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@huggingface/tasks

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const taskData = { datasets: [ { description: "A common dataset that is used to train models for many languages.", id: "wikipedia", }, { description: "A large English dataset with text crawled from the web.", id: "c4", }, ], demo: { inputs: [ { label: "Input", content: "The <mask> barked at me", type: "text", }, ], outputs: [ { type: "chart", data: [ { label: "wolf", score: 0.487, }, { label: "dog", score: 0.061, }, { label: "cat", score: 0.058, }, { label: "fox", score: 0.047, }, { label: "squirrel", score: 0.025, }, ], }, ], }, metrics: [ { description: "Cross Entropy is a metric that calculates the difference between two probability distributions. Each probability distribution is the distribution of predicted words", id: "cross_entropy", }, { description: "Perplexity is the exponential of the cross-entropy loss. It evaluates the probabilities assigned to the next word by the model. Lower perplexity indicates better performance", id: "perplexity", }, ], models: [ { description: "State-of-the-art masked language model.", id: "answerdotai/ModernBERT-large", }, { description: "A multilingual model trained on 100 languages.", id: "FacebookAI/xlm-roberta-base", }, ], spaces: [], summary: "Masked language modeling is the task of masking some of the words in a sentence and predicting which words should replace those masks. These models are useful when we want to get a statistical understanding of the language in which the model is trained in.", widgetModels: ["distilroberta-base"], youtubeId: "mqElG5QJWUg", }; export default taskData;