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@huggingface/tasks

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import type { TaskDataCustom } from "../index.js"; const taskData: TaskDataCustom = { datasets: [ { description: "A widely used dataset used to benchmark multiple variants of text classification.", id: "nyu-mll/glue", }, { description: "The Multi-Genre Natural Language Inference (MultiNLI) corpus is a crowd-sourced collection of 433k sentence pairs annotated with textual entailment information.", id: "nyu-mll/multi_nli", }, { description: "FEVER is a publicly available dataset for fact extraction and verification against textual sources.", id: "fever/fever", }, ], demo: { inputs: [ { label: "Text Input", content: "Dune is the best movie ever.", type: "text", }, { label: "Candidate Labels", content: "CINEMA, ART, MUSIC", type: "text", }, ], outputs: [ { type: "chart", data: [ { label: "CINEMA", score: 0.9, }, { label: "ART", score: 0.1, }, { label: "MUSIC", score: 0.0, }, ], }, ], }, metrics: [], models: [ { description: "Powerful zero-shot text classification model.", id: "facebook/bart-large-mnli", }, { description: "Cutting-edge zero-shot multilingual text classification model.", id: "MoritzLaurer/ModernBERT-large-zeroshot-v2.0", }, { description: "Zero-shot text classification model that can be used for topic and sentiment classification.", id: "knowledgator/gliclass-modern-base-v2.0-init", }, ], spaces: [], summary: "Zero-shot text classification is a task in natural language processing where a model is trained on a set of labeled examples but is then able to classify new examples from previously unseen classes.", widgetModels: ["facebook/bart-large-mnli"], }; export default taskData;