| import type { TaskDataCustom } from "../index.js"; | |
| const taskData: TaskDataCustom = { | |
| canonicalId: "text2text-generation", | |
| datasets: [ | |
| { | |
| description: | |
| "News articles in five different languages along with their summaries. Widely used for benchmarking multilingual summarization models.", | |
| id: "mlsum", | |
| }, | |
| { | |
| description: "English conversations and their summaries. Useful for benchmarking conversational agents.", | |
| id: "samsum", | |
| }, | |
| ], | |
| demo: { | |
| inputs: [ | |
| { | |
| label: "Input", | |
| content: | |
| "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. It was the first structure to reach a height of 300 metres. Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct.", | |
| type: "text", | |
| }, | |
| ], | |
| outputs: [ | |
| { | |
| label: "Output", | |
| content: | |
| "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building. It was the first structure to reach a height of 300 metres.", | |
| type: "text", | |
| }, | |
| ], | |
| }, | |
| metrics: [ | |
| { | |
| description: | |
| "The generated sequence is compared against its summary, and the overlap of tokens are counted. ROUGE-N refers to overlap of N subsequent tokens, ROUGE-1 refers to overlap of single tokens and ROUGE-2 is the overlap of two subsequent tokens.", | |
| id: "rouge", | |
| }, | |
| ], | |
| models: [ | |
| { | |
| description: | |
| "A strong summarization model trained on English news articles. Excels at generating factual summaries.", | |
| id: "facebook/bart-large-cnn", | |
| }, | |
| { | |
| description: "A summarization model trained on medical articles.", | |
| id: "Falconsai/medical_summarization", | |
| }, | |
| ], | |
| spaces: [ | |
| { | |
| description: "An application that can summarize long paragraphs.", | |
| id: "pszemraj/summarize-long-text", | |
| }, | |
| { | |
| description: "A much needed summarization application for terms and conditions.", | |
| id: "ml6team/distilbart-tos-summarizer-tosdr", | |
| }, | |
| { | |
| description: "An application that summarizes long documents.", | |
| id: "pszemraj/document-summarization", | |
| }, | |
| { | |
| description: "An application that can detect errors in abstractive summarization.", | |
| id: "ml6team/post-processing-summarization", | |
| }, | |
| ], | |
| summary: | |
| "Summarization is the task of producing a shorter version of a document while preserving its important information. Some models can extract text from the original input, while other models can generate entirely new text.", | |
| widgetModels: ["facebook/bart-large-cnn"], | |
| youtubeId: "yHnr5Dk2zCI", | |
| }; | |
| export default taskData; | |