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01mteb /cqadupstack-gaming CQADupstackGamingRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Web, Written Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackGamingRetrieval"]) evaluator = mteb.MTEB(task)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-gaming.texttext-retrieval10K<n<100K0 likes6.4k downloads1y agoHugging Face02mteb /cqadupstack-unix CQADupstackUnixRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Web, Programming Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackUnixRetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-unix.texttext-retrieval10K<n<100K0 likes6.3k downloads1y agoHugging Face03clips /beir-nl-cqadupstack Dataset Card for BEIR-NL Benchmark Dataset Summary BEIR-NL is a Dutch-translated version of the BEIR benchmark, a diverse and heterogeneous collection of datasets covering various domains from biomedical and financial texts to general web content. Our benchmark is integrated into the Massive Multilingual Text Embedding Benchmark (MMTEB). BEIR-NL contains the following tasks: Fact-checking: FEVER, Climate-FEVER, SciFact Question-Answering: NQ, HotpotQA, FiQA-2018… See the full description on the dataset page: https://huggingface.co/datasets/clips/beir-nl-cqadupstack.texttext-retrieval100K<n<1M0 likes5.6k downloads2y agoHugging Face04mteb /cqadupstack-physics CQADupstackPhysicsRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Academic, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackPhysicsRetrieval"]) evaluator… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-physics.texttext-retrieval10K<n<100K2 likes1.7k downloads1y agoHugging Face05mteb /cqadupstack-english CQADupstackEnglishRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackEnglishRetrieval"]) evaluator = mteb.MTEB(task)… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-english.texttext-retrieval10K<n<100K1 likes1.6k downloads1y agoHugging Face06mteb /cqadupstack-programmers CQADupstackProgrammersRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Programming, Written, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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/cqadupstack-programmers.texttext-retrieval10K<n<100K0 likes1.2k downloads1y agoHugging Face07mteb /cqadupstack-wordpress CQADupstackWordpressRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Web, Programming Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackWordpressRetrieval"]) evaluator… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-wordpress.texttext-retrieval10K<n<100K2 likes1.1k downloads1y agoHugging Face08mteb /cqadupstack-stats CQADupstackStatsRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Academic, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackStatsRetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-stats.texttext-retrieval10K<n<100K0 likes1.1k downloads1y agoHugging Face09mteb /cqadupstack-gis CQADupstackGisRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Non-fiction Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackGisRetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-gis.texttext-retrieval10K<n<100K3 likes1.1k downloads1y agoHugging Face10mteb /cqadupstack-mathematica CQADupstackMathematicaRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Academic, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackMathematicaRetrieval"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-mathematica.texttext-retrieval10K<n<100K1 likes1k downloads1y agoHugging Face11mteb /cqadupstack-webmasters CQADupstackWebmastersRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Web Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackWebmastersRetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-webmasters.texttext-retrieval10K<n<100K0 likes1k downloads1y agoHugging Face12mteb /cqadupstack-tex CQADupstackTexRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Written, Non-fiction Reference http://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackTexRetrieval"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-tex.texttext-retrieval10K<n<100K1 likes987 downloads1y agoHugging Face13mteb /CQADupstackAndroidRetrieval CQADupstackAndroidRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Programming, Web, Written, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ Source datasets: mteb/cqadupstack-android 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/CQADupstackAndroidRetrieval.texttext-retrieval10K<n<100K0 likes861 downloads11mo agoHugging Face14BeIR /cqadupstack Dataset Card for BEIR Benchmark Dataset Summary BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks. Fact-checking: FEVER, Climate-FEVER, SciFact Question-Answering: NQ, HotpotQA, FiQA-2018 Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus News Retrieval: TREC-NEWS, Robust04 Argument Retrieval: Touche-2020, ArguAna Duplicate Question Retrieval: Quora, CqaDupstack Citation-Prediction: SCIDOCS Tweet Retrieval: Signal-1M… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/cqadupstack.textzero-shot-classification100K<n<1M0 likes483 downloads6mo agoHugging Face15mteb /cqadupstack-android CQADupstackAndroidRetrieval An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Benchmark Data Set for Community Question-Answering Research Task category t2t Domains Programming, Web, Written, Non-fiction Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/ 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(["CQADupstackAndroidRetrieval"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-android.texttext-retrieval10K<n<100K0 likes417 downloads1y agoHugging Face16mteb /CQADupstack-Wordpress-PL CQADupstack-Wordpress-PL An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset Task category t2t Domains Written, Web, Programming Reference https://huggingface.co/datasets/clarin-knext/cqadupstack-wordpress-pl 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(["CQADupstack-Wordpress-PL"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CQADupstack-Wordpress-PL.texttext-retrieval10K<n<100K0 likes78 downloads1y agoHugging Face17GreenNode /cqadupstack-physics-vn 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(["CQADupstackPhysics-VN"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how to run models on mteb task check out the GitHub repitory. Citation If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/cqadupstack-physics-vn.texttext-retrieval10K<n<100K0 likes63 downloads1y agoHugging Face18BeIR /cqadupstack-generated-queries Dataset Card for BEIR Benchmark Dataset Summary BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks: Fact-checking: FEVER, Climate-FEVER, SciFact Question-Answering: NQ, HotpotQA, FiQA-2018 Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus News Retrieval: TREC-NEWS, Robust04 Argument Retrieval: Touche-2020, ArguAna Duplicate Question Retrieval: Quora, CqaDupstack Citation-Prediction: SCIDOCS Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/cqadupstack-generated-queries.texttext-retrieval1M<n<10M1 likes60 downloads4y agoHugging Face19mteb /CQADupstack-Programmers-PL CQADupstack-Programmers-PL An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset Task category t2t Domains Programming, Written, Non-fiction Reference https://huggingface.co/datasets/clarin-knext/cqadupstack-programmers-pl 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(["CQADupstack-Programmers-PL"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CQADupstack-Programmers-PL.texttext-retrieval10K<n<100K0 likes57 downloads1y agoHugging Face20GreenNode /cqadupstack-programmers-vn 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(["CQADupstackProgrammers-VN"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how to run models on mteb task check out the GitHub repitory. Citation If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/cqadupstack-programmers-vn.texttext-retrieval10K<n<100K0 likes55 downloads1y agoHugging Face21mteb /CQADupstack-English-PL CQADupstack-English-PL An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset Task category t2t Domains Written Reference https://huggingface.co/datasets/clarin-knext/cqadupstack-english-pl 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(["CQADupstack-English-PL"]) evaluator = mteb.MTEB(task) model =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CQADupstack-English-PL.texttext-retrieval10K<n<100K0 likes52 downloads1y agoHugging Face22LLukas22 /cqadupstack Dataset Card for "cqadupstack" Dataset Summary This is a preprocessed version of cqadupstack, to make it easily consumable via huggingface. The original dataset can be found here. CQADupStack is a benchmark dataset for community question-answering (cQA) research. It contains threads from twelve StackExchange1 subforums, annotated with duplicate question information and comes with pre-defined training, development, and test splits, both for retrieval and classification… See the full description on the dataset page: https://huggingface.co/datasets/LLukas22/cqadupstack.textsentence-similarity100K<n<1M0 likes51 downloads3y agoHugging Face23Hyukkyu /beir-cqadupstack-mathematica CQADupstackMathematicaRetrieval — BEIR, unified schema A normalised copy of the dataset behind the mteb task CQADupstackMathematicaRetrieval, one of the tasks of the BEIR benchmark as mteb defines it (a member of the aggregate task CQADupstackRetrieval). Same queries, documents and relevance judgements as the benchmark evaluates — reshaped into one strict schema shared by every dataset in this collection. Source mteb/cqadupstack-mathematica @ 90fceea13679 (the… See the full description on the dataset page: https://huggingface.co/datasets/Hyukkyu/beir-cqadupstack-mathematica.texttext-retrieval10K<n<100K0 likes50 downloads18d agoHugging Face24GreenNode /cqadupstack-webmasters-vn 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(["CQADupstackWebmasters-VN"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how to run models on mteb task check out the GitHub repitory. Citation If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/cqadupstack-webmasters-vn.texttext-retrieval10K<n<100K0 likes49 downloads1y agoHugging Face25mteb /CQADupstack-Stats-PL CQADupstack-Stats-PL An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset Task category t2t Domains Written, Academic, Non-fiction Reference https://huggingface.co/datasets/clarin-knext/cqadupstack-stats-pl 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(["CQADupstack-Stats-PL"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CQADupstack-Stats-PL.texttext-retrieval10K<n<100K0 likes48 downloads1y agoHugging Face26BaoLocTown /cqadupstack-programmers-vn-rawtext10K<n<100K0 likes48 downloads2y agoHugging Face27MCINext /cqadupstack-physics-fa Dataset Summary CQADupstack-physics-Fa is a Persian (Farsi) dataset developed for the Retrieval task, with a focus on duplicate question detection in community question-answering (CQA) platforms. This dataset is a translated version of the "Physics" StackExchange subforum from the English CQADupstack collection and is part of the FaMTEB benchmark under the BEIR-Fa suite. Language(s): Persian (Farsi) Task(s): Retrieval (Duplicate Question Retrieval) Source: Translated from… See the full description on the dataset page: https://huggingface.co/datasets/MCINext/cqadupstack-physics-fa.text10K<n<100K0 likes47 downloads1y agoHugging Face28mteb /CQADupstack-Webmasters-PL CQADupstack-Webmasters-PL An MTEB dataset Massive Text Embedding Benchmark CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset Task category t2t Domains Written, Web Reference https://huggingface.co/datasets/clarin-knext/cqadupstack-webmasters-pl 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(["CQADupstack-Webmasters-PL"]) evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CQADupstack-Webmasters-PL.texttext-retrieval10K<n<100K0 likes47 downloads1y agoHugging Face29GreenNode /cqadupstack-android-vn 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(["CQADupstackAndroid-VN"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how to run models on mteb task check out the GitHub repitory. Citation If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/cqadupstack-android-vn.texttext-retrieval10K<n<100K0 likes47 downloads1y agoHugging Face30GreenNode /cqadupstack-mathematica-vn 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(["CQADupstackMathematica-VN"]) evaluator = mteb.MTEB(task) model = mteb.get_model(YOUR_MODEL) evaluator.run(model) To learn more about how to run models on mteb task check out the GitHub repitory. Citation If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/cqadupstack-mathematica-vn.texttext-retrieval10K<n<100K0 likes47 downloads1y agoHugging Face

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