Dataset · Hugging Face

mteb/SwednClusteringP2P

Name: SwednClusteringP2P
Creator: mteb
License: cc-by-4.0
Keywords: task_categories:text-classification, annotations_creators:derived, multilinguality:monolingual, source_datasets:sbx/superlim-2, language:swe, license:cc-by-4.0, size_categories:100K<n<1M, format:parquet, modality:text, library:datasets, library:pandas, library:polars, library:mlcroissant, arxiv:2502.13595, arxiv:2210.07316

SwednClusteringP2P An MTEB dataset Massive Text Embedding Benchmark The SWE-DN corpus is based on 1,963,576 news articles from the Swedish newspaper Dagens Nyheter (DN) during the years 2000--2020. The articles are filtered to resemble the CNN/DailyMail dataset both regarding textual structure. This dataset uses the category labels as clusters. Task category t2c Domains News, Non-fiction, Written Reference https://spraakbanken.gu.se/en/resources/swedn… See the full description on the dataset page: https://huggingface.co/datasets/mteb/SwednClusteringP2P.

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Author / organization	mteb
License (as declared)	cc-by-4.0
Downloads	241 (as reported by Hugging Face)
Likes	0
Created	19 June 2025
Last updated at source	24 February 2026

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17 Oct 2026 Description: SwednClusteringP2P An MTEB dataset Massive Text Embedding Benchmark The SWE-DN corpus is based on 1,963,576 news articles from the Swedish newspaper Dagens Nyheter (DN) during the years 2000--2020. The articles are filtered to resemble the → SwednClusteringP2P An MTEB dataset Massive Text Embedding Benchmark The SWE-DN corpus is based on 1,963,576 news articles from the Swedish newspaper Dagens Nyheter (DN) during the years 2000--2020. The articles are filtered to resemble the

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