@huggingface/tasks
Version:
List of ML tasks for huggingface.co/tasks
65 lines (62 loc) • 1.75 kB
text/typescript
import type { TaskDataCustom } from "../index.js";
const taskData: TaskDataCustom = {
datasets: [
{
description:
"ImageNet-1K is a image classification dataset in which images are used to train image-feature-extraction models.",
id: "imagenet-1k",
},
],
demo: {
inputs: [
{
filename: "mask-generation-input.png",
type: "img",
},
],
outputs: [
{
table: [
["Dimension 1", "Dimension 2", "Dimension 3"],
["0.21236686408519745", "1.0919708013534546", "0.8512550592422485"],
["0.809657871723175", "-0.18544459342956543", "-0.7851548194885254"],
["1.3103108406066895", "-0.2479034662246704", "-0.9107287526130676"],
["1.8536205291748047", "-0.36419737339019775", "0.09717650711536407"],
],
type: "tabular",
},
],
},
metrics: [],
models: [
{
description: "A powerful image feature extraction model.",
id: "timm/vit_large_patch14_dinov2.lvd142m",
},
{
description: "A strong image feature extraction model.",
id: "nvidia/MambaVision-T-1K",
},
{
description: "A robust image feature extraction model.",
id: "facebook/dino-vitb16",
},
{
description: "Cutting-edge image feature extraction model.",
id: "apple/aimv2-large-patch14-336-distilled",
},
{
description: "Strong image feature extraction model that can be used on images and documents.",
id: "OpenGVLab/InternViT-6B-448px-V1-2",
},
],
spaces: [
{
description: "A leaderboard to evaluate different image-feature-extraction models on classification performances",
id: "timm/leaderboard",
},
],
summary: "Image feature extraction is the task of extracting features learnt in a computer vision model.",
widgetModels: [],
};
export default taskData;