@huggingface/tasks
Version:
List of ML tasks for huggingface.co/tasks
58 lines (55 loc) • 1.55 kB
text/typescript
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;