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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 /mteb-example-submissiontextn<1K0 likes187 downloads4y agoHugging Face02lbourdois /MTEB_leaks_and_duplications LLE MTEB This dataset lists the presence or absence of leaks and duplicate data in the datasets constituting the MTEB leaderboard (EN & FR). For more information concerning the methodology and find out what the column names correspond to, please consult the following blog post.To keep things simple, we invite the reader to read the percentages indicated in the text_and_label_test_biased column, which correspond to the proportion of biased data in the test split of the dataset in… See the full description on the dataset page: https://huggingface.co/datasets/lbourdois/MTEB_leaks_and_duplications.textn<1K0 likes81 downloads2y agoHugging Face03robzchhangte /mizo-mteb-retrievaltext100K<n<1M0 likes69 downloads2mo agoHugging Face04b4ph /mlcd-mteb-cifar-eval MLCD vs CLIP on MTEB CIFAR-10/100: integration and evaluation Evaluation results accompanying the MTEB integration of two MLCD image encoders (PR #5406, resolving issue #2571). Two DeepGlint-AI MLCD encoders were integrated into MTEB, verified against the reference implementation, and evaluated on the official MTEB CIFAR-10/CIFAR-100 image-classification tasks alongside size-matched OpenAI CLIP baselines. What was measured Official MTEB image classification: 5… See the full description on the dataset page: https://huggingface.co/datasets/b4ph/mlcd-mteb-cifar-eval.tabularimage-classificationn<1K0 likes57 downloads14d agoHugging Face05projetomemoreba /mteb_ASSIN2_STStabular1K<n<10K0 likes41 downloads3y agoHugging Face06projetomemoreba /mteb_HateBR_offensive_binarytabular1K<n<10K0 likes27 downloads3y agoHugging Face07projetomemoreba /mteb_told-brtabular10K<n<100K0 likes27 downloads3y agoHugging Face08projetomemoreba /mteb_brazilian_court_decisionstabular1K<n<10K1 likes24 downloads3y agoHugging Face09clips /mteb-nl-legalqa This dataset consists of Dutch legislative articles, with queries formulated based on subordinating conjunctions. Citation Information If you find our paper, benchmark or models helpful, please consider cite as follows: @misc{banar2025mtebnle5nlembeddingbenchmark, title={MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch}, author={Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans}… See the full description on the dataset page: https://huggingface.co/datasets/clips/mteb-nl-legalqa.tabulartext-retrieval10K<n<100K0 likes20 downloads1y agoHugging Face10projetomemoreba /mteb_faquadtabularn<1K0 likes16 downloads3y agoHugging Face11mehran-sarmadi /sts_mteb_fstabular1K<n<10K0 likes16 downloads2y agoHugging Face12mehran-sarmadi /our_rerank_mtebtext10K<n<100K0 likes7 downloads2y agoHugging Face13mehran-sarmadi /sts_mteb_ourstabular10K<n<100K0 likes6 downloads2y agoHugging Face

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