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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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01ludolara /DStruct2Designtabular10K<n<100K0 likes805 downloads2y agoHugging Face02liam168 /dstc9text1K<n<10K0 likes85 downloads4y agoHugging Face03jmparejaz /dstc9_GODELtext10K<n<100K0 likes58 downloads4y agoHugging Face04Ywhsheng /DS-test3text10K<n<100K0 likes20 downloads1y agoHugging Face05klusai /ds-tf2-en-ro-15k 🌱 TinyFabulist-TF2-EN-RO-15K TinyFabulist-TF2-EN-RO-15K is a parallel English–Romanian dataset of 15,000 moral fables for benchmarking and training literary translation models, including parameter-efficient fine-tuning for LLMs. It was curated and released by the TinyFabulist team for open research. Dataset Structure Train: 12,000 EN–RO pairs Validation: 1,500 pairs Test: 1,500 pairs Each example is a JSON object with the following fields: language: "en" (source) or… See the full description on the dataset page: https://huggingface.co/datasets/klusai/ds-tf2-en-ro-15k.tabulartranslation10K<n<100K2 likes19 downloads1y agoHugging Face06xentau /dstit STIT Logic Problems (Xu Axiomatization) Dataset Description This dataset contains 1000 synthetically generated problems designed to test logical reasoning capabilities, specifically within the framework of the deliberative 'seeing-to-it-that' (dstit) logic of agency, as axiomatized by Ming Xu (1998) and further analyzed using sequent calculus (G3) in Negri and Pavlović (2020). Each problem presents a scenario involving agents, their actions (or inactions), and… See the full description on the dataset page: https://huggingface.co/datasets/xentau/dstit.text1K<n<10K1 likes15 downloads1y agoHugging Face07kelzla /ds_test1textn<1K0 likes12 downloads3y agoHugging Face08kelzla /ds_test3textn<1K0 likes10 downloads3y agoHugging Face09marcomaccarini /DS_test1text1K<n<10K0 likes8 downloads2y agoHugging Face10kelzla /ds_test4textn<1K0 likes6 downloads3y agoHugging Face11tttx /dstar-1-step1-mastertext1K<n<10K0 likes5 downloads2y agoHugging Face12tttx /dstar-3-step1-slave-0text1K<n<10K0 likes5 downloads2y agoHugging Face13tttx /dstar-4-step1-mastertext1K<n<10K0 likes5 downloads2y agoHugging Face14tttx /dstar-19-step1-mastertext1K<n<10K0 likes5 downloads2y agoHugging Face15kelzla /ds_test2textn<1K0 likes4 downloads3y agoHugging Face16tttx /dstar-6-step1-slave-0text1K<n<10K0 likes4 downloads2y agoHugging Face17tttx /dstar-7-step1-mastertext1K<n<10K0 likes4 downloads2y agoHugging Face18tttx /dstar-10-step1-slave-0text1K<n<10K0 likes4 downloads2y agoHugging Face19tttx /dstar-10-step1-mastertext1K<n<10K0 likes4 downloads2y agoHugging Face20tttx /dstar-16-step1-slave-0text1K<n<10K0 likes4 downloads2y agoHugging Face21tttx /dstar-16-step1-mastertext1K<n<10K0 likes4 downloads2y agoHugging Face22codesj /dstc12_track1_chatevalgatedIf you use this dataset please use the following citation: @inproceedings{mendonca2025dstc12t1, author = "John Mendonça and Lining Zhang and Rahul Mallidi and Luis Fernando D'Haro and João Sedoc", title = "Overview of Dialog System Evaluation Track: Dimensionality, Language, Culture and Safety at DSTC 12", booktitle = "DSTC12: The Twelfth Dialog System Technology Challenge", series = "26th Meeting of the Special Interest Group on… See the full description on the dataset page: https://huggingface.co/datasets/codesj/dstc12_track1_chateval.tabularn<1K0 likes4 downloads1y agoHugging Face23Ywhsheng /DS-test2text10K<n<100K0 likes4 downloads1y agoHugging Face24tttx /dstar-1-step1-slave-0text1K<n<10K0 likes3 downloads2y agoHugging Face25tttx /dstar-2-step1-slave-0text1K<n<10K0 likes3 downloads2y agoHugging Face26tttx /dstar-3-step1-mastertext1K<n<10K0 likes3 downloads2y agoHugging Face27tttx /dstar-4-step1-slave-0text1K<n<10K0 likes3 downloads2y agoHugging Face28tttx /dstar-5-step1-mastertext1K<n<10K0 likes3 downloads2y agoHugging Face29monty1122 /dst-trainingtextn<1K0 likes2 downloads2y agoHugging Face30tttx /dstar-2-step1-mastertext1K<n<10K0 likes2 downloads2y agoHugging Face

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