@huggingface/tasks
Version:
List of ML tasks for huggingface.co/tasks
89 lines (86 loc) • 1.95 kB
text/typescript
import type { TaskDataCustom } from "../index.js";
const taskData: TaskDataCustom = {
datasets: [
{
// TODO write proper description
description: "",
id: "",
},
],
demo: {
inputs: [
{
filename: "image-classification-input.jpeg",
type: "img",
},
{
label: "Classes",
content: "cat, dog, bird",
type: "text",
},
],
outputs: [
{
type: "chart",
data: [
{
label: "Cat",
score: 0.664,
},
{
label: "Dog",
score: 0.329,
},
{
label: "Bird",
score: 0.008,
},
],
},
],
},
metrics: [
{
description: "Computes the number of times the correct label appears in top K labels predicted",
id: "top-K accuracy",
},
],
models: [
{
description: "Multilingual image classification model for 80 languages.",
id: "visheratin/mexma-siglip",
},
{
description: "Strong zero-shot image classification model.",
id: "google/siglip2-base-patch16-224",
},
{
description: "Robust zero-shot image classification model.",
id: "intfloat/mmE5-mllama-11b-instruct",
},
{
description: "Powerful zero-shot image classification model supporting 94 languages.",
id: "jinaai/jina-clip-v2",
},
{
description: "Strong image classification model for biomedical domain.",
id: "microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224",
},
],
spaces: [
{
description:
"An application that leverages zero-shot image classification to find best captions to generate an image. ",
id: "pharma/CLIP-Interrogator",
},
{
description: "An application to compare different zero-shot image classification models. ",
id: "merve/compare_clip_siglip",
},
],
summary:
"Zero-shot image classification is the task of classifying previously unseen classes during training of a model.",
widgetModels: ["google/siglip-so400m-patch14-224"],
youtubeId: "",
};
export default taskData;