-base"],
};
export default taskData;
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