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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01mteb /twentynewsgroups-clustering TwentyNewsgroupsClustering.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of the 20 Newsgroups dataset (subject only). Task category t2c Domains News, Written Reference https://scikit-learn.org/0.19/datasets/twenty_newsgroups.html How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["TwentyNewsgroupsClustering.v2"]) evaluator = mteb.MTEB(task)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/twentynewsgroups-clustering.texttext-classificationn<1K1 likes17k downloads1y agoHugging Face02mteb /stackexchange-clustering StackExchangeClustering.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles from 121 stackexchanges. Clustering of 25 sets, each with 10-50 classes, and each class with 100 - 1000 sentences. Task category t2c Domains Web, Written Reference https://arxiv.org/abs/2104.07081 How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/stackexchange-clustering.texttext-classificationn<1K1 likes5.9k downloads7mo agoHugging Face03mteb /arxiv-clustering-s2s ArXivHierarchicalClusteringS2S An MTEB dataset Massive Text Embedding Benchmark Clustering of titles from arxiv. Clustering of 30 sets, either on the main or secondary category Task category t2c Domains Academic, Written Reference https://www.kaggle.com/Cornell-University/arxiv How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["ArXivHierarchicalClusteringS2S"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/arxiv-clustering-s2s.texttext-classificationn<1K1 likes4.1k downloads7mo agoHugging Face04mteb /medrxiv-clustering-s2s MedrxivClusteringS2S.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles from medrxiv across 51 categories. Task category t2c Domains Academic, Medical, Written Reference https://api.medrxiv.org/ How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["MedrxivClusteringS2S.v2"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/medrxiv-clustering-s2s.texttext-classification10K<n<100K1 likes3.9k downloads1y agoHugging Face05mteb /biorxiv-clustering-p2p BiorxivClusteringP2P.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles+abstract from biorxiv across 26 categories. Task category t2c Domains Academic, Written Reference https://api.biorxiv.org/ How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["BiorxivClusteringP2P.v2"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/biorxiv-clustering-p2p.texttext-classification10K<n<100K0 likes3.9k downloads7mo agoHugging Face06mteb /arxiv-clustering-p2p ArXivHierarchicalClusteringP2P An MTEB dataset Massive Text Embedding Benchmark Clustering of titles+abstract from arxiv. Clustering of 30 sets, either on the main or secondary category Task category t2c Domains Academic, Written Reference https://www.kaggle.com/Cornell-University/arxiv How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/arxiv-clustering-p2p.texttext-classificationn<1K3 likes3.6k downloads7mo agoHugging Face07mteb /medrxiv-clustering-p2p MedrxivClusteringP2P.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles+abstract from medrxiv across 51 categories. Task category t2c Domains Academic, Medical, Written Reference https://api.medrxiv.org/ How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["MedrxivClusteringP2P.v2"]) evaluator = mteb.MTEB(task) model =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/medrxiv-clustering-p2p.texttext-classification10K<n<100K3 likes3.1k downloads7mo agoHugging Face08mteb /stackexchange-clustering-p2p StackExchangeClusteringP2P.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of title+body from stackexchange. Clustering of 5 sets of 10k paragraphs and 5 sets of 5k paragraphs. Task category t2c Domains Web, Written Reference https://arxiv.org/abs/2104.07081 How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["StackExchangeClusteringP2P.v2"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/stackexchange-clustering-p2p.texttext-classificationn<1K1 likes2.9k downloads1y agoHugging Face09mteb /reddit-clustering RedditClustering.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles from 199 subreddits. Clustering of 25 sets, each with 10-50 classes, and each class with 100 - 1000 sentences. Task category t2c Domains Web, Social, Written Reference https://arxiv.org/abs/2104.07081 How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["RedditClustering.v2"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/reddit-clustering.texttext-classificationn<1K0 likes2.4k downloads1y agoHugging Face10mteb /biorxiv-clustering-s2s BiorxivClusteringS2S.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of titles from biorxiv across 26 categories. Task category t2c Domains Academic, Written Reference https://api.biorxiv.org/ How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["BiorxivClusteringS2S.v2"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/biorxiv-clustering-s2s.texttext-classification10K<n<100K2 likes1.3k downloads1y agoHugging Face11mteb /reddit-clustering-p2p RedditClusteringP2P.v2 An MTEB dataset Massive Text Embedding Benchmark Clustering of title+posts from reddit. Clustering of 10 sets of 50k paragraphs and 40 sets of 10k paragraphs. Task category t2c Domains Web, Social, Written Reference https://arxiv.org/abs/2104.07081 How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task = mteb.get_tasks(["RedditClusteringP2P.v2"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/reddit-clustering-p2p.texttext-classificationn<1K0 likes406 downloads1y agoHugging Face12ai-forever /georeview-clustering-p2ptext1K<n<10K2 likes198 downloads2y agoHugging Face13slvnwhrl /tenkgnad-clustering-p2pThis dataset can be used as a benchmark for clustering word embeddings for German. The datasets contains news article titles and is based on the dataset of the One Million Posts Corpus and 10kGNAD. It contains 10'275 unique samples, 10 splits with 1'436 to 9'962 samples and 9 unique classes. Splits are built similarly to MTEB's TwentyNewsgroupsClustering. Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation results. If you use this… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/tenkgnad-clustering-p2p.textn<1K0 likes175 downloads2y agoHugging Face14slvnwhrl /blurbs-clustering-s2sThis dataset can be used as a benchmark for clustering word embeddings for German. The datasets contains book titles and is based on the dataset from the GermEval 2019 Shared Task on Hierarchical Classification of Blurbs. It contains 17'726 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to MTEB's ArxivClusteringS2S. Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/blurbs-clustering-s2s.textn<1K0 likes173 downloads2y agoHugging Face15slvnwhrl /tenkgnad-clustering-s2sThis dataset can be used as a benchmark for clustering word embeddings for German. The datasets contains news article titles and is based on the dataset of the One Million Posts Corpus and 10kGNAD. It contains 10'267 unique samples, 10 splits with 1'436 to 9'962 samples and 9 unique classes. Splits are built similarly to MTEB's TwentyNewsgroupsClustering. Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation results. If you use this… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/tenkgnad-clustering-s2s.textn<1K0 likes170 downloads2y agoHugging Face16slvnwhrl /blurbs-clustering-p2pThis dataset can be used as a benchmark for clustering word embeddings for German. The datasets contains book titles and is based on the dataset from the GermEval 2019 Shared Task on Hierarchical Classification of Blurbs. It contains 18'084 unqiue samples, 28 splits with 177 to 16'425 samples and 4 to 93 unique classes. Splits are built similarly to MTEB's ArxivClusteringP2P. Have a look at German Text Embedding Clustering Benchmark (Github, Paper) for more infos, datasets and evaluation… See the full description on the dataset page: https://huggingface.co/datasets/slvnwhrl/blurbs-clustering-p2p.textn<1K0 likes167 downloads2y agoHugging Face17ryzzlestrizzle /multi-wiki-clustering-p2ptextn<1K0 likes152 downloads2y agoHugging Face18lyon-nlp /clustering-hal-s2s Clustering HAL This dataset was created by scrapping data from the HAL platform. Over 80,000 articles have been scrapped to keep their id, title and category. It was originally used for the French version of MTEB, but it can also be used for various clustering or classification tasks, or even evaluate the general knowledge of a model. ⚠️ This dataset contains 2 subsets. IT IS STRONGLY ADVISED TO USE THE CLEANED UP mteb_eval SUBSET: "raw" subset : contains the data originally… See the full description on the dataset page: https://huggingface.co/datasets/lyon-nlp/clustering-hal-s2s.texttext-classification100K<n<1M1 likes128 downloads2y agoHugging Face19UTokyo-Yokoya-Lab /arxiv-clustering-p2p_CS-MTEB ArXiv Clustering P2P CS-MTEB An MTEB dataset Massive Text Embedding Benchmark Code-switching version of mteb/arxiv-clustering-p2p, with sentences rewritten in Chinese-English, Japanese-English, German-English, Spanish-English, Korean-English, French-English, Italian-English, Portuguese-English, Dutch-English code-switching styles. Dataset Structure The dataset contains the following configurations: Code-switching versions: test_zh_en: Chinese-English code-switching… See the full description on the dataset page: https://huggingface.co/datasets/UTokyo-Yokoya-Lab/arxiv-clustering-p2p_CS-MTEB.text100K<n<1M0 likes120 downloads5mo agoHugging Face20jinaai /cities_wiki_clustering WikiCities Clustering Dataset This dataset was created from the (Wikipedia)[https://huggingface.co/datasets/wikipedia] training dataset by using a list of countries, retrieving all cities for each country, and then finding their corresponding Wikipedia article in the Wikipedia dataset. Postprocessing removed the last 25th percentile of countries with fewest city articles, and also took a maximum of 200 articles per country. The final set has a total of 126 countries, and a total of… See the full description on the dataset page: https://huggingface.co/datasets/jinaai/cities_wiki_clustering.textn<1K1 likes88 downloads3y agoHugging Face21PL-MTEB /8tags-clusteringtext1K<n<10K0 likes66 downloads9mo agoHugging Face22PL-MTEB /plsc-clustering-s2stext10K<n<100K0 likes65 downloads2y agoHugging Face23PL-MTEB /plsc-clustering-p2ptext10K<n<100K0 likes56 downloads2y agoHugging Face24thellert /physbert_category_clusteringtext10K<n<100K0 likes39 downloads2y agoHugging Face25Ibisbill /Clustering_deduplicated_reasoning Clustering_deduplicated_reasoning 数据集描述 Clustering deduplicated reasoning data filtered from OpenThoughts2-1M, 77662 examples in total, 10000 examples for each category 文件结构 clustering_deduplicated_reasoning_data_english.jsonl: 主数据文件（JSONL格式） 数据格式 数据集包含以下字段： question: str quality: int difficulty: int topic: str validity: int 使用方法 方法1: 使用datasets库 from datasets import load_dataset # 加载数据集 dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Ibisbill/Clustering_deduplicated_reasoning.texttext-generation10K<n<100K0 likes28 downloads1y agoHugging Face26jinaai /big-patent-clustering Big Patent Clustering Dataset This dataset is created for patent classification. It is derived from the big patent dataset but only contains a subset of the test set of the original dataset. The subsets contain only patents which are assigned to one single category in the original dataset. textn<1K1 likes24 downloads3y agoHugging Face27numsysjp /arxiv-clustering-p2p ArXivHierarchicalClusteringP2P An MTEB dataset Massive Text Embedding Benchmark Clustering of titles+abstract from arxiv. Clustering of 30 sets, either on the main or secondary category Task category t2c Domains Academic, Written Reference https://www.kaggle.com/Cornell-University/arxiv How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: import mteb task =… See the full description on the dataset page: https://huggingface.co/datasets/numsysjp/arxiv-clustering-p2p.texttext-classificationn<1K0 likes18 downloads4mo agoHugging Face28PL-MTEB /plsc-hierarchical-clustering-p2ptext1K<n<10K0 likes17 downloads9mo agoHugging Face29ai-forever /ru-scibench-grnti-clustering-p2ptext10K<n<100K1 likes16 downloads2y agoHugging Face30willhath /french-reddit-clusteringtextn<1K0 likes14 downloads3y agoHugging Face

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