const taskData = {
    datasets: [
        {
            description: "A widely used dataset used to benchmark multiple variants of text classification.",
            id: "nyu-mll/glue",
        },
        {
            description: "A text classification dataset used to benchmark natural language inference models",
            id: "stanfordnlp/snli",
        },
    ],
    demo: {
        inputs: [
            {
                label: "Input",
                content: "I love Hugging Face!",
                type: "text",
            },
        ],
        outputs: [
            {
                type: "chart",
                data: [
                    {
                        label: "POSITIVE",
                        score: 0.9,
                    },
                    {
                        label: "NEUTRAL",
                        score: 0.1,
                    },
                    {
                        label: "NEGATIVE",
                        score: 0.0,
                    },
                ],
            },
        ],
    },
    metrics: [
        {
            description: "",
            id: "accuracy",
        },
        {
            description: "",
            id: "recall",
        },
        {
            description: "",
            id: "precision",
        },
        {
            description: "The F1 metric is the harmonic mean of the precision and recall. It can be calculated as: F1 = 2 * (precision * recall) / (precision + recall)",
            id: "f1",
        },
    ],
    models: [
        {
            description: "A robust model trained for sentiment analysis.",
            id: "distilbert/distilbert-base-uncased-finetuned-sst-2-english",
        },
        {
            description: "A sentiment analysis model specialized in financial sentiment.",
            id: "ProsusAI/finbert",
        },
        {
            description: "A sentiment analysis model specialized in analyzing tweets.",
            id: "cardiffnlp/twitter-roberta-base-sentiment-latest",
        },
        {
            description: "A model that can classify languages.",
            id: "papluca/xlm-roberta-base-language-detection",
        },
        {
            description: "A model that can classify text generation attacks.",
            id: "meta-llama/Prompt-Guard-86M",
        },
    ],
    spaces: [
        {
            description: "An application that can classify financial sentiment.",
            id: "IoannisTr/Tech_Stocks_Trading_Assistant",
        },
        {
            description: "A dashboard that contains various text classification tasks.",
            id: "miesnerjacob/Multi-task-NLP",
        },
        {
            description: "An application that analyzes user reviews in healthcare.",
            id: "spacy/healthsea-demo",
        },
    ],
    summary: "Text Classification is the task of assigning a label or class to a given text. Some use cases are sentiment analysis, natural language inference, and assessing grammatical correctness.",
    widgetModels: ["distilbert/distilbert-base-uncased-finetuned-sst-2-english"],
    youtubeId: "leNG9fN9FQU",
};
export default taskData;
